The Mathematical Model of High Voltage Switch as An Element of a Power System

Published by 1. Andriy CZABAN1, 2. Vitaliy LEVONIUK2, 3. Radosław FIGURA1,
Kazimierz Pulaski University of Technology and Humanities in Radom (1), Lviv National Agrarian University (2) ORCID: 1. – 0000-0002-4620-301X; 2. 0000-0003-2113-107X; ; 3. 0000-0001-8048-5623


Abstract. In this work, on the basis of an interdisciplinary method of modelling, a mathematical model of a power system is presented, main element of which system is an gas switch. For modelling of non-mechanical part, a popular theorem on flickering centre of speed of rotation was used. For a mathematical model of an arc, when the resistance was of non-linear nature, a resistive-capacitive alternative diagram was used. The final system of differential equations was presented in a normal cauche form. Results of simulation were given as drawings and were analysed.

Streszczenie. W pracy na podstawie interdyscyplinarnej metody modelowania zaproponowano model matematyczny układu elektroenergetycznego, głównym elementem którego wyłącznik gazowo-elektryczny typu SF6. Dla modelowania części mechanicznej wyłącznika wykorzystano słynny teoremat o migowym centrum prędkości obracania. Dla modelu matematycznego luku wykorzystano rezystancyjno-pojemnościowy schemat zastępczy, gdy rezystancja rozpatrywała się jako funkcja nieliniowa. Końcowy układ równań różniczkowych przedstawiony w normalnej postaci Causze’go. Wyniki symulacji komputerowej podano w postaci rysunków, które analizują się. (Model matematyczny wyłącznika wysokiego napięcia jako elementu układu elektroenergetycznego).

Keywords: high voltage switch, mathematical modelling, the Hamilton-Ostrogradskii principle, the Euler-Lagrange equation.
Słowa kluczowe: wyłącznik wysokiego napięcia, zasada Hamiltona-Ostrogradskiego, równania Eulera-Lagrange’a, nieustalone procesy.

Introduction

Analysis of unsteady electromagnetic processes of complex power systems is extremely important both at the design stage and during exploitation of the said systems, which are elements of one integrated power system.

It is obvious that such systems are characterized with very sophisticated physical processes, for the purpose of analysis of these it is necessary to use complex mathematical model, based on the theory of common differential equations, and sometimes on common equations and partial derivative equations.

Power systems consist of many various components. In order to provide highly adequate mathematical model it a must to describe each of the operating electric devices in details. Depending on the task, attention should be paid to a required device.

This work concentrates on one of the most crucial element of power systems of high voltage – the gas switch. In order to switch long power supply lines on/off, it is the said device that is used. In the course of analysis of unsteady processes of power supply line of high voltage, an important problem occurs, i.e. the necessity to model electric arc processes in switches of high voltage and high voltage. In a general case when current function curve breaks due to contacts opening, an arc is formed, physical principles of which arc are highly complex. These principles are described by plasma theory, electromagnetic field, thermodynamics theory etc. Nowadays, the models of these devices [1] are quite complex and cumbersome. Therefore they are not always acceptable in the analysis of transients in electrical networks.

Another factor to consider is the mechanical processes that occur in the switch when moving the contacts. These processes take as much time as the electromagnetic ones that occur in the switched elements of electrical networks, and therefore can affect the latter.

It is obvious that providing highly adequate mathematical model of the switch requires both use of complex theory and few experts.

Nowadays, SF6 circuit breakers ABB type LTB 362-800 (T) E4 are widely used for switching elements of ultra-high voltage electrical networks on the territory of European Union and in the CIS countries. These switches consist of two modules, each of which has two pairs of series-connected contacts – two fixed and two movable, which are driven by one mechanism for moving the contacts (see Fig. 1). Capacitors are connected in parallel to the contacts for even voltage distribution during switching.

Figure 2 presents proposed simplified kinematic diagram of right side of the mechanism triggering of switch’s contacts. Left side is symmetrical to the right one.

Fig. 1. The mechanism for moving the contacts of the SF6 circuit breaker ultrahigh voltage company ABB type LTB 362-800 (T) E4

Fig.2. Simplified virtual kinematic scheme of replacement of the mechanism of movement of contacts of the switch.

The mentioned mechanism of movement of contacts (see Fig. 1) consists of two crank mechanisms which are symmetrical concerning a longitudinal axis of the whole mechanism. The mechanism is driven by a spring (not shown). These crank mechanisms have a specific design, because the axis of movement of the spring and the axis of movement of the contacts do not coincide with the center of rotation of the mechanism itself. Such crank mechanisms are called deaxial.

We have already built a mathematical model of such a mechanism [2], however, with the high adequacy of this model, it is too cumbersome and difficult to implement as a computer program for the potential user. Therefore, in the present paper, we propose to use a mathematical model of the switch with a simplified kinematic substitution scheme for the analysis of transients in electrical networks with SF6 switches. A comparative analysis of the work of both models showed the convergence of the obtained results by 92%. This gives grounds for the application of a simplified substitution scheme when the calculations do not require high accuracy. The use of a simplified kinematic substitution scheme does not significantly affect the adequacy of the results, but allows to significantly simplify the model of the switch.

In this article, on the basis of variational approaches, we will build a mathematical model of the electrical network, the main element of which is a switch. This approach makes it possible to avoid the decomposition of a unified dynamic system and to obtain the initial equations of the electromagnetic and mechanical state exclusively from a unified energy approach, by constructing an extended Lagrange function [3].

Recent research analysis

Power system problems are often discussed in scientific articles, there are plenty of alike works. Work [4] provides analysis of problems concerning design of mathematical models and macro models of power supply lines with switches. The mathematical model here is developed in the MatLab/Simulink software package. Obtained results are presented.

In [5], the study of electromagnetic transients during the shutdown of short-circuit currents on the 500 kV transmission line with shunt reactors turned on is presented. Here, the model of the switch and other elements of the electrical network is built in the EMTP-RV software package.

In [6] shows the results of researches of the reasons of accidents of SF6 switches during switchings of the compensated power lines of 750 kV. Based on the simulation model developed in the MatLab/Simulink software package, the study of electromagnetic processes in compensated power lines depending on the switching moments is carried out.

In [7] the influence of transient switching processes in power lines on the operational state of the power system was studied. In [8] the transient electromagnetic processes in the power line with shunt reactors during an emergency shutdown due to a short circuit were analyzed. In these works, the study was also carried out in the software package EMTP-RV.

Analysis of the above mentioned works, and numerous articles, make us judge that their authors in the course of modeling transient electromagnetic states neglect mechanical processes in high voltage switches, which are commensurate in duration with electromagnetic, and therefore can affect them. We also see that in the present time the most popular software packages for the study of switching processes are MatLab and EMTP. However, in these systems, the switches are modeled in such a way that the break in the function of the circuit breaker current occurs exclusively at zero, which is not always true.

Based on the above, the aim of this work is a developing of a mathematical model of the ultra-high voltage switch taking into account the simplified kinematic scheme of replacement of the mechanism of moving its contacts to simplify the switch model and analysis of switching transients in electrical network elements.

Fig.3. Power system diagram

Mathematical model of the system

Figure 3 shows part of power grid of high voltage, which part consists of power system (EMF), internal resistance, inductance, high voltage switch, the latest presented as nonlinear active-capacitive components connection, П-alternative diagram of power supply line with concentrated parameters and resistive-inductive load.

We propose to use variational principles for building of mathematical models of electrical network elements, in particular the modified Hamilton-Ostrogradsky principle [3].

For the system we study, the extended action functional by Hamilton-Ostrogradski and its variation will be the following [3]:

.

where S is the action by Hamilton-Ostrograd, L* is the augmented Lagrange function.

Expanded lagrangian of the integrated system is given as follows [3]:

.

where Т~* – kinetic coenergy, P* – potential energy, Φ* – energy dissipation, D* – energy of outside nonpotential forces.

Next, elements of dispersed expanded non-conservative lagrangian is presented:

.

where LS1, LН, LL – system inductances; RS1, RН, RL – system resistances; eS1 – electromotive force; СL1, CL2 – line’s capacities; gL1, gL2 – line’s conductivities; iS1, iН, iL, igL1, igL2 – currents; CV – capacity of contacts capacitor; rD – non-linear resistance of arc; iD – arc’s current; ∆х – spring’s end shift; Vx – spring’s end speed; k – resilience coefficient; kd – spring diffusion coefficient; m – contacts mass reduced to a spring system; FX – arc displacement force reduced to a spring system; Qj – charge of the j-th element; uj – the voltage of the j-th element.

For example, we present a differential equation that describes the transient process of current in an equivalent power system (System, see Fig. 3) based on the principles of variation.

We write the Euler – Lagrange equation [3]

.

where q is the generalizing coordinate; – the speed of the generalizing coordinate. As a generalizing coordinate we take the charge – the speed of the generalizing coordinate

qS1 = QS1, S1 = dqS1/dt = dQS1/dt = iS1.

We should note that in the Euler-Lagrange equation (7) we substitute only the components that relate to the element for which we obtain the equation of the electromagnetic state, since the derivatives of other functions (generalized coordinates) are identically zero, because the latter is not differentiated.

We write the Euler – Lagrange equation (7) taking into account (3) – (6) given that

∂Т* / ∂QS1= uVuCL1.

.

We obtain the equation of the extremals of the Hamilton action functional by changing the order of differentiation (8) and applying the theorem on the derivative of the integral over the upper bound:

.

This way we obtain an equation that describes the current of an equivalent power system:

.

In order to avoid overloading the article with mathematical inferences, we will not reflect the procedure for obtaining the rest of the equations, but only present their final form. You can learn more about the principles of obtaining the equations of such a prolan, for example, in [3, 9]

.

where igL1, igL2 – line leakage; uCL1, uCL2 – line start voltage, line end voltage; uV – voltage between the contacts.

As already mentioned, electric arc resistance rD is nonlinear and it depends on distance between contacts. In order to describe this resistance, it is necessary to know how the resistance is related regarding contacts distance.

On the basis of Fig. 2, the equation takes the following form:

.

Then, referring to the popular theorem on flickering centre of speed, the equation is [10]:

.

On the base (15) and (16) the Vx is calculated by formula:

.

Using (15), angle β is calculated:

.

Next, putting (18) into (17) Vy speed is calculated:

.

Differential equations for finding speed increase will be obtained Δyfakt

.

On the basis of Fig. 2, equations for finding functions Δy and Δxfakt are made

.

In a general case, resistance rD is of exponential nature [11].

Therefore approximation is done using 5-degree polynomial:

.

Dependence (22) initially has a slowly increasing character (simulates arc combustion), and when the contacts diverge by a distance of more than 0.02 m – a sharply increasing nonlinear character (simulates arc attenuation).

Integration is calculated for differential equations: (10) – (12), first equation in (13), (14), (20). This is due to the following second and third equations in (13), (19), (21), (22).

Computer simulation results

Computer simulation of transient states was carried out for power supply line presented in Fig. 3, mechanical processes in high voltage switch of type ABB LTB 362-800 (T) E4 were calculated.

The experience proceeded as follows. The system startup was realised by activating EMF. After reaching transient state (0,18 s) in p. К, symmetrical 3-phase short circuit was triggered. Next, in 0.04 s (time for activation up of relays protection) contacts started to disconnect. The system parameters were: eS1 = 612sin(ωt + 20°) kV, RS1 = 2,032 Ω, LS1 = 0,161 H, RL = 6,85 Ω, LL = 0,333 H, CL1 = CL2 = 0,0000024 F, gL1 = gL2 = 0,0000058 Sm, CV = 400·10-12 F, LH = 0,7 H, RH = 800 Ω, k = 320000 N/m, m = 2,032 kg, kd = 0 Ns/m. The following assumption was adopted: FX = 0 N (arc displacement force not referred to).

Fig.4. Transient switch current

Temporary switch current values are shown at Figure 4. Analysis of the figure let one conclude that for short circuit the surge current is over 7 times higher. Within this time interval, protection system got activated up. Next due to switch operation, the current began to actively drop down and in 0.3 seconds its value was zero. The line got disconnected.

In Fig. 5, voltage between switch’s contacts was presented. It is obvious that in an operating state of the system the voltage value is zero. Next, in the switch activation state, the voltage increases to 750 kV. With contacts disconnection resistance grows, in 0.03 s voltage on contacts equals EMF rated voltage, 630 kV.

Fig.5. Transient voltage between the contacts.

Fig.6. Transient current in power supply line

In Figure 6 transient current in power supply line is presented. It can be observed that in operating state of the system, the maximum current value was 0.9 kА, in short circuit state it was 7 kА. When comparing Figures 4 and 6, a difference is observed, the difference may be a result of complex processes occurring on the line end.

Fig.7. Transient voltage on the right of the switch

Fig.8. Transient voltage on the left of the switch

Figures 7 and 8 are very interesting, they visualize voltage on the right and on the left of the switch. Analysis of the figures leads to the following conclusion: after short circuit on the line end (p. K),the voltage on the line start dropped to 400 kV. After activation/of the switch, voltage on the right dropped down to zero (Fig. 7). As for the second figure (Fig. 8), the case is different. Voltage in a transient state equals system’s EMF.

Fig.9. Switch’s contacts disconnection as a function of time, within time interval [0,2; 0,28] s

Transient disconnection of switch’s contacts within time interval [0,2; 0,28] s shows at Fig. 9. This drawing can be treated as a light theme of this work concept. The approximated curve shows the dependence of arc resistance as a function of the distance of contacts and time. It has been described in the present paper by a mathematical model. This model takes into account the elements that make up the high-voltage circuit breaker.

Conclusions

1. The use of the modified Hamilton-Ostrograd principle gives the possibility to build mathematical models of very complex dynamic objects. Therefore, this method is used to describe electrical power systems.

2. The developed mathematical model of the ultrahigh voltage switch taking into account the virtual simplified kinematic scheme of replacement of the mechanism of movement of contacts, allows to reproduce with a sufficient level of adequacy transient electromagnetic and mechanical processes in the switch taking into account physical principles of switching. In this case, this also applies to the rupture of the current function not only during its transition through zero, but also in a fairly wide time range around zero.

3. The results of the computer simulation presented in this paper fully confirm the theories of transient processes in gas switches, which are complicated high voltage power systems.

REFERENCES

[1] A. Ahmethodžić, M. Kapetanović, and Z. Gajić, «Computer Simulation of High-voltage SF6 Circuit Breakers: Approach to Modeling and Application Results,» IEEE Transactions on Dielectrics and Electrical Insulation, 2011. 18, (4), р. 1314 – 1322.
[2] A. Chaban, A. Szafraniec, and V. Levoniuk, «Mathematical modelling of transient processes in power systems considering effect of high-voltage circuit breakers,» Przeglad elektrotechniczny, 2019. 1, р. 49 – 52.
[3] A. Chaban, «Zasada Hamiltona-Ostrogradskiego w układach elektromechanicznych,» Publisher T. Soroki, Lviv, 2015. (Ukr).
[4] P. Stakhiv, «Discrete mathematical macromodel of electric transmission,» Przegląd Elektrotechniczny, 2013. 4, p. 272-274.
[5] I. Naumkin, M. Balabin, N. Lavrushenko, and R. Naumkin, «Simulation of the 500 kV SF6 circuit breaker cutoff process during the unsuccessful three-phase autoreclosing,» Proceedings of International Conference on power systems Transients, Kyoto, Japan, June 14-17, 2011. р. 5 – 11.
[6] V. Kuchanskyi, «Controlled switching SF6 breakers in the main power electrical grids,» Proceedings of the IED NASU, 2017. 48, р. 38 – 42.
[7] P. Dehghanian, and M. Kezunovic, «Probabilistic impact of transmission line switching on power system operating states,» Proceedings of International Conference on Transmission and Distribution and Exposition (T&D), 2016.
[8] D. Lin, H. Wang, and S. Shen, «An adaptive reclosure scheme for parallel transmission lines with shunt reactors,» Proceedings of International Conference on Transmission and Distribution and Exposition (T&D), 2016.
[9] A. Chaban, V. Levoniuk at all, «Mathematical model of electromagnetic processes in Lehera line at open-circuit operation,» Electrical Engineering & Electromechanics, 2016, 3, p. 30 – 35.
[10] K. Pomorski, «Theoretical mechanics,» Publisher Maria CurieSkłodowska University, Lublin, 2000. (Pol).
[11] V. Sidorets, and I. Pentegov, «Deterministic chaos in nonlinear circuits with an electric arc», Publisher Welding, Kiev, 2013. (Rus).


Authors: dr hab. inż. Andriy Czaban, prof. UTH Rad., University of Technology and Humanities in Radom, Faculty of Transport and Electrical Engineering, ul. Malczewskiego 29, 26-600 Radom, E-mail: atchaban@gmail.com; Ph.D. Vitaliy Levoniyk, Lviv National Agrarian University, Department of Electrical Systems, 1, V. Velykogo str., 80381 Dubliany, Lviv region, Ukraine, E-mail: Bacha1991@ukr.net; assoc. prof., Ph.D Radosław Figura, University of Technology and Humanities in Radom, Faculty of Transport and Electrical Engineering, ul. Malczewskiego 29, 26-600 Radom, E-mail: r.figura@uthrad.pl.


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 97 NR 7/2021. doi:10.15199/48.2021.07.19

Large-Power Synchronous Motor Braking by Field Current

Published by Marian HYLA, Silesian University of Technology, Department of Power Electronics, Electrical Drives and Robotics


Abstract. The paper presents the braking process of a large-power salient-pole synchronous motor forced by field current. The motor control was carried out using a microprocessor block for the excitation of large-power synchronous motors. Cases of free retardation and braking resulting from eddy currents generated in the machine body by the magnetic field of the rotating winding of the rotor with open stator windings were considered. The method proposed was to determine the dependence of braking time on the value of the field current on the basis of the observation of changes in the rotational speed without the knowledge of the parameters of the engine and braking moments of the drive system. The measurement verification of the braking time calculated for the assumed field current has been presented.

Streszczenie. W artykule przedstawiono proces hamowania jawnobiegunowego silnika synchronicznego dużej mocy za pomocą prądu wzbudzenia. Sterowanie silnika zrealizowano za pomocą mikroprocesorowego bloku zasilania wzbudzenia silników synchronicznych dużej mocy. Rozpatrzono przypadek wybiegu swobodnego oraz hamowania na skutek prądów wirowych generowanych w korpusie maszyny przez pole magnetyczne wirującego uzwojenia wirnika przy rozwartych uzwojeniach stojana. Zaproponowano metodę wyznaczania zależności czasu hamowania od wartości prądu wzbudzenia bazującą na obserwacji zmian prędkości obrotowej bez konieczności znajomości parametrów silnika i momentów hamujących układu napędowego. Zaprezentowano weryfikację pomiarową czasu hamowania obliczonego dla założonego prądu wzbudzenia. (Hamowanie silnika synchronicznego dużej mocy prądem wzbudzenia)

Keywords: eddy-current, field current control, synchronous motor braking
Słowa kluczowe: prądy wirowe, regulacja prądu wzbudzenia, hamowanie silnika synchronicznego

Introduction

Large-power synchronous motors are used in industry to drive devices that do not require speed control. Typical applications are the drives of main ventilators in coal mines. The mining regulations in force in Poland require that in each exhaust shaft, in addition to the active main fan or the main fan set, a back-up fan is required , which can be started within 10 minutes [1]. Failure of the main fan and failed start-up of the reserve fan poses a serious threat to the health and life of the employees , and a break lasting more than 20 minutes results in suspension of works and evacuation of workers towards the inspiratory shafts or to the surface [1].

Due to the mass of the fans, reaching several tens of tons, and diameters up to 9 metres, this type of propulsion system is characterized by a high moment of inertia, about 10 times greater than the moment of inertia of the rotor of the propulsion engine. For this reason, coasting times can reach tens of minutes, and the engine can be re-started only after it has been stopped.

It is therefore advisable to shorten the coasting process of motor with braking in order to prepare it for a restart.

Braking methods of large-power synchronous motors

After switching off the motor supply during operation, the rotational speed decreases until it is completely stopped under the influence of the rotary motion resistance forces. The time to stop the motor is strictly dependent on the antitorque moments and the moment of load of the drive system. This method of stopping the motor is often insufficient due to technological reasons as the process lasts relatively long. Therefore other methods are used to accelerate the process of stopping the engine by forced braking.

The motor is braked by converting its kinetic energy into a different kind of energy. During electric braking the kinetic energy is converted into electrical energy and, eventually, into another type of energy, e.g. thermal energy.

In practice, with large-power synchronous motors, dynamic braking is used, in which involves disconnecting the stator windings from the supply network and switching on the resistance into the stator circuit for energy discharging. In order to achieve the most effective braking, relatively large resistances are switched on in the stator circuit, so that the braking from the synchronous speed takes place with the maximum braking torque, and then subsequent stages with appropriately reduced resistance are switched on.

Another method is the use of a mechanical brake placed on the machine shaft and increasing the frictional moment. Mechanical braking is used in solutions where braking reliability is required, even after power failure. This method causes rapid wear of the brake friction covers. For this reason, the mechanical brake is usually used in the final phase of motor braking process at a low shaft speed.

In drive systems with an inverter in the stator circuit, generator braking with the return of energy to the grid is used. By correspondingly reducing the frequency of the motor stator supply voltage, according to the braking ramp that maintains the right angle between the axis of the stator magnetic field and the rotor’s magnetic field, the motor can be braked in a relatively short time. Other electrical braking methods such as counter-current braking, DC braking or single-phase braking are not used in large-power synchronous motors.

Object of the research

The test object was a synchronous motor type GYd-178sp/02 with rated active power 4000 kW, stator voltage 6000 V, stator current 500 A and rotation speed 750 rpm, coupled on a shaft witch two P-1500/10/250/03 type DC generators with rated active power 1750 kW, stator voltage 650 V and stator current 2700 A. During the tests, the synchronous generators were turned off, increasing only the resultant moment of inertia, the moment of friction and the moment of ventilation losses of the entire drive system.

Control of drive operation was carried out by the ProgressPOWER microprocessor block for the excitation of synchronous motors [2] developed in cooperation with the author. The block diagram of the device is shown in Figure 1.

ProgressPOWER excitation power supply block is designed for cooperation with large-power synchronous motors with rated stator voltage 6 kV and excitation current up to 400 A.

The device is managed by a microprocessor system, and implemented algorithms allow to perform asynchronous start-up in classical or starting-choke systems, the control of synchronous operation with the possibility of reactive power or field current regulation, and technological or emergency drive shutdown with energy discharging of the field circuit through inverter operation of the thyristor converter [3], or braking of the motor by field current. The field current control is carried out by a microprocessor system by means of changes in the thyristors switching delay angle of the rectifier that supplies the excitation winding.

Fig.1. Diagram of the synchronous motor control system with microprocessor block for excitation and start-up reactor: M – synchronous motor, WT – thyristor exciter, µP – microprocessor system, PT – thyristor rectifier, UR – start-up system, W – circuit breaker, O – disconnector, WD – choke circuit breaker, DR – inrush choke

In the circuit of the starting resistor, transistor keys were used in the configuration enabling the flow of bidirectional current induced in the field winding during the asynchronous motor start-up. The contactless excitation system allows to increase the reliability and durability of the device.

The microprocessor system, in addition to controlling the current in the excitation circuit, controls the circuit breakers in the 6 kV field, controlling the permissible working area and the state of internal and external protections located, for example, in the switch bay supplying the motor.

A stand-alone operation mode or cooperation with an external, superior control system is available. Cooperation with external devices is carried out through built-in RS-485, USB and Ethernet communication interfaces. Suitable firmware versions enable the device to work with a medium voltage inverter in the synchronous motor stator circuit or control the voltage of the synchronous generator.

Free retardation braking

Figure 2 shows the registered course of the rotational speed of the drive system during free retardation of the synchronous motor. The motor was switched off while running at a synchronous speed, and the braking time was 15 minutes and 26 seconds. The shutdown consisted of opening the stator power switch and quickly discharging the energy of the field circuit by preparing the thyristor bridge to inverter-type work [3].

Fig.2. Speed course during coasting of the motor

The motion equation for the rotating element is as follows

.

where: J – moment of inertia, M – moment affecting the drive system, ω – angular speed.

During the braking process, the load torque M has a negative sign. For an unloaded motor coast, this moment is the sum of the friction torque Mf and the moment of ventilation resistance Mv:

.

where kv – a constant reflecting the influence of rotational speed on the value of the moment of ventilation resistance, hence the equation of motion can be written as

.

and after differentiation, the expression is given for the angular velocity as a function of time

.

After the braking time th the speed ω is 0 (slip s=1), i.e.:

.

Knowing the braking time th, the moment of inertia J can be expressed in the following form

.

and including in (4) the following is obtained

.

simplifying the entry as

.

Equation (7) describes the curve passing through the point A(t=0, s=0) and B(t=th, s=1) of the waveform in Figure 2 (where s – slip corresponding to the speed of rotation) however, such curves are infinitely many depending on the coefficient λ. To determine the coefficient λ, the knowledge of the additional point of ω=f(t) characteristic is required.

Assuming the coordinates of the point C(t=5, s=0.6) for the motor speed curve from Figure 2, the value of the coefficient λ was determined by a numerical method as λ=1.181·10-3 s2, which allows the expression of the curve shape of the braking using the analytical equation without the knowledge of the values of the moment of inertia of the drive system and the moment of friction and ventilation losses.

Equation of the synchronous machine motion

The mathematical model of a salient-pole synchronous machine, due to the magnetic asymmetry of the rotor, is usually presented in the form of a system of equations describing currents, voltages and fluxes expressed in relative units in a d-q system rotating at synchronous speed, supplemented by a motion equation in the following form

.

where: TMmechanical time constant, ψd, ψq – relative rotor magnetic flux linkages in d and q axis, id, iq – relative stator currents in d and q axis, m0 – relative load torque. According to the presented standard mathematical model, with the stator windings open (id=0, iq=0), the braking torque is equal to the moment of load m0, in which the moment of friction and the moment of ventilation losses can be taken into account.

The spinning rotor of a synchronous machine with forced field current generates a magnetic field permeating the stator’s static structure. The magnetic flux, which is variable in the time and space generates loses in the iron, which can be divided into hysteresis losses and eddy-current losses.

Hysteresis losses over one period are proportional to the hysteresis loop area, and are proportional to the frequency of re-magnetization of the iron. For a synchronous machine with forced current flow into the excitation winding, this frequency is related to the rotor speed.

Eddy-current losses are associated with the induction of iron currents due to the changing magnetic field. With sinusoidal flux variability, based on empirical studies by Richter, they are assumed to be proportional to the square of the frequency of changes in the magnetic field.

In a rotating synchronous machine with open armature winding and forced flow of field current, the magnetic flux is greater than the flux in the rated synchronous operating state due to the lack of reaction of the magneto-motive force of the armature, which causes a much greater impact of eddy-currents on the braking torque than in the synchronous state, not included in the standard mathematical model of the synchronous motor.

Braking the motor by field current

Increasing the effectiveness of the motor braking process is possible thanks to the induction of eddy-currents in the stator magnetic circuit due to the flow of current in the rotating field winding.

The general theory of eddy currents is known, and research on eddy-current brakes has been carried out for over 100 years [4-7], using more and more modern techniques recently, e.g. by means of finite element analysis [8, 9]. The main problem in this type of research is the proper determination of the model parameters and the need to adopt some simplifying assumptions.

Fig.3. The speed curves during motor braking for different field current values

The presented method does not require knowledge of the system parameters, and is based on the observation of the course of the rotational speed change during the motor braking process. In addition, it does not require the use of additional braking devices, using the phenomena caused by the flow of current in the rotating field winding with open stator windings.

Figure 3 shows the recorded waveforms during the deceleration process of the tested motor for different values of the field current. For field current If1=150 A, the overrun time has been reduced to 8 minutes 55 seconds and for field current If2=345 A to 3 minutes 12 seconds.

Assuming that the hysteresis losses are proportional to the speed of the magnetic field’s rotation generated by the field current, and the eddy-current losses are proportional to the square of this speed, the motion equation can be represented as

.

where: A, B – constants with unknown values. Differentializing (10) gives an equation describing the angular speed ω as a function of the field current If and coefficients A and B, and additionally it is difficult to determine the friction torque Mf on the basis of the speed during the coasting, which makes it impossible to determine the numerical values of the unknowns even when knowing additional points of registered speed curve.

There are methods to determine the mechanical losses of the drive system [10-12], but they require measurement of other quantities, e.g. power at the moment when the braking procedure starts.

Assuming that the additional braking moment related with the magnetic field from the field current depends on the rotational speed of the rotor and the rotational speed during the braking process depends on time, a correcting element has been introduced into (7), obtaining a dependence in the following form

.

where C and D are unknown constants, and the t/th member takes into account the influence of speed on the additional braking torque related to the current flow in the field circuit.

For the excitation current If1, the rotational speed ω reaches the value 0 after the braking time th1, which considering in (11) allows to save the coefficient C in the following form

.

Equation (12) means that there are infinitely many coefficients C and D that provide the solution.

Taking into account the braking time of the th2 engine with the If2 excitation current, the numerical value of the D coefficient can be determined

.

and next, coefficient C from (12) can be determined too. For the tested drive system these values were determined as C=2.462·10-4 s-1A-D and D=2.333.

The determined coefficients reflect the influence of various phenomena, such as losses on hysteresis and eddy-currents loses, magnetic circuit nonlinearity, parasitic moments and other phenomena difficult to describe in an analytical manner and requiring the adoption of many simplifying assumptions.

Taking into account the determined coefficients C and D in (11), it is possible to determine analytically the field current causing the motor to stop after a given time tx

.

Based on (14), the dependence of the braking time on the field current shown in Figure 4 was determined.

Fig.4. Dependence of the braking time on the field current on the base (14)

Determining the time after which the motor will stop at the given field current, due to the entanglement of time t in (14), is possible only through a numerical calculation process. For the assumed field current If3=400 A, based on (14), the engine stoppage time was determined as 2 minutes 31 seconds. Figure 5 shows the registered motor speed during braking process in such a case. The real braking time was 2 minutes 23 seconds.

Fig. 5. Recorded motor speed during braking at 400 A field current
Conclusions

Using the braking moments generated from the eddy-currents in the machine body generated by the flow of current in the rotating field winding of the rotor, the motor braking time can be significantly reduced without the use of additional braking devices. It is also possible to quite accurately estimate the field current causing the drive to stop within the set time without knowing the magnetic and mechanical parameters of the system. The presented method of determining the influence of the field current on the course of the synchronous motor braking process does not require knowledge of the motor parameters, and at the same time allows to take into account the influence of real phenomena in the motor stator magnetic circuit, which are associated with the interaction of the rotating magnetic field generated by the current in the field winding.

The considerations concerned the coasting and braking of the synchronous motor non-loaded by the braking torque of driven device. The braking torque of the driven device causes the motor to stop in an even shorter time, but regardless of this, the maximum reduction of the braking time will be achieved at the maximum permissible field current. But it should be taken into account that the current flow through the field winding causes losses in this winding, resulting in an increase of its temperature , simultaneously the reduction of the speed of rotation causes the ventilation and cooling of the winding to become less effective.

The tests carried out with the motor and the microprocessor block for excitation [2] confirmed the possibility of controlling the motor braking time with the help of the field current. The application of the field current control system regardless of the state of the motor operation makes the braking procedure effective even after an emergency power off and opening of the stator windings.

REFERENCES

[1] Decree by the Minister of Economy from 28 June 2002 on occupational health and safety, mining operations and fire protection in underground mines, Republic of Poland Journal of Law from 2002, No 139, item 116 9 and from 2006, No 124, item 863
[2] Hyla M.: Power supply unit for the excitation of a synchronous motor with a reactive power regulator, Mining – Informatics, Automation and Electrical Engineering, vol. 53, no. 1, pp. 17-21, 2015
[3] Hyla M.: Wybrane aspekty sterowania tyrystorową wzbudnicą silnika synchronicznego (in Polish, abstract in English), 5th Conf. Modelling and Simulation, Kościelisko, 2008, pp. 345–348
[4] Morris D. K., Lister G. A.: The eddy current brake for testing motors, Journal of the Institution of Electrical Engineers, vol.35, no. 175, pp. 445-468, 1905
[5] Davies E. J.: General theory of eddy-current couplings and brakes, Proceedings of the Institution of Electrical Engineers, vol. 113, no. 5, pp. 825-837, 1966
[6] Gonen D., Stricker S.: Analysis of an Eddy-Current Brake, IEEE Transactions on Power Apparatus and Systems, vol. 84, no. 5, pp. 357-361, 1965
[7] Venkataratnam K., Kadir M. S. A.: Normalized Force-Speed Curves of Eddy Current Brakes with Ferromagnetic Loss Drums, IEEE Transactions on Power Apparatus and Systems, vol. PAS-104, no. 7, pp. 1789-1796, 1985
[8] Holtmann C., Rinderknecht F., Friedrich H. E.: Simplified model of eddy current brakes and its use for optimization, 10th Int. Conference on Ecological Vehicles and Renewable Energies (EVER), Monte Carlo, 2015, pp. 1-8
[9] Sinmaz A., Gulbahce M. O., Kocabas D. A.: Design and finite element analysis of a radial-flux salient-pole eddy current brake, 9th Int. Conf. on Electrical and Electronics Engineering (ELECO), Bursa, 2015, pp. 590-594
[10] Ilina I. D.: Experimental determination of moment to inertia and mechanical losses vs. speed, in electrical machines, 7th Int. Symposium on Advanced Topics in Electrical Engineering (ATEE), Bucharest, 2011, pp. 1-4
[11] Ćalasan M., Ostojić M., Petrović D.: The retardation method for bearings loss determination, Int. Symposium on Power Electronics Power Electronics, Electrical Drives, Automation and Motion, Sorrento, 2012, pp. 25-29
[12] Ćalasan M. P., Petrović D. S., Ostojić M. M.: Electrical braking of synchronous generators for combined generator and water turbine bearings as well as stray-load losses determination, IET Electric Power Applications, vol. 7, no. 4, pp. 313-320, 2013


Autor: dr inż. Marian Hyla, Silesian University of Technology, Faculty of Electrical Engineering, Department of Power Electronics, Electrical Drives and Robotics, ul. B. Krzywoustego 2, 44-100 Gliwice, Poland, e-mail: marian.hyla@polsl.pl


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 11/2020. doi:10.15199/48.2020.11.04

Influence of Environmental Exposures on Electrical Parameters of Low Voltage Surge Arresters

Published by Piotr PAJĄK1, Bartłomiej SZAFRANIAK1, Anna DĄDA2, AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering (1), MGGP S.A., Krakow Branch (2)


Abstract. Low voltage surge arresters work in a very different environmental conditions. During the exploitation, under the influence of environmental exposures, the structure of metal oxide surge arresters (MOSA) is gradually degraded. These processes can change their protective properties and lead to a reduction in the effectiveness of surge protection. The aim of the paper is to analyze the influence of environmental exposures on the electrical parameters of low voltage surge arresters.

Streszczenie. Warunki środowiskowe w jakich pracują niskonapięciowe ograniczniki przepięć są bardzo zróżnicowane. Podczas eksploatacji, pod wpływem narażeń środowiskowych, struktura ograniczników przepięć ulega stopniowej degradacji. Procesy te mogą powodować zmiany parametrów elektrycznych ograniczników i prowadzić do zmniejszenia skuteczności ochrony przeciwprzepięciowej. Celem referatu jest analiza wpływu narażeń środowiskowych na parametry elektryczne niskonapięciowych ograniczników przepięć. Analiza wpływu narażeń środowiskowych na parametry elektryczne niskonapięciowych ograniczników przepięć

Keywords: metal oxide surge arresters, impedance spectroscopy, water immersion, leakage current.
Słowa kluczowe: beziskiernikowe ograniczniki przepięć, spektroskopia impedancyjna, degradacja pod wpływem wilgoci, prąd upływowy

Introduction

The main purpose of using surge arresters is to protect the insulation of devices from significant voltage increases that may occur in the power system. Reliable operation of the surge arresters and preservation of reduced voltage values declared by manufacturers within a long time is required in order for this protection to be effective. Surge arresters are exposed to many environmental factors during their exploitation, which directly affect the operating parameters, advance their ageing and in extreme cases may damage them. Current stroke, high temperature, moisture penetration and salt contamination are these negative impact factors. Substantial penetration of moisture in combination with high air pollution, significantly advance the degradation of surge arresters, decreasing the protective voltages of the varistor and with an avalanche way increase in leakage current, they can even lead to its damage [1].

The basic element of sparkless surge arresters are varistors made of zinc oxide (ZnO) with additions of other metal oxides, Bi2O3, CoO, MnO, Sb2O3 among others. The varistors are resistors whose resistance depends on the voltage applied to them. The material from which the varistors are made is properly prepared – first ground and homogenized, and then pressed and sintered at high temperatures. The end result of such a technological process is a polycrystalline structure with unique properties. The basic element of the varistor’s microstructure is grain, which should be characterized by appropriate size, homogeneity and low resistivity. The formation of grain microstructure, occurring at the stage of production processes, determines the creation of current paths in the varistor. The current flowing through the varistor is the sum of partial currents flowing through its structure through various paths. Paths with fewer borders are led by larger currents. Voltage drops in a given varistor sector depend on the number of intergranular borders, which is directly influenced by the amount and size of grains. The total voltage drop on the varistor results from the equalization of voltages by varying the leakage currents [2].

The chemical composition and suitably selected parameters of the varistor manufacturing process allow for the shaping of their strongly nonlinear current-voltage characteristics (U = C · Iβ; V – voltage, I – current, C – constant, β – nonlinearity coefficient) [3, 4].

The mechanism of current conduction on the varistor is related to phenomena occurring at the boundaries between grains. At the interface of neighboring grains there are potential barriers resulting from the electric charge accumulated on the boundary surfaces. In the characteristics of the dependence of the electric field intensity on the value of varistor current density E = f (J), three clearly distinct ranges can be distinguished (Fig. 1): pre-breakdown range (normal operation range), breakdown range (stabilization range) and saturation range [5].

Fig.1. The characteristics of the electric field intensity dependence on the current density [4]

Varistors are usually made in the form of cylindrical disks of various diameters and thicknesses. They are closed in sealed enclosures designed to protect against external factors, in particular against moisture (Fig. 2a, 2b). The geometrical dimensions of the varistor are related to the assumed value of the discharge current (diameter, surface area of the disk), the operating voltage (thickness of the disk) and its ability to absorb energy (disk volume) [6]. Typically, the ZnO grain diameter is a few micrometers (Fig. 2c).

Diagnostic tests of surge arresters are carried out at all stages of their technical life. They are based on various evaluation methods, for example on visual inspection, thermovision studies, or on the measurement of electrical parameters, performed at both constant and alternating voltages. The energy (overvoltage) and environmental (physicochemical) exposures occurring in operation lead to changes in the internal structure and various types of damage to the arresters [6].

Fig.2. A low voltage metal-oxide varistor as the main element of the surge protection device (SPD): a) example of the low voltage SPD design, b) manufactured disk varistors, c) the microscopic level varistor structure

Research Program

This work contains tests and analysis of the results performed on a series of low voltage surge arresters with similar parameters produced by two different manufacturers. Four samples were selected for observing the parameters of the tested arresters, two samples of object A and two samples of object B. The analysis of the results is to determine the permissible dispersion in which the monitored parameters may be contained. The tests were performed on surge arresters designed for installation in low voltage aerial power transmission networks. Their technical parameters are listed in table 1.

Table 1. Selected parameters of tested SPD

.

All presented measurements were made in High Voltage Laboratory of Electrical and Power Engineering Department of AGH University of Science and Technology in Krakow, Poland. Surge arresters were tested with the following procedure:

Impedance spectroscopy

The impedance spectroscopy method was used to observe changes in the dielectric properties of the tested surge arresters. This is a test method used to determine the physical and chemical properties of materials and electrochemical processes. It consists in measuring the linear, electrical response of the tested object as a result of stimulation with a small electromagnetic signal in a wide frequency band. Small voltage induction allows treating the tested element, in this case the surge arrester as a linear element. The measuring instrument depending on the impedance frequency Z(ω) is the frequency response analyzer (FRA). This device generates a stimulation of a specific shape and selects individual points on the frequency scale. An impedance spectrum is created from the measured current responses at selected frequencies. The current flowing through the tested object is combined with two synchronous, orthogonal reference signals (cosωt and sinωt), one of which corresponds to an trigger signal.

Fig.3. Configuration of a laboratory stand for measuring dielectric parameters of tested surge arresters: 1) wideband impedance measurement system (Solartron 1260 + 1296); 2) surge arrester

The characteristics of the relative permittivity εr and the dielectric loss coefficient tgδ were registered depending on the frequency f for all samples, in no way previously operated or subjected to laboratory exposures. The measurements were carried out over a wide range of frequencies, from 10-2 Hz to 104 Hz. The measuring station was equipped with a Solartron 1260A frequency response analyzer, Solartron 1296A dielectric interface and a supervising computer (Fig. 3).

Electrometer – recording of the leakage current waveform

In order to performed detailed diagnostic, it is particularly important to analyze the pre-breakdown range of surge arresters, because this is the state of their normal operation. Then, a leakage current flows through the arrester. Measurement of this current enables the technical condition of arrester to be evaluated. Observation of the value and shape of the leakage current is often used to assess the operation of surge arresters [7-10].

The tested surge arresters were connected in such a way that the measurement only includes the cross-current component of the leakage current. The surface current was shielded – the arresters were placed in a copper band which was grounded.

The leakage currents waveforms were recorded over time, all samples were subjected to the experiment. The measurement took place for one minute at constant voltage 308V, which is the highest value of the operating voltage. The measurements were carried out using an electrometer from the B2987A series of Keysight Technologies.

Exposure to moisture and salt solutions

Surge arresters were combined into two pairs. Each pair is a object A surge arrester and a object B surge arrester. In order to imitate the actual environmental conditions to which devices are subjected during exploitation, each pair of arresters has been drenched in the following liquids: water and 5% NaCl solution. Ageing was executed at an ambient temperature of 23°C to 25°C and lasted 600h. Each time, after another 150 hours of ageing, before the next tests, the surge arresters were dried.

Results and Analysis of Measurements

The article presents the results of testing low voltage surge arresters. Tests were performed using the impedance spectroscopy method. This is one of the nondestructive testing methods that can be used for diagnostic of ZnO varistors. The obtained test results are presented in the following figures (Fig.4 – Fig.7).

Fig.4. The influence of water immersion on ageing of the object A parameters: a) dependence of relative permittivity on frequency εr(f), b) the dependence of the dielectric loss factor on the frequency tgδ(f)

Fig.5. The influence of water immersion on ageing of the object B parameters: a) dependence of relative permittivity on frequency εr(f), b) the dependence of the dielectric loss factor on the frequency tgδ(f)

The analysis of impact of ageing based on the εr and tgδ wideband characteristics shows gradual growth of these parameters’ values. That effect has been observed within the range of low frequencies for all surge arresters. It was also found that the reaction of surge arresters within the same voltage group, immersed in a 5% NaCl solution, is different. Strong growth of object A surge arresters’ tgδ can be observed at the frequency range of kHz’s whereas this parameter does not change for object B surge arresters at the same range of frequency.

Fig.6. The influence of 5% NaCl immersion on ageing of the object A parameters: a) dependence of relative permittivity on frequency εr(f), b) the dependence of the dielectric loss factor on the frequency tgδ(f)

Fig.7. The influence of 5% NaCl immersion on ageing of object B parameters: a) dependence of relative permittivity on frequency εr(f), b) the dependence of the dielectric loss factor on the frequency tgδ(f)

Fig.8. The influence of immersion in water on leakage current of the arresters for 308V: a) object A b) object B

Fig.9. The influence of immersion in 5% NaCl solution on leakage current of the arresters for 308V: a) object A b) object B

Tested surge arresters have reached similar values of leakage currents. That value is influenced by the relatively short ageing time and lack of raised temperature. Nevertheless, the moisture penetration into arresters’ interior increases the leakage current. In the example of object A, it can be observed that the leakage current values grow with time, and the differences between respective waveforms are greater while immersed in a 5% NaCl solution. In the case of object B, these differences are not so significant.

The voltage–current characteristics of metal oxide varistors depend on moisture content at low current, in the vicinity of continuous operating voltage [11]. Greater leakage current of surge arresters immersed in 5% NaCl solution in relation to immersion in water was observed. The changes are more significant for the arresters manufactured by object A than object B, which means that they are much more sensitive to moisture impact. The use of this type of arresters in environments with significant contamination and salinity may cause major difficulties in maintaining the stability of the requested parameters.

Summary and Conclusions

Based on the results, moisture penetration into arresters interior is confirmed. The impact of immersion in water and in a 5% NaCl solution on the surge arresters’ parameters was already noticeable, despite the relatively short ageing period. It points out that a deterioration of their technical condition ensued.

There are visible changes in the shape of wideband characteristics as a result of the surge arresters’ ageing test. Within the range of low frequencies, the εr and tgδ characteristics reach the higher values along with the length of ageing time, as well as for immersion in water and in 5% NaCl solution. Tgδ(f) characteristics indicate an significant increase in the conductivity losses at low frequencies.

The impact of moisture penetration into varistors’ interior is also visible on obtained leakage currents waveforms. Surge arresters aged in 5% NaCl solution show higher values of leakage current compared to an analogous test in water. The values of these currents are different for various series of arresters used within the same voltage group. Analysis of appearances occurring during the ageing processes is an additional source of information on the mechanism of current conduction in the varistor.

REFERENCES

[1] Wanderley Neto E. T., Da Costa E. G., Ferreira T. V., Maia M. J. A., Failure Analysis in ZnO Arresters Using Thermal Images, IEEE PES Transmission and Distribution Conference and Exposition Latin America, Venezuela, (2006)
[2] Mielcarek W., Uwarunkowania technologiczne warystorów tlenkowych, Prace Instytutu Elektrotechniki, Zeszyt nr 212, Warszawa, (2002)
[3] Chrzan K. L., High-Voltage Surge Arresters, Wrocław, Dolnośląskie Wydawnictwo Edukacyjne publishing company, (2003)
[4] Flisowski Z., High Voltage Technology, Warszawa, PWN publishing company, (2017), 226–234
[5] Florkowska B., Furgał J., Zydroń P., Materials Engineering in Electrical Engineering. Laboratory, AGH issues, Kraków, (2012), 72–80
[6] Bonk M., Fusnik Ł., Szafraniak B., Zydron P., Influence of temperature and high-energy stresses on selected wideband characteristics of metal-oxide varistor parameters, Proc. 9th Int. Sci. Symp. Electr. Power Eng. Elektroenergetika 2017, (2017), 306–310
[7] Biglar B., Jayaram S., Cherney E. A., Evaluation of the insulation design of polymer housed surge arresters using saltfog test, 2000 Conference on Electrical Insulation and Dielectric Phenomena, (2000), 385–388
[8] Da Silva D. A., Costa E. C. M., Pissolato J., De Jesus R. C., De Franco J. L., De Abreu S. R., Romano M. A. A., Lahti K., Evaluation of the moisture ingress and the electrical performance on polymeric surge arresters of distribution networks, 18th International Symposium on High Voltage Engineering, (2013), 349–354
[9] Silva D. A., Costa C. M., Franco J. L., Abreu S. R., Jesus R. C., Antonionni M. , Pissolato J., Polymer Surge Arresters: Degradation Versus Electrical Performance, (2012)
[10] Dalai S., Chatterjee B., Study on the effect of moisture ingression into metal oxide surge arrester using leakage current analysis, 3rd International Conference on Condition Asstessment Techniques in Electrical Systems (CATCON), (2017), 330–334
[11] Chrzan K. L., Influence of moisture and partial discharges on the degradation of high-voltage surge arresters, European Transactions on Electrical Power, Euro. Trans. Electr. Power 2004, (2004), No. 14, 175-184


Authors: dr inż. Piotr Pająk, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland, E-mail: ppajak@agh.edu.pl, mgr inż. Bartłomiej Szafraniak, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland, E-mail: szafrani@agh.edu.pl, mgr inż. Anna Dąda, MGGP S.A., Cracow Branch, e-mail: annadada0709@gmail.com


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 1/2020. doi:10.15199/48.2020.01.14

Application of Multi-Stage Window Comparator Circuit with Safety Mode for Swell Voltage Control in Low Voltage Systems

Published by Saktanong WONGCHAROEN, Sansak DEEON, Pathumwan Institute of Technology, Thailand


Abstract. This article presents the application of a multi-stage window comparator circuit with safety mode for swell voltage control in low voltage systems that lack stability and electrical quality. High-voltage transistors were used to build a simple voltage detecting circuit with multi-stage functions and electronic load to detect and control swell voltage . SVSS as the overloaded energy receptor resulted in clamping voltage. The voltage of a device is equal to the voltage flowing to smart electronic loads and not over the IEEE 1159 and 1100 standards. The device worked normally without causing damages. Failure Mode and Effect Analysis (FMEA) might occur using a multi-stage window comparator circuit in the safety mode. The reliability and stability in detecting voltage and controlling electronic loads to work safely under many kinds of situations were also assessed.

Streszczenie. W artykule zaprezentowano wykorzystanie komparatorów do kontroli zwiększonego napięcia w systemach niskiego napięcia. Napięcie nie przekracza zaleceń norm IEEE 1159 i 1100. Zastosowanie kaskadowych komparatorów w trybie bezpieczeństwa do kontroli spiętrzenia napięcia w systemach niskonapię1)ciowych

Keywords: window comparator multi-stage, Failure Modes and Effects Analysis (FMEA), Swell Voltage Surge Suppressor (SVSS)
Słowa kluczowe: komparatory kaskadowe, analiza zakłóceń pracy układu, przepięcvia.

Introduction

Advancement of electronic technology has resulted in many innovations that facilitate and improve the lives of people. For example, information and knowledge can be easily accessed by connecting to the internet, building smart homes, smart grids, solar PV rooftops [1] and smart farms. Smart electronic devices are now connected to the distribution system in the Provincial Electricity Authority (PEA). These advanced technological electronic devices have sensitivity towards noise. Quality problems of electricity systems or swell voltage cause damages to smart electronics used in the household as seen in Fig. 1.

Fig.1. Effect from swell voltage resulting in the damages of Electronic devices

Problems of electric quality are often found in rural areas caused by lighting, switched capacitors, system maintenance, use of nonlinear devices, incorrect ground system and use of inconsistent technology in the electrical system [2-3]. These problems promote changes in electrical quality. If the devices have sensitivity towards the response this might cause failure or malfunction. Although many systems have Surge Protection Devices (SPDs) for AC surge [4-7], damage to electronic devices still occurs as seen in Fig. 1. Damages from the change of electrical quality or swell voltage occur when RMS voltage exceeds IEEE 1159 and 1100 standards [8-9] (Fig. 2). Installation of SPDs in low-voltage systems [10] cannot prevent swell voltage lower than the working level of the device, resulting in damages to smart electronic machinery. This is a big problem for electrical quality of distribution systems in PEA. Apart from the damages, swell voltage also impacts users. As a result, analysis and improvement of electrical quality must adhere to real situations of specific areas in the country.

Fig.2. Voltage Reduction Standard of IEEE Std 1159-1995

This article presents the concepts of application of a multi-stage window comparator circuit with safety mode for swell voltage control in low voltage systems through the development of a Swell Voltage Surge Suppressor (SVSS) to reduce damages to smart electronic devices conducted to distribution systems in PEA. Design of a multi-stage window comparator circuit with safety mode using high-voltage transistors [11-14] enhances the endurance of the circuit towards high voltage systems and prevents failure, resulting in improved circuit reliability.

Basic Window Comparator Circuit

Window comparator circuits (WCs) often used are IC Op-Amp, Logic gate, IC packet, IC CMOS and TTL [15-18]. The window comparator circuit type IC has low input voltage and current. It is suitable for analysing small signals. If devices inside the IC are damaged or lack qualification, the circuit will not work or work abnormally. For these IC devices, characteristics of damages inside the circuit cannot be examined. The window comparator circuit has different low-voltage levels (VLow) and high-voltage levels (Vhigh). This qualification is called Hysteresis and is used to detect the signal as the designed function. If the analogue input (Vin) is in the range of standardised electrical level, the output signal will be 1 (High). However, apart from this condition, signal output will be 0 (Low).

Window Comparator Circuit with Transistors

After the IC window comparator circuits have been applied to detect the overvoltage [19], this might damage the devices inside IC. The use of transistors in the design of window comparator circuits is important [12-14]. Today, semi-conductors have been developed for use at higher voltage. Application of high-voltage transistors with VCE ±300V of KSP42 and KSP92 transistors in the design can be adapted for other uses. Oscillator circuits made from a pair of transistors are used in window comparator design (Fig. 3). When Vin is higher than Vref_L (Vin>Vref_L), the transistor Q1 works (on) with electricity flowing through Q1, resulting in clamping voltage at R3 (VR3). The resistors, R4 and R5, are voltage divider circuits. They control the function of low voltage (Vref_L) as seen in the equation.

.

When Vin has voltage higher than Vref_H (Vin>Vref_H), the transistor Q2 will work (on) while the resistors, R1 and R2, which are voltage divider circuits, control the function of low voltage (Vref_H). When the transistor Q2 works and enters saturation, the output signal Vout =0V as seen in the equation.

.
Fig.3. Window Comparator Circuit with Transistors

Application of a window comparator circuit requires expansion of the output signal to make the output signal logic become 0 (OFF) or 1 (ON). When Vin is at the specified level, the voltage Vout at the Q3 transistor’s base is around 0.7V, resulting in electricity flowing and the clamping voltage Vce of the Q3 transistor is 0V. The Q4 transistor will not work (IC =0). Therefore, the transistor works like a switch in an open circuit or in the cut-off state, causing clamping Vce(cut-off) at the Q4 transistor equal to Vo and VP as seen in the equation.

.

When Vin is outside the standard voltage level, the voltage at the Q3 transistor’s base will be lost, causing flow of electricity (IC=0). The clamping voltage has R6 equal to ICR6, resulting in voltage at the Q4 transistor’s base while the electricity IC flows to the high position resulting in clamping voltage Vce=0V. Therefore, the transistor works like a switch in a closed circuit or in saturation state as seen in equation.

Fig.4. Window Comparator Circuit with Extended Circuit

In Fig. 4, Vp is the output voltage that can control the voltage level of electronic loads. Characteristics of the output signal of a window comparator circuit with Q3 and Q4 transistors work like a switched circuit. When the signal of Vin in the windows of Vref_L and V ref_H is according to the set function as seen in Fig. 5, the output signal remains High (ON). If Vin is outside of Vref_L and V ref_H, the output signal will be Low (OFF) as seen in the equation.

.
Fig.5. Comparison of output signals of the window comparator circuit

To make it simple, a block diagram similar to Op-amp was drawn with single input and output. This means 1 Opamp symbol is equal to 1-stage window comparator circuit or WCS-1 as seen in Fig. 6.

From Fig. 6, set the function of window comparator with four resistors: R1, R2, R3, and R4, connecting in the voltage divider circuit as R1 and R2 to control the function of Vref_H while R3 and R4 control the function of Vref_L. To create the signal channel of the window comparator, the difference between voltage level Vref_L and Vref_H will be called hysteresis voltage or Vhyst [18]. This could cause a change of voltage level at two positions as seen in Fig. 7. Consequently, to calculate Window Comparator Hysteresis, the voltage level should be set to eliminate the swing of the input signal Vin due to error or noise as the equation below.

.
Fig.6. Functionality of Window Comparator
Fig.7. Output Signal of Window Comparator with Hysteresis

Multi-stage Window Comparator Circuit

A multi-stage window comparator can set multi ranges of voltage level to assess the difference between Vref_L-N and Vref_H-N when an analog output signal Vin is added into the system. If it is from WCS-1 to WCS-N as the regulated function, the output signal from Vo-1 to Vo-N of any stage will be 1. Apart from this condition, the output signal will be 0 as seen in Fig. 8.

Fig.8. Multi-stage Window Comparator Circuit

Fig. 8 demonstrates the overview of the multi-stage window comparator circuit. When used to detect swell voltage, it will assist by dividing the violent level of swell voltage that enters the low voltage system. Selection of device, resistor and transistor in the circuit must be endurable. The working function must be examined and failure mode analysed to check the abnormality of physical characteristics.

Principle of Swell Voltage Control

Swell voltage control by a Swell Voltage Surge Suppressor (SVSS) can be used as the electronic load that receives overvoltage in the system [20-21]. There are four sets of window comparator circuits for detecting swell voltage. Each set has a different window level. WCS-1 first detects the swell voltage. If Vin shares the same value as the window’s voltage of WCS-1, the output signal Vo1 becomes 1. When Vin rises to reach the window levels of WCS-2, WCS-3 or WCS-4, then one of the output signals at Vo2, Vo3 or Vo4 is 1. All three sets work under the window level of WCS-1 as seen in Fig. 9.

Fig.9. Multi-stage Window Comparator Circuit and Output Signal

In Fig. 9, the electronic load controlled by the multi-stage window comparator circuit will work when Vin shares the same window level as WCS-1. The output signal Vo1 will force the switch of Solid-state Relay (SSR) [22] to activate (on) and when the voltage of Vin is equal to the window level of WCS-2 ,WCS-3 or WCS-4, it will cause Leakage Current (LC1) through electronic loads M1, M2 or M3, which connect in parallel. If the device at M1 level becomes damaged and the voltage Vin continues to increase, M2 and M3 still work. M1, M2, and M3 are electronic device type Power MOSFET. Here, selected SCT3080KL MOSFET with voltage between Drain– Source could reach 1,200V. It is an electronic lead that works as the energy supporter and could be compared to a load in the system. The use of MOSFET enhances the endurance of the electronic circuit to be safer, more constant and prevent dangerous failure that might occur in the system. When Vin is lower, the window comparators WCS-2 , WCS-3 or WCS-4 will cause M1, M2 or M3 to stop working, while they are working under WCS-1, until the voltage is lower than WCS-1. It also causes the SSR to stop working (off). The electricity IC1 ceases to flow. Characteristics of electronic load control of M1, M2, and M3 have different voltage control level. This affects the flow of electricity through electronic loads and helps to control the loaded voltage at the standard level in accordance with IEEE Std 1159 and IEEE Std 1100.

The multi-stage window comparator for swell voltage control with RMS over the standard (230V ±10%) [8-9] will be installed parallel to the power system. The swell voltage causes electricity to flow through the first rectifier circuit, which is the voltage sensor (VSS), while the resistors R1 and R2 connect to the voltage divider circuit to reduce the voltage to remain at the appropriate level. The received Vin will be added to the window comparators WCS-1 WCS-2 WCS-3, and WCS-4 respectively, as seen in equation.

.
Fig.10. Multi-stage Window Comparator Circuit for Swell Voltage Control

From Fig. 10, the voltage detector circuit by the window comparator with the safe mode will examine the voltage Vin. If Vin follows the condition, the output signals Vo1, Vo2, Vo3 or Vo4 will control electronic loads in accordance with the overvoltage level in the system. The electronic load control circuit will supply electricity and control voltage, resulting in clamping voltage at the electronic loads as seen in the equation.

.

If drawing the block diagram by replacing SVSS as the resistor load (REL), when removing the sensitive load out of the circuit, it is evident that REL makes the series with the resistant (ZS) of the power distribution source by dividing from the voltage at VSVSS. As seen in Fig. 11, the electronic load pulls the power current ICl to flow through itself as a means to preserve the voltage level, VSVSS ≅ VL that is distributed to the load to remain level and not over the standard as seen in the equation.

.

The electronic load is similar to the resistor load connecting to the AC source, resulting in swell voltage and swell current as seen in the equation.

.
Fig.11. Connection of electronic loads by dividing the voltage from the power source

To calculate the clamping voltage of the electronic load circuit, see the equation.

.

For consideration of the power of electronic loads in the AC power system during the electricity flow due to swell voltage, the multiple results of voltage and short current, see the equation.

.

Table 1. Result of Failure Modes and Effects Analysis of the created Window Comparator Circuit

.

Notes *(0.5) and *(2) referred from the standard measurement. (a): Normal Output (b): No Output (c): window Voltage reduced (d): window Voltage increase (e): Output as Vp (f): Half reduction output Δ : no significant consequences of SVSS

Analytical Result of The Window Comparator’s Safe Mode Circuit

Failure Modes and Effects Analysis (FMEA) [23-26] is the indicator in analysis of the safe failure of the window comparator that leads to prevention of damages. The principle of the analysis has been standardised and the result confirms that the window comparator circuit will work with the safe mode. If there is any dangerous failure with any device in the window comparator or the four sets, SVSS will stop working immediately and will not cause any dangerous failure to the system. See Table 1.

Testing Result of Swell Voltage Control

The SVSS device was tested for swell voltage control [27-29] by connecting to the top the system before distributing the voltage at 280V, 290V, 300V, 310V, 320V, 330V, 340V and 350V [20-21] and measuring the signal wave of clamping voltage at the output as seen in Fig. 12 and Fig. 13.

Fig.12. Testing the SVSS Circuit for Swell Voltage Control
Fig.13. Measurement of the model SVSS by Oscilloscope

The wave of the output signal of the multi-stage window comparator was measured for electronic load control by adding the triangle-wave signal to test its function. When the voltage reached the destined level, the output signal through the windows Vo1, Vo2, Vo3, and Vo4 to control the electronic loads in accordance with the overvoltage. See Fig. 14 and Fig. 15.

Fig.14. Output signal of multi-stage window comparator for SVSS control

The distributed AC current was at 280-350V and the frequency was 50 Hertz. The wave of the signal to test the size of overrated voltage is shown in Fig. 16. The test applied an oscilloscope to measure the signal wave of current and clamping voltage at the output before recording (Table 2).

Fig.15. Input and Output Signals of multi-stage window comparator for SVSS control
Fig.16. Testing the signal of 320V
Fig.17. Input and Output signal of SVSS for Swell Voltage Control
Fig.18. Frontal expansion of swell voltage control

Fig. 17 shows the distributed overvoltage in the system. The signal detected CH1 as the signal wave of swell voltage and CH3 as the output signal from the window comparator with V01 as the signal forcing M1 CH4 as the output signal from the window comparator with V04 as the signal forcing M2, and CH2 as the wave of electric current ICl flowing through the electronic loads for swell voltage control. as seen in Fig. 18 and Fig. 19.

Fig.19. Rear expansion of swell voltage control

Table 2. SVSS Test Results for Swell Voltage Level Control

.
Fig.20. Graph showing the relationship between voltage test and clamping voltage
Fig.21. Graph showing the relationship between voltage test and leakage current
Fig.22. Graph showing the relationship between transient power loss and voltage test

Data were demonstrated in the graph as the relationship between voltage, electric current and electric power of SVSS for swell voltage control as seen in Fig. 20, Fig. 21 and Fig. 22 respectively.

Conclusion

This article demonstrated the multi-stage window comparator circuit as safe for swell voltage control in low voltage systems. Problems are caused by the quality and stability of the power system and might affect smart electronic devices conducted on distribution systems in PEA. The design of swell voltage level control contains the main circuit as the window comparator circuit with safe mode to detect the overvoltage level from the high-voltage transistor, with the purpose of enhancing the endurance of high-voltage. It also reduces the effect of dangerous failure in the system. The created window comparator circuit can detect voltage level and control electronic loads with safe mode. The FMEA result based on IEC 61496-1 standard, assured the working process of the device to be reliable and stable to control safety under many kinds of situations. The testing result showed that SVSS for swell voltage level control was effective by allowing the electric current to flow through itself, resulting in reduction of voltage level. The current moving through smart electronic devices was not over the standards of IEEE Std 1159 and IEEE Std 1100.

REFERENCES

[1] SB. Kjaer, JK. Pedersen, and F. Blaabjerg, “A review of single-phase grid-connected inverters for photovoltaic modules,” in IEEE Transactions on Industry Applications, 41(2005), 1292–1306
[2] D. O. Johnson, K. A. Hassan. “Issues of Power Quality in Electrical Systems,” International Journal of Energy and Power Engineering, 5 (2016), No. 4, 148-154
[3] J. Kaniewski, “Transformator hybrydowy z dwubiegunowym przekształtnikiem AC/AC bez magazynu energii DC,” Przegląd Elektrotechniczny, ISSN 0033-2097, 94 (2018), nr 5, 80-85
[4] V. Radulovic, S. Mujovic, and Z. Miljanic, “Characteristics of Overvoltage Protection with Cascade Application of Surge Protective Devices in Low-Voltage AC Power Circuits,” Advances in Electrical and Computer Engineering, 15 (2015), No. 3, 153-160
[5] IEEE Std C62.41.1-2002, IEEE Guide on the Surge Environment in Low-Voltage (1000 V and Less) AC Power Circuits, April 2003.
[6] P. Hasse, Overvoltage Protection of Low Voltage Systems, 2nd ed. United Kingdom: The Institution of Electrical Engineers, 2000.
[7] D. Paul, “Low-voltage power system surge overvoltage protection,” in IEEE Transactions on Industry Applications, 37 (2001), 223-229
[8] IEEE Std 1159-2009, IEEE Recommended Practice for Monitoring Electric Power Quality, November 2009.
[9] IEEE Std 1100-2005, IEEE Recommended Practice for Powering and Grounding Electronic Equipment, December 2005.
[10] Z. He and Y. Du, “SPD Protection Distances to Household Appliances Connected in Parallel,” in IEEE Transactions on Electromagnetic Compatibility, 56 (2014), No. 6, 1377-1385
[11] E. J. Wade, and D. S. Davidson, “Application of Transistors to Safety Circuits,” in IRE Transactions on Nuclear Science, 5 (1958), No. 2, 44-46
[12] K. Futsuhara, and M. Mukaidono, “Application of Window Comparator to Majority Operation,” in The Nineteenth International Symposium on Multiple-Valued Logic, (1989), 114-121
[13] K. Futsuhara, and M. Mukaidono, “A Realization of Fail-safe Sensor Using Electromagnetic Induction,” in Conference on Precision Electromagnetic Measurements CPEM, (1988), 99-100
[14] M. Sakai, M. Kato, K. Futsuhara, and M. Mukaidono, “Application of Fail-safe Multiple-valued Logic to Control of Power Press,” in 1992 Proceedings The Twenty-Second International Symposium on Multiple-Valued Logic, (1992), 271-350
[15] P. Sagar, P. P. R. Madhava, “A Novel, High Speed Window Comparator Circuit,” in 2013 International Conference on Circuits, Power and Computing Technologies (ICCPCT), (2013), 691-693
[16] M.W.T. Wong, and Y. Zhang, “Design and Implementation of Self-Testable Full Range Window Comparator,” in Proceedings of the 13th Asian Test Symposium (ATS2004), (2004), 1-5
[17] S. Maheshwari, “Current Conveyor Based Window Comparator Circuits,” Advances in Electrical Engineering, (2016), 1-8
[18] V. A. Pedroni, “Low-voltage high-speed Schmitt trigger and compact window comparator,” in Electronics Letters, 41 (2005), No. 22, 1213-1214
[19] Y. Zhang and M.W.T. Wong, “Self-Testable Full Range Window Comparator,” in IEEE Region 10 Conference TENCON 2004, (2004), 262-265
[20] N. Mungkung, S. Wongcharoen, C. Sukkongwari, and S. Arunrungrasmi, “Design of AC Electronics Load Surge Protection,” in International Journal of Electrical, Computer, and Systems Engineering, ISSN 1307-5179, 1 (2007), No. 2, 126-131
[21] N. Mungkung, S. Wongcharoen, K. Chomsuwan, P. Nuchuay, K. Permsupsin and T. Yuji, “Electronics Load for Voltage Swell Protection,” in Conference on Embedded Systems and Intelligent Technology, (2008), 303-307
[22] R. N. Eldine, I. Amor, A. Massoud, and L. B. Brahim, “Smart Low Voltage ac Solid State Circuit Breakers for Smart Grids,” in Global Journal of Advanced Engineering Technologies, 2 (2013), No. 3, 71-79
[23] IEC Std 60812-2018, Failure modes and effects analysis (FMEA and FMECA), 3th ed. IEC International Standard, July 2018.
[24] C. Summatta, W. Khamsen, A. Pilikeaw and S. Deeon, “Design and Simulation of Relay Drive Circuit for Safe Operation Order,” in Conference on Mathematics, Engineering & Industrial Applications 2016 (ICoMEIA 2016), August 2016.
[25] S. Deeon, Y. Hirao, K. Tanaka, “A Relay Drive Circuit for a Safe Operation Order and its Fail-safe Measures,” in The Journal of Reliability Engineering Association of Japan, 34 (2012), No.7, 489-500
[26] S. Deeon, Y. Hirao and K. Futsuhara, “A Fail-safe Counter and its Application to Low-speed Detection,” in The Journal of Reliability Engineering Association of Japan, 33 (2011), No.3, 135-144
[27] IEC Std 61496-1, Safety of machinery-Electro-sensitive protective equipment-Part 1: General requirements and tests, IEC International Standard, April 2012.
[28] IEEE Std C62.41.1-2002, IEEE Guide on the Surge Environment in Low-Voltage (1000 V and Less) AC Power Circuits, April 2003.
[29] IEC Std 6100-4-5-2014, Electromagnetic Compatibility (EMC), Part 4-5, Testing and measurement techniques, Surge immunity test, IEC International Standard, June 2014.


Authors: Mr. saktanong wongcharoen, E-mail: saktanong.w@gmail.com; Dr. Sansak Deeon, E-mail: sdeeon2013@gmail.com. Department of Electrical Engineering, Pathumwan Institute of Technology, 833 Rama1 Wangmai District, Bangkok, Thailand;


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 5/2020. doi:10.15199/48.2020.05.17

Faults Detection in PMSM Drive using Artificial Neural Network

Published by Konrad URBAŃSKI, Dariusz MAJCHRZAK,Poznań University of Technology


Abstract. In this paper, simulation research results of PMSM drive with open phase fault detection are presented. Proposed fault detection system is implemented using two artificial neural networks. One of them is neural model of healthy PMSM and another one generates diagnostic signals. When the fault occurs, the amplitude of current residuals increases and evaluation system returns diagnosis. In proposed system detection time is about 1 ms. Moreover, diagnosis does not depend on load state.

Streszczenie. Artykuł przedstawia wyniki badań symulacyjnych napędu PMSM z detekcją przerwy fazy. Proponowany system detekcji uszkodzeń zaimplementowano z użyciem dwóch sztucznych sieci neuronowych. Jedna z nich pełni rolę modelu neuronowego sprawnego PMSM, natomiast druga generuje sygnały diagnostyczne. W przypadku wystąpienia uszkodzenia amplituda residuów prądów wzrasta, a system ewaluacji zwraca diagnozę. Czas detekcji w przedstawionym układzie jest rzędu 1 ms. Ponadto działanie systemu nie zależy od stanu obciążenia (Detekcja uszkodzeń w napędzie z PMSM przy użyciu Sztucznej Sieci Neuronowej).

Keywords: Artificial Neural Network, PMSM, Fault detection, Electric drive.
Słowa kluczowe: Sztuczna Sieć Neuronowa, PMSM, Detekcja uszkodzeń, Napęd elektryczny.

Introduction

The permanent magnet synchronous motors (PMSM) are becoming increasingly popular in industry due to their high power density, low inertia and high efficiency. Thanks to their excellent dynamic performance, they are widely used in robots, machine tool, winders and similar systems that require precise speed and torque control. Nowadays, electrical drives often work in human life-critical systems, where high reliability is required [1]. In these applications the traditional control algorithms do not provide a sufficient safety, so fault tolerant control (FTC) is commonly used. FTC algorithms require information about type and location of fault [2], therefore the fault detection and diagnosis systems are necessary. There are many methods of fault detection and identification. They can be divided into signal processing based and model-based categories. First of them uses measured signals analysis methods such as spectral analysis [3] or wavelet transform [4]. In general, they only uses output signals of drive, but no input signals, so influence of input on output may be ignored [5]. Mode-based methods use information about structure and parameters of dynamic model of plant. These include state estimation methods, for example observers or Extended Kalman Filter [6]. Moreover, model parameters estimation methods like recursive last square algorithm can be used [7]. Model-based methods generate residuals, by estimating output signals (or parameters of the plant) and computing estimation error vector [8]. Next the residual evaluation system generates diagnosis. Fig. 1 presents the block diagram of model-based method of fault detection. Symbols shown in Fig. 1 are u – plant inputs, y – plant outputs, z – disturbance, f – fault, and r – generated residuals. The main disadvantage of mentioned methods is the need for a reliable model [5]. In this paper, fault detection method based on model is connected with computational intelligence methods. Presented in this paper the residual generator contains neural model of PMSM. Moreover, the residual evaluation system is also realized using the Artificial Neural Network (ANN).

Mathematical model and control structure

Dynamic model of PMSM used in this paper is given as follows:

.
Fig.1. Block diagram of model-based fault detection system
.

where id, iq,Ld, Lq, vd, vq – currents, inductances and voltages in d-q axes, R – winding resistance, p – pole pairs, ωr – angular speed of rotor, λ – permanent magnets flux linkage, Te – electromagnetic torque, J – moment of inertia, F – viscous friction coefficient, Tm – load torque, ϴ – rotor angular position.

Used control algorithm was Field Oriented Control (FOC) [9]. Clarke and Park transforms were used for 3 phase non-rotating frame into two coordinate rotating reference frame conversions. PI controllers were used in speed and currents control loops. Transistors gate pulses were generated using Space Vector Pulse Width Modulation (SVPWM) [9]. The block diagram of control structure is shown in Fig. 2.

Fig.2. Block diagram of Field Oriented Control with Space Vector Pulse Width Modulation

Fault detection method

The main blocks of the system are neural model of PMSM and diagnostic module. The inputs of the both networks are phase currents, phase voltages, speed and the motor shaft position. In addition, the current residuals vector is given to the input of the diagnostic block, which returns the diagnosis. The output of the system is diagnostic signal which indicates open phase fault occurrence. The block diagram of the system is presented in Fig. 3.

Fig.3. Block diagram of neural fault detection system

In the figure, ϴ is the position, and ω is the speed. For increase of residual signal magnitude during open phase fault, in place of measured currents the weighted arithmetic mean of estimated and measured currents was applied. Used coefficients was experimentally determined and was 0.8 for estimated and 0.2 for measured values. The tapped delay line (TDL), delays voltages, speed and position samples by 0, 1 and 2 steps. It also delays currents by 1 and 2 steps. In practical applications the phase voltages are not measured. To avoid implementation of extra sensors the reference voltages can be used. In that approach system processes variables that are already used by vector control algorithm.

Signals acquired from the several simulations of healthy motor drive, working at various speeds and loads were used for training the neural model. Residual evaluation system was trained on data obtained during open phase fault simulations. A fault trigger signals were used as a target data. Neural model consists two-layer feed-forward ANN, with 6 neurons in the first layer, and 3 neurons in output layer. Activation functions are hyperbolic tangent in hidden layer, and linear in output layer. Residual evaluation system is three-layer perceptron. The first hidden layer has 14 and the second 7 neurons. Activation functions are:

linear in the first layer and hyperbolic tangent in the other ones. Both ANNs were trained with the Levenberg Marquardt algorithm [10,11] with Bayesian regularization using structures shown in Fig. 4.

Fig.4. Artificial neural network training schemes. a) neural model, b) residual evaluation system

Simulation results

The simulation studies of presented system were performed in MATLAB/Simulink environment. PM machine and power converter models were implemented using SimPowerSystems toolbox. The PMSM drive model operates using vector control, with outer loop of speed control, and inner loop of current control. The motor is fed by a voltage source inverter. It was necessary to create power converter in such a way that the open phase fault could be simulated. There was logical AND operation applied on transistors gate pulse signals, to simulate open circuit fault by holding selected ones at logical zero. The ANNs were implemented and trained using MATLAB Neural Networks Toolbox. Fundamental sample time used in simulation was 1 μs for motor and power converter models, and 100 μs for other blocks. The PWM carrier frequency was equal 10 kHz, and used “dead time” was equal 4 μs. Some sample simulation results of fault detection system behavior are shown in Fig. 5. and Fig. 6.

The waveforms in Fig. 5a shows phase currents during motor startup, which is working at speed 250 rad/s. In addition, at time 0.04 s, a stepwise load was attached, from zero to nominal value. At time 0.06 s open phase A fault is occurred. It is shown in Fig. 5b that fault occurrence causes residuals amplitude increase. This is because of differences between measured and estimated currents. There are some peaks in residual evaluation system output signal, as presented in Fig. 6a. It is caused by inaccurate model of electric drive. To avoid a false-positive error the 10 point moving average filter was applied. Proposed filter was defined as:

Fig.5. Simulation results of proposed neural residual generator. a) phase currents, b) residuals
Fig.6. Simulation results of proposed open phase detection system. a)Residual evaluation system output, b) filtered output, c) diagnosis
Fig.7. Impact of the time-varying load torque on false-positive error. a) phase currents, b) torque, c) residual evaluation system output, d) diagnosis

where ff – filter output signal , fraw – filter input signal, and N – number of points in average. The figure 6b presents filtered residual evaluation system output signal. Diagnosis is created by thresholding of filtered signal.

In the Fig. 7 the impact of the time-varying load torque on diagnosis is presented. After motor startup, drive is working at constant speed and load torque steps and ramps occur.

It can be seen, that peaks in residual evaluation system output signal has been filtered and diagnosis does not depend on load state. It is worth noting that fault detection system works properly from the very beginning of motor startup, so no detection disabling signals are required. Presented system can work as autonomous block in the motor drive.

Simulations at various speeds and angles has been done to examine the electrical angle of the fault occurrence impact on detection time. In table 1, there are presented the fault detection times in a case of various conditions for testing of the break in phase A.

Table 1. Detection time at different electrical angle of open phase A fault occurrence and at various speeds

.

In the most cases, detection time is less than 1 ms, except angles near 0° and 180° during phase A current zero crossing. Zero phase current caused by open phase fault cannot be distinguished from natural current zero crossing so fault detection is delayed. It is worth to add that angular velocity does not impact on detection time.

Conclusions

In this paper, an open phase fault detection system has been introduced. Presented method was verified by simulation research and gave good results. Proposed detection system is fast – detection time is about 1 ms. Short time of fault detection allows to enable FTC algorithm before eventual drive damage, which may occur due to high torque pulsation during open phase state. Presented system processes variables which are already used by vector control algorithm, avoiding the use of extra sensors. Moreover, transient states of drive system and motor speed do not influence diagnosis.

Appendix. Parameters of used Permanent Magnet Machine model

.

REFERENCES

[1] Ertugrul N., Soong W., Dostal G., Saxon D., Faulttolerant motor drive system with redundancy for critical applications, proceedings of the IEEE Power Electronics Specialists Conference 2002 (PESC ‘02), pp. 1457-1462, 2002.
[2] Łuczak D., Siembab K., Comparison of fault tolerant control algorithm using space vector modulation of PMSM drive, proceedings of the 16th Mechatronika, pp. 24-31, 2014.
[3] Khlaief A., Boussak M., Gossa M., Phase faults detection in PMSM drives based on current signature analysis, XIX International Conference on Electrical Machines (ICEM), pp. 1-8, 2010.
[4] Riba J.R., Rosero J.A., Garcia A., Romeral L., Detection of demagnetization faults in permanent-magnet
synchronous motors under nonstationary conditions, IEEE Transactions on Magnetics, vol 45, no. 7, pp. 2961-2969, 2009.
[5] Liu X.Q., Zhang H.Y., Liu J., Yang J., Fault Detection and Diagnosis of Permanent Magnet DC Motor Based on Parameter Estimation and Neural Network, IEEE Transactions on Industrial Electronics, vol 47, no. 5, pp.1021-1030, 2000.
[6] Park B.G., Jang J.S., Kim T.S., Hyun D.S., EKF based fault diagnosis for open-phase faults of PMSM driver, proceedings of the IEEE In Power Electronics and Motion Control Conference, pp. 418-422, 2009.
[7] Park B.G., Kim R.Y., Hyun D.S., Fault diagnosis using recursive least square algorithm for permanent magnet synchronous motor drives, in Power Electronics and ECCE Asia (ICPE & ECCE), pp. 2506-2510, 2011.
[8] Korbicz J., Koscielny J.M., Kowalczuk Z., Cholewa W., Fault Diagnosis. Models, Artificial Intelligence, Applications, Springer ,Berlin 2004.
[9] Quang N.P., Dittrich J.-A., Vector Control of ThreePhase AC Machines, Springer, Berlin 2008.
[10] Levenberg K., A Method for the Solution of Certain Non-Linear Problems in Least Squares. Quarterly of Applied Mathematics 2, pp. 164–168, 1944.
[11] Marquardt D., An Algorithm for Least-Squares Estimation of Nonlinear Parameters. SIAM Journal on Applied Mathematics 11 (2), pp. 431–441, 1963.


Authors: dr inż. Konrad Urbański, Politechnika Poznańska, Instytut Automatyki i Inżynierii Informatycznej, ul. Piotrowo 3a, 60-965 Poznań, E-mail: Konrad.Urbanski@put.poznan.pl; mgr inż. Dariusz Majchrzak, Automatyki i Inżynierii Informatycznej, ul. Piotrowo 3a, 60-965 Poznań, E-mail: Dariusz.zb.Majchrzak@doctorate.put.poznan.pl.


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 93 NR 6/2017. doi:10.15199/48.2017.06.06

Power Quality — Basics Commercial Buildings

Published by HSB, Power quality — basics Commercial property, One State Street P.O. Box 5024 Hartford, CT 06102-5024 Tel: (800) 472-1866. Website: HSB.com


Introduction

Power quality is a general term used to describe the compatibility between connected equipment and its electrical supply. The supply system can be affected by changes to the frequency or amplitude of the voltage, the balance between phases on a three-phase system, and distortion levels of the original signals. The characteristics that are important and what can be tolerated by the connected equipment can vary from facility to facility.

Most electro-mechanical equipment is robust and can handle minor power quality related issues with little or no effect on operations. Electronic equipment is very susceptible to power quality related issues. Due to the shift in the type of loads from electro-mechanical to electronic, power quality is a real concern in all types of applications. This includes hospitals, universities, commercial buildings, and industrial facilities.

Poor power quality

An ideal power source offers a continuous, smooth sinusoidal voltage. Typical power quality issues include:

• Voltage transients (surges)
• Harmonics
• Voltage sags
• Voltage swells
• Voltage interruptions

Typical power quality issues. Image by HSB

The effects of poor power quality are based on the length, magnitude, and timing of the issue as well as the sensitivity of the connected equipment. Poor power quality can result in process interruptions, data corruption, data loss, malfunctioning of computer controlled equipment, and overheating of electrical equipment.

Causes of poor power quality

You might think that poor power quality is primarily the result of weather and utility-related disturbances. However, studies have shown that issues such as lightning, other natural phenomena, and utility operations, account for only a small portion of all electrical disturbances.

A large portion of electrical disturbances are from internal sources or from neighboring businesses that share the same building or are in close proximity. Internal sources can be fax machines, copiers, air conditioners, elevators, and variable frequency drives.

The conditions below are considered warning signs for potential power quality issues in a building. These conditions do not guarantee a problem; however, a building with these conditions will have an increased likelihood of having power quality issues.

• History of power-related issues
• Poorly maintained electrical system
• Failure of surge protection equipment
• Weather and utility disturbances are common
• High concentration of electronic equipment
• Infrared surveys which identify excessive current flow (heat) on grounding conductors and/or system neutrals
• Repeated and random equipment malfunctions, failures, tripped breakers, or blown fuses with no identified causes
• Overheated equipment
• Frequent switching to backup power systems
• Lost data or data corruption
• Premature equipment failures

Solutions

Each type of business will have a different sensitivity level to poor power quality and will have different sources of poor power quality. However, common to all businesses is the importance of a well-maintained electrical distribution and grounding system. The importance of these systems cannot be overstated. When addressing potential or actual power quality issues, the power and grounding system should be the first item addressed. This will improve personnel safety, allow for the proper operation of surge protection devices, minimize the potential for currents on neutral conductors, and provide a common reference plane for electronic equipment.

Once the power and grounding system deficiencies have been addressed, the next steps include power quality inspections, surveys, and the selection and installation of appropriate mitigation equipment.

Inspections are a means to understand a facility from a power quality standpoint. This understanding can be gained by noting:

• Type of equipment installed
• Concentration of computer and electronic equipment
• Presence of welders, power factor correction capacitors, or variable frequency drives
• Heat discoloration of electrical equipment
• Communication and control wiring in close proximity to power wiring
• Condition of the grounding system
• Presence of surge protection installed on power and data lines

Surveys typically involve monitoring and recording the electrical system of a building or a specific area of a building. Reviewing and analyzing the data from the survey helps to determine if a problem exists. The types and severity of problems will dictate the appropriate power quality mitigation strategy.

Power quality inspections and surveys should only be completed by competent power quality professionals.

In many commercial or light industrial businesses, only a few loads are affected by power quality issues. By identifying the most vulnerable loads during a survey, targeted mitigation techniques can be applied.

A wide variety of power quality correction products is available utilizing a range of technologies to correct power quality issues. Common mitigation techniques include surge protection devices, isolation transformers, voltage regulators, motor-generators, standby power supplies, uninterruptible power supplies, and harmonic filters. Each technique has advantages and disadvantages, and should be applied based on its ability to solve a problem identified in the power quality survey and analysis.


Author: HSB, a Munich Re company, is a technology-driven company built on a foundation of specialty insurance, engineering, and technology, all working together to drive innovation in a modern world.


Source & Publisher Item Identifier: ES004 (Rev 12/2020-110), https://www.munichre.com/content/dam/munichre/contentlounge/website-pieces/documents/power-quality-basics.pdf/_jcr_content/renditions/original.media_file.download_attachment.file/power-quality-basics.pdf

Storage Electric Multiple Units on Partially Electrified Suburban Railway Lines

Published by Aleksander JAKUBOWSKI1, Natalia KARKOSIŃSKA–BRZOZOWSKA2, Krzysztof KARWOWSKI1, Andrzej WILK1, Gdańsk University of Technology, Faculty of Electrical and Control Engineering (1), Civil and Environmental Engineering (2)


Abstract. The paper presents possible environmental, energy and economical gains implied by replacing conventional traction vehicles with independently powered electric multiple units (IPEMU) on partially electrified suburban railways. IPEMUs can operate in two modes of power supply – using an overhead catenary or the on–board battery storage. Appropriate computer simulations were carried out in the Matlab program, indicating the parameters of storage electric multiple units.

Streszczenie. W artykule wskazano na potencjalne korzyści energetyczne, środowiskowe i częściowo ekonomiczne wynikające z zastąpienia konwencjonalnych jednostek trakcyjnych nowymi zasobnikowymi zespołami elektrycznymi mogącymi się poruszać na liniach kolejowych częściowo niezelektryfikowanych. Zespoły te mogą pracować w dwóch trybach – zasilania sieciowego lub zasobnikowego. Przeprowadzono odpowiednie symulacje komputerowe w programie Matlab wskazując na parametry zasobnikowych zespołów trakcyjnych. Zasobnikowe zespoły trakcyjne w transporcie podmiejskim

Keywords: railway electric traction, vehicle hybrid power, energy storage devices, computer simulation.
Słowa kluczowe: elektryczne pojazdy szynowe, hybrydowe zasilanie pojazdu, zasobniki energii, symulacja komputerowa.

Introduction

Improved versions of electric rail vehicles have been implemented for over 100 years, capable of crossing routes on non–electrified railway sections. The AT 3 series of two– car electric battery traction unit, known as Wittfeld after the name of the designer, eng. Gustav Wittfeld [1] is an interesting vehicle from the beginning of the 20th century. The train, which could seat 90 passengers, was powered by two 62 kW motors and reached speeds of up to 60 km/h with a tare weight of 60 t. In Gdańsk Pomerania region, AT 3 units most often serviced suburban traffic. Subsequent modernizations extended the range of the units up to 300 km. In the 1950s, worn–out battery rail–cars were withdrawn from line use in Poland.

Current global trends point to potential energy, environmental and partly economic benefits resulting from the replacement of conventional DMU (Diesel Multiple Unit) traction units with new BEMU (Battery Electric Multiple Unit) electric vehicles, and especially IPEMU (Independently Powered Electric Multiple Unit) that can run on partially non–electrified lines [2–8]. DMU and BEMU vehicles are operated on non–electrified lines. IPEMU vehicles can work in two modes – overhead contact line or storage supply. On electrified sections, these assemblies draw energy from the overhead contact line for vehicle propulsion, non–traction needs and energy storage charging, while on non– electrified sections they consume energy from the accumulator, which is recharged during regenerative braking. As energy storage, Li–ion batteries are used most often, and sometimes as a hybrid storage in combination with supercapacitors [9, 10]. Vehicle power systems based on fuel cells and hybrid storages are also considered in the literature [2].

An example of the Tri–City (Gdańsk–Sopot–Gdynia) agglomeration railway line was selected for the sake of analysis and simulations presented below. A short 8– kilometer section of the single–track passenger line on the Gdynia Chylonia – Gdynia Port Oksywie route was considered, on which revitalization is planned that could reduce heavy traffic at rush hours (Fig. 1). On–board battery storage of IPEMU units charged from the catenary line while traveling on the Gdynia Główna – Gdynia Chylonia section of the Urban Rapid Railway (pol. Szybka Kolej Miejska, SKM) line would allow for further travel to the Port Oksywie station and return travel without the need to build electrical traction infrastructure [11].

Fig.1. The route of the non–electrified Gdynia Chylonia – Port Oksywie railway line

In the Tri–City agglomeration you can find many sections of the line with similar features as, for example, regional line No. 213 Reda – Hel with a length of 62 km with great touristic importance. The IPEMU unit can be supplied from the catenary line on the Gdynia Główna – Reda section, which is enough to travel from Reda to Hel station. To charge the vehicle before the return trip, a charging station was assumed to be built to charge the unit while stationary. Similar railways can also be found in other national agglomerations.

Electrical drivetrain structure

Virtually all electric multiple units (EMUs) built nowadays use an overhead contact line or a third rail for power supply. Vehicles operating in urban rail networks in Poland utilize DC line voltage of 3000 V. Thus, the construction and maintenance of a costly railway electrification system is necessary. However, depending on localization, unobstructed construction works may be impossible. The impact of electric catenary on the environment needs also to be taken into account.

Electric multiple units are characterized by drivetrain spread over all carriages, with numerous induction motors, installed in pairs in motorized bogies and fed by inverters (Fig. 2a). Such design allows for wide–range tractive effort regulation with good dynamics and regenerative braking.

Therefore, equipping EMU with on–board energy storage (Fig. 2b) that allows to travel through non– electrified route sections might be worthwhile. Such solutions were implemented in trolleybuses and are widely used [12].

Fig.2. Examples of EMU drivetrain layout: a) conventional; b) light rail vehicle with on–board storage

Fundamental drawbacks for using energy storages in railway vehicles are the large size and weight of such devices, and the necessity of additional energy converter usage. In comparison to a vehicle supplied by an overhead line, IPEMU could have limited passenger space and slightly worse energy efficiency. Therefore, onboard storage applications are limited to light rail vehicles with various drivetrain design.

Vehicle model

Energy consumption analysis of rail vehicle equipped with on–board battery storage has been conducted on the basis of train run calculations [13–15]. For this task, a simulation program was developed using Matlab/Simulink software. Thanks to modular structure of the program, editing input parameters can be easily done, allowing for multiple cases analysis (Fig. 3).

Fig.3. Simplified block diagram of IPEMU run simulation program

Calculations are based on vehicle movement dynamics model, described by equation

.

where: a – acceleration, v – velocity, s – distance, z – control function, F – tractive effort, W – motion resistance, m – vehicle mass, k – rotational mass coefficient.

which is calculated by integrating acceleration a(t). Tractive effort F is set by control function z(s, v, t), with output limited to the range determined by rated torque and speed of the electric drivetrain. Motion resistance W(v,s) consists of fundamental Wz(v) and additional Wd(s) components – the former represents air drag, friction forces and rolling resistances (dependent on velocity), the latter reflects resistance forces from railroad track geometry curvature and inclination.

It was assumed, that acceleration and braking are realized with full available tractive effort; to simplify calculations, electric–only braking was considered. The velocity profile was set by control function z(s, v, t) which determines the relation between cruising and coasting phase, acceleration/braking dynamics as well as station stationary time. The control function program has been designed with compatibility with various drivetrain models and optimizing algorithms in mind.

Electrical energy usage is calculated by integrating electrical power, which is equal to mechanical power (computed by multiplication of traction effort and movement velocity) divided by drivetrain efficiency factor

.

where: Ez – energy consumed, η – drivetrain efficiency factor, pn – power of auxiliary loads, T – analyzed run time.

In order to estimate more accurately the energy consumption, a changing efficiency value of η(F, v) was adopted, using a predetermined table expressing the dependence of the propulsion efficiency on the torque produced by the engines and their angular velocity. The value of the power of the vehicle’s own needs has been defined at a constant level.

Energy recuperated during electric braking of the analyzed vehicle is computed as

.

Onboard battery storage has been represented by a battery model, defined in Simscape/SimPowerSystems library. Its capacity was calculated in order to allow the vehicle to cover the analyzed route in both directions, without using an overhead line nor charging the battery underway. A fully charged state of batteries at the beginning of non–electrified route was assumed.

Energy requirement for IPEMU on the analyzed railway line

Initial run calculations were conducted for 2 MW, 4– section electric multiple unit (Fig. 2a), which is a standard formation for trains in urban rail operating in Poland.

Hypothetically, such conventional vehicle could have on–board battery storage installed, so it can operate on local non–electrified line between stations Gdynia Chylonia and Gdynia Port Oksywie (15,7 km round trip, station numbers – Fig. 1). The route is characterized by relatively small differences in elevation and the speed limit is set at 70 km/h for most of its length. Entire drivetrain parameters utilization was assumed, so acceleration and braking were realized with maximum available tractive effort, also distance between stations was covered with maximum speed allowed (without coasting). The computed speed waveform is shown in Fig. 4a.

Maintaining desired velocity profile requires adequate power supply, which needs to be provided by on–board battery storage. Thus, values of battery capacity and maximum continuous discharge current are the critical factors in storage design (Fig. 4b).

On–board battery storage with parameters allowing conventional EMU for operation under assumed conditions would mass about 18 t. The volume of the storage is also significant – almost 20 m3. Equipping a vehicle with such a massive device would be impractical.

Fig.4. Conventional EMU run waveforms (Fig. 1): a) train velocity and intermediate stops; b) electrical power and energy usage

For further analysis, based on 2– section DMU similar to Pesa SA132–class (produced by PESA Bydgoszcz SA), a light rail vehicle was considered. The hypothetical vehicle would be powered by two 350 kW induction motors, sufficient for maximum speed of 100 km/h. Assuming that electric motors with inverters would replace diesel engines with torque converters and fuel tanks, 80 t net weight of vehicle was increased by 10 t (estimated weight of Li–ion battery storage).

Calculations were performed for two velocity profiles – trapezoidal, without coasting (Fig. 5) and energy–efficient (coasting until braking zone or speed dropping below 60 km/h, Fig. 6).

Results of the storage operation simulation are shown in Fig. 7. At the end of the analyzed run, the state of charge dropped to 78% – batteries were under no risk of deep discharge despite the fact that the storage was not recharged underway. Therefore, the assumed battery storage parameters are sufficient for a vehicle to cover the analyzed route without motion dynamics limitations. Also, there is no need for charging station construction. It is worth noting, that the size of battery storage could be reduced while prolonging its lifespan by equipping supercapacitors, which would absorb regenerative braking energy and provide additional power during acceleration.

Application study and investment costs

In existing Japanese [19] and British IPEMU applications, two–segment lightweight vehicles with a mass of approx. 40 t, number of passengers 130, maximum speed of 100 km/h and acceleration of 1.2 m/s2 were adopted on agglomeration lines. An interesting European vehicle offer is the Bombardier Talent 3 intended for German and Austrian railways with much higher parameters – necessary rather for regional transport (3 units, 140 km/h, 170 seats) [20].

Fig.5. IPEMU parameters on the selected railway line without coasting: a) waveform of velocity; b) waveforms of energy and power

Fig.6. IPEMU parameters on the selected railway line with energy– efficient ride: a) waveform of velocity; b) waveforms of energy and power

Fig.7. Waveforms of currents, voltage and state of charge on– board storage: a) when passing the train without coasting; b) at the energy–saving passage

According to the manufacturer, Talent 3 generates noise and vibrations level 7 dB lower than DMU vehicles, does not emit NOx and indirectly generates CO2 only in power plants. The installed energy storage increases the vehicle’s energy efficiency compared to classic EMUs as a result of braking energy recovery and starting support. To compare the costs of purchasing Talent 3, the prices of domestic producers’ delivery were analyzed as part of tenders from 2016 for EMU and DMU vehicles for the Wielkopolskie, Śląskie, Mazowieckie and Przewozy Regionalne railway companies as well as for Poznań Metropolitan Railway. The average purchase costs are summarized in Table 1. In lines 2 and 3, there are approximate values which, together with the lack of electrification cost of the sample line (line 4) indicate the advantages of IPEMU. The full analysis of the legitimacy of choosing the type of traction unit should include the cost of the entire Life Cycle Cost, which for IPEMU is still difficult to determine.

Summary

The simulation analyses carried out indicate that on both urban and suburban lines it may be beneficial to introduce electric storage traction units of the IPEMU type to service passengers. Estimated costs presented in Tab. 1 indicate the profitability of purchasing one IPEMU instead of classic DMU while discarding 8 km section electrification. The purchase of a classic electric multiple unit together with the electrification of the section in question is similar in price to IPEMU without catenary line. However, the purchase of a larger number of IPEMUs can be economically justified if they are also used to support other non–electrified sections, e.g. Gdańsk Wrzeszcz – Airport, Rumia – Hel and similar. This relation of investment costs can be a challenge for domestic rail vehicle manufacturers in the construction of light IPEMU with technical parameters sufficient to operate on both urban and suburban lines.

Table.1 Average costs of purchase, transport and CO2 emissions of trainsets in Polish national conditions DMU

.

REFERENCES

[1] Jerczyński M., Nasz portret: wagon akumulatorowy typu„Wittfeld”, Świat Kolei 03 (1995)
[2] Pagenkopf J., Kaimer S.: Potentials of alternative propulsion systems for railway vehicles – a techno–economic evaluation, Ninth International Conference EVER, 2014
[3] Ghaviha N., Bohlin M., Holmberg C., Dahlquist E., Speed profile optimization of catenary–free electric trains with lithium–ion batteries, Journal of Modern Transportation, 2019
[4] Furuta R., Kawasaki J., Kondo K., Hybrid traction technologies with energy storage devices for nonelectrified railway lines, IEEJ Transactions on Electrical and Electronic Engineering, Vol. 5, Issue 3, 2010, 291–297
[5] H. al–Ezee, C. Gould, S. B. Tennakoon, Novel method for energy management for catenary free system operation, 53rd International Universities Power Engineering Conference, 2018
[6] Y. Kono, N. Shiraki, H. Yokoyama, R. Furuta, Catenary and storage battery hybrid system for electric railcar series EV–E301, International Power Electronics Conference, IPEC, 2014
[7] Shao–bo Yin, Li–jun Diao, Wei–jie Li, Rong–jia He, Hai–chen Lv, On board energy storage and control for inter–city hybrid EMU. 43rd Annual Conference, IECON 2017
[8] F. Becker, A. Dämmig, Catenary free operation of light rail vehicles – topology and operational concept. 18th European Conference EPE’16 ECCE Europe, 2016
[9] Long Cheng, Wei Wang, Shaoyuan Wei, Hongtao Lin, Zhidong Jia, An improved energy management strategy for hybrid energy storage system in light rail vehicles, Energies 2018
[10] Radu P. V., Szelag A., Steczek M., On–Board energy storage devices with supercapacitors for metro trains – case study analysis of application effectiveness. Energies, 2019, 12, 1291
[11] Telecki M., Studium zastosowania zasobnikowych elektrycznych jednostek trakcyjnych na tworzonej pasażerskiej linii kolejowej do północnych dzielnic Gdyni. Praca dyplomowa. Politechnika Gdańska, 2018
[12] Bartłomiejczyk M., Dynamic charging of electric buses. De Gruyter, 2019
[13] Karwowski K. (red.), Energetyka transportu zelektryfikowanego. Poradnik inżyniera. Wyd. Politechniki Gdańskiej, Gdańsk 2018
[14] Bartłomiejczyk M., Mirchevski S., Jarzębowicz L., Karwowski K., How to choose drive’s rated power in electrified urban transport? 17th European Conference, EPE’17 ECCE Europe, 2017
[15] Jakubowski A., Jarzębowicz L., Karwowski K., Wilk A., Efektywność energetyczna pojazdu szynowego w różnych warunkach obciążenia, TTS Technika Transportu Szynowego, 12 (2018), 44–48
[19] Takiguchi H., Overview of series EV–E301 catenary and battery–powered hybrid railcar, JR EAST Technical Review No. 31 (2015) 27–31
[20] Laperrière P., Realize your vision with Bombardier TALENT 3 BEMU, APTA Rail Conference, 2019


Authors: mgr inż. Aleksander Jakubowski, Politechnika Gdańska, Wydział Elektrotechniki i Automatyki E-mail: aleksander.jakubowski@pg.edu.pl; mgr inż. Natalia Karkosińska– Brzozowska, Politechnika Gdańska, Wydział Inżynierii Lądowej i Środowiska, E-mail: natalia.brzozowska@pg.edu.pl; dr hab. inż. Krzysztof Karwowski, E-mail: krzysztof.karwowski@pg.edu.pl; dr hab. inż. Andrzej Wilk, E-mail: andrzej.wilk@pg.edu.pl; Politechnika Gdańska, Wydział Elektrotechniki i Automatyki, ul. Narutowicza 11/12, 80–233 Gdańsk


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 4/2020. doi:10.15199/48.2020.04.33

Hybrid Energy Storage System in Hybrid Vehicles: Design of Energy Management Strategy and Comparative Analysis

Published by Piotr WOŹNIAK, Politechnika Łódzka, Instytut Systemów Inżynierii Elektrycznej


Abstract. This article presents simulation tests showing the benefits of using an additional energy storage device in the form of a supercapacitor in a hybrid car. An original power flow control system was proposed. The main emphasis was placed on determining the driving characteristics, emissions of harmful substances, fuel consumption and increasing the service life of batteries by limiting rapid changes in the charging and discharging currents and the operating temperature of the cells.

Streszczenie. W artykule przeprowadzono badania symulacyjne pokazujące korzyści płynące z zastosowania dodatkowego zasobnika energii w postaci pakietu superkondensatorów w samochodzie z napędem hybrydowym. W tym celu zaproponowano oryginalny system zarządzania energią. Główny nacisk położono na określenie właściwości jezdnych, emisji szkodliwych substancji, zużycia paliwa oraz wydłużenie okresu użytkowania akumulatorów poprzez ograniczenie gwałtownych zmian prądów ładowania i rozładowania oraz temperatury pracy ogniw. (Wykorzystanie hybrydowych zasobników energii w pojazdach z napędem hybrydowym: projekt strategii zarządzania energią oraz badania porównawcze)

Keywords: hybrid vehicles, supercapacitors, energy management systems.
Słowa kluczowe: pojazdy hybrydowe, superkondensatory, systemy zarządzania energią.

Introduction

Increased fuel prices and high stringent requirements for harmful emissions in recent years have made electric and hybrid vehicles more popular. In the first quarter of 2019, a further increase in interest in cars with alternative power supply was visible in Europe. Sales of electric vehicles (EV) increased by 87.5% compared to the first quarter of 2018, and hybrid vehicles (HEV) by 33%. HEV vehicles accounted for around 4.7% of market share, while EV vehicles around 2%. One way to reduce emissions of harmful substances and to comply with applicable standards “downsizing”, i.e. reducing the capacity of internal combustion engines and the use of a turbine or compressor boost. However, this is not advantageous, because the motor often works in conditions of high overload and adversely affects its durability. A much better solution is to support traditional internal combustion engines with an electric drive, i.e. using a hybrid drive (HEV) or elimination of the internal combustion engine and the use of electric drive (EV). Hybrid cars combine the best features of vehicles with an internal combustion engine and cars with electric drive such as: long range, high power, lower fuel consumption, lower emissions [1]. Batteries used in electric and hybrid vehicles lose their performance over time. This is due to redox reactions occurring, overcharge, changes in internal and external environment parameters. They work well when they are charged/unloaded monotone [2, 3]. If the vehicle suddenly accelerates or brakes, the battery cannot be discharged/charged quickly enough. High battery current, especially when acceleration / deceleration is repetitive (when driving in the city) can have a detrimental effect on electrolyte and shorten battery life [2]. The price of batteries is a large part of the value of the entire car and their replacement is associated with high costs. A large number of charging cycles and use in improper conditions cause their degradation and reduction of capacity. Therefore, it is important to properly control the charging process of the battery pack [4].

Unlike batteries, supercapacitors (ultracapacitors) have a low energy density, which means that they cannot be used as the primary power source. Lithium-ion batteries can store about 20 times higher energy density than supercapacitors. Supercapacitors are also not suitable for long-term energy storage due to the fact that the self-discharge speed of supercapacitors is much higher than for lithium-ion batteries (up to 10-20 percent of charge per day). Although they cannot store as much energy and for as long as lithium-ion batteries of comparable size, their advantage is the ability to charge and discharge in a short time, in some cases the charging time is up to 1000 times shorter than the time of charging a battery with similar capacity.

Fig.1. Advisor menu for the original Toyota Prius model

Supercapacitors therefore have a much higher power density than batteries. That is why they are well suited for applications that require frequent charging and discharging cycles, as well as operation at extreme temperatures. In China, some hybrid buses use supercapacitors to increase acceleration, and in the case of trams, these energy reservoirs allow travel from one stop to another, the charging process takes place at the stops. A hypothetical electric car will be considered to justify the use of supercapacitors. It can move with an average power of about 20 kW, however, during rapid acceleration it requires a peak power several times higher, e.g. 100 kW. Although this power level is only needed for a short time, it means that the vehicle needs additional batteries [5, 6, 7]. Supercapacitors can provide this power required for acceleration, while the battery will provide average power during normal driving, which means that generally the vehicle requires a smaller battery. In the world literature, hybrid power systems using batteries and supercapacitors are mainly used in cars with a serial or parallel hybrid drive and cars with only electric drive (EV) [1, 2], including public utility vehicles.

Technologies used

All tests were carried out using the ADVISOR simulation program, developed at the National Renewable Energy Laboratory (NREL – USA) and operating in the MATLAB environment [8]. This software is widely used for research purposes in many academic centers, e.g. [9, 10, 11, 12, 13].

In the main program menu (Fig. 1) it is possible to freely configure the vehicle, for which simulations will be carried out.

As part of the work described in the article, the first-generation Toyota Prius hybrid car model embedded in the ADVISOR program was tested, which entered serial production in 1997. This model and its parameters were adopted as a reference for research consisting in modification of the power supply system aimed at optimizing the use of energy storage in terms of fuel consumption and emissions of harmful substances such as hydrocarbons (HC), carbon oxides (CO), nitrogen oxides (NOx) and solid particles (PM). And also extending the battery life by lowering their operating temperature, charging / discharging cycles and other parameters affecting driving comfort, such as hill climbing ability.

Fig.2. Toyota Prius block diagram before modification
Fig.3. Toyota Prius power bus before modification
Vehicle parameters and modifications

Standard first generation Prius is powered by Ni-MH rechargeable batteries (1.2V cells, 6 cells connected together in a module, 40 modules). The vehicle modification consists in adding an additional energy storage in the form of a supercapacitors package (Maxwell PC2500 – 2700 F 2.5V). The vehicle model includes the mass of the supercapacitors module. The block diagram of the car built in ADVISOR before modification is shown in Fig. 2. Figure 3 shows the power bus model (block ‘prius power bus ‘ in Fig. 2). The block diagram (Fig. 2) and the power bus (Fig. 3) have been modified to add the energy storage. To add a second energy store, the block name and all parameters and variables starting with the prefix ‘ess_’ to ‘ess2_’ have been changed. This was necessary to avoid conflicts with the battery pack model. In the developed strategy for controlling energy storage, the input parameters are: the absolute value of the power for which there is demand at a given moment from energy storage devices (or which is available for energy storage), its sign (a positive value means discharge, and a negative charge, according to the convention adopted in the environment used), restrictions imposed on SOC (state of charge) for both storage tanks and the rate of power change over time (derivative). In addition, the information on which energy storage was previously used is included and restrictions on switching on the battery container are imposed when large instantaneous values of the charging or discharging current are required. This last action is to extend the life of the energy storage, because limiting the on/off cycles also leads to a lower average operating temperature. The possibility of each energy storage unit operation has been taken into account, and with increased power demand at a given moment, as well as in the case of a large amount of recovered power available, simultaneous operation of both tanks is possible, but the preference is always to use the current capabilities of supercapacitors .

To prevent frequent switching between energy storage, two hysteresis loops were used in the control strategy. In the first loop, the current power derivative value and its belonging to the ranges defined by the two values are checked (e.g. 1000, 2500 – these values may be variable, what is more, in practice they can be determined by the driver based on the knowledge of the route, its profile and traffic) and on this basis the preference for energy storage is determined. In the second hysteresis loop, the preference of energy storage is determined depending on the absolute power value in relation to the estimated supercapacitor power. Designed control system (number of inputs 8, outputs 2), including logic after maximum reduction of Boolean expressions has been implemented in Simulink and includes: 31 logic gates (AND, OR, NOT), 10 comparison systems, 6 multipliers, derivative determination block, 2 blocks for absolute value determination and summation system. As a result of its operation, a binary signal is obtained defining the state (on/off) of each energy storage in the next time step. This allows the available/required power to be distributed to energy storage. The fragment marked with a red frame in Fig. 3 has been changed in the power bus. Figure 4 shows the modified part of the power bus. If there is a high demand for power, e.g. rapid acceleration, we use an additional energy storage in the form of a supercapacitor. During calm driving, energy is taken from the main power source.

Fig.4. Modified part of the power bus after adding supercapacitors
Simulations

The first simulations were made for two built-in routes (CYC_REP05, CYC_US06) and the route for the agglomeration of Lodz developed by the author (CYC_LODZ). The acquisition of this route was made using parameters read from the vehicle’s OBD interface, and the ride was made during rush hour. Route speed profiles are shown in Fig. 5. To extend the travel time, the cycle was repeated three times. An example of the simulation result in the ADVISOR environment for transit using the built-in Toyota Prius model is shown in Fig. 6. The same initial conditions were used for all tests: SOC=0,7; SOC2=0,7; temp=20°C.

Then a series of simulations was performed using a modified version of the vehicle with an additional energy storage in the form of a supercapacitors package (30-60 modules) using the model embedded in the ADVISOR environment and a modified energy management system as described in chapter 3. An example of the simulation result is shown in Fig. 7. The rest of the simulation results for all routes in different combinations of the number of battery modules and supercapacitors (nBT and nUC where n is the number of modules, BT – baterries, UC – supercapacitors ) are shown in Table 2. 40BT refers to the original Toyota Prius.

Additionally, for each nBT nUC configuration, perform an acceleration test and gradeability test at 50 km/h, at initial values SOC=0,6 and SOC2=0,6. The simulation results are shown in Table 1.

Table 1. The results of the acceleration and gradeability test

.

Table 2. Simulation results for the route CYC_REP05, CYC_US06 and CYC_LODZ

.
Fig.5. Route profiles (a) CYC_REP05, (b) CYC_US06, (c) CYC_LODZ
Fig.6. Simulation results for the route CYC_US06 (original Toyota Prius)
Fig.7. Simulation results for the route CYC_US06 for configuration 30BT 40UC
Conclusions

The simulation results show that the use of an additional energy storage in the form of a supercapacitor brings, in most cases, many benefits. First of all, in many cases lower fuel consumption has been achieved, which reduces the release of harmful substances by the vehicle. In addition, the use of an additional energy storage(supercapacitor) has reduced the number of battery modules (from standard 40 to 30-35). Less batteries means lower replacement costs when old batteries degrade. The proposed energy management strategy has reduced the average operating temperature of the battery pack, average current drawn from the battery, and on and off cycles, which has a positive effect on extending the life cycle of this energy storage. Adding an additional energy storage in the form of supercapacitors is associated with additional costs, but due to longer life and susceptibility to a large number of charging and discharging cycles (up to 1000000) this investment is a one-off with a typical vehicle life. The big advantage of supercapacitors, unlike batteries, is the ability to receive and release large amounts of energy in a short time, which is included in the proposed control strategy.

REFERENCES

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[4] Czerwiński A., Akumulatory, Baterie, Ogniwa, WŁK, 2005
[5] King A. , Power-hungry Tesla picks up supercapacitor maker, ChemistryWorld, 2019,
https://www.chemistryworld.com/news/power-hungry-teslapicks-up-supercapacitor-maker-/3010215.article
[6] Juda Z., Zastosowanie superkondensatorów w układzie odzysku energii pojazdu z napędem elektrycznym, Czasopismo Techniczne. Mechanika, 105 (2008), z. 6-M, 191-199
[7] Kasprzyk L., Bednarek K., Dobór hybrydowego zasobnika energii do pojazdu elektrycznego, Przegląd Elektrotechniczny, 91 (2015), nr.12, 129-132
[8] http://adv-vehicle-sim.sourceforge.net/
[9] Chen D., et al., ‘Research on Simulation of the Hybrid Electric Vehicle Based on Software ADVISOR, Sensors & Transducers Journal, 171 (2014), 68-77
[10] Gao D. W., Mi C. , Emadi A., Modeling and Simulation of Electric and Hybrid Vehicles, in Proceedings of the IEEE, 95 (2007), 729-745
[11] Rashid M. I. M., Daniyal H., Mohamed D.I, ‘Comparison performance of split plug-in hybrid electric vehicle and hybrid electric vehicle using ADVISOR’, MATEC Web Conf., 90 (2017), https://doi.org/10.1051/matecconf/20179001019
[12] Szumska E, Pawełczyk M., Ocena korzyści zastosowania napędów hybrydowych w pojazdach komunikacji miejskiej, Autobusy: technika, eksploatacja, systemy transportowe, 18 (2017), 1087-1092
[13] Wu Y., Power Distribution System Modeling and Simulation of an Alternative Energy, 2010,
https://etd.ohiolink.edu/!etd.send_file?accession=ohiou1289960977&disposition=inline


Author: mgr inż. Piotr Woźniak, Politechnika Łódzka, Instytut Systemów Inżynierii Elektrycznej, ul. Stefanowskiego 18/22, 90-924 Łódź, E-mail: piotr.wozniak@dokt.p.lodz.pl.


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 8/2020. doi:10.15199/48.2020.08.12

Memristive Devices In Three-Phase Systems

Published by Piotr ZEGARMISTRZ, Bartłomiej GARDA, AGH University of Science and Technology


Abstract. The aim of the research presented in a paper was to provide trustworthy simulation results for symmetrical three-phase systems with memristive load. The memristors in the system are combined with linear resistors in order to limit the current in the element. Linear drift model of the memristor was considered in Matlab simulations. It is based on Strukov model with Biolek window. High nonlinearity of memristor results in deformation of most of the signals in the system. Since the voltage of the neutral point is highly non-sinusoidal it affects on other signals like phase voltage, phase currents, delta voltages. A Fast Fourier Transform (FFT) is applied to chosen signals in order to provide a frequency spectrum. On this basis a Total Harmonic Distortion (THD) parameter was calculated.

Streszczenie. W pracy zaprezentowano wyniki badan´ symulacyjnych nad układem trójfazowym symetrycznym z obcia˛z˙eniem elementami memrystorowymi. Memrystory w obwodzie odbiornika sa˛ poła˛czone szeregowo z rezystorami liniowymi w celu ograniczenia pra˛du. W obliczeniach symulacyjnych przyje˛ to model memrystora “linear drift”, bazuja˛cy na modelu Strukova z oknem Biolka. Wysoka nieliniowos´c´ elementów memrystorowych skutkuje odkształceniem wie˛kszos´ci sygnałów w obwodzie. Skoro napie˛cie punktu neutralnego odbiornika wykazuje wysoka˛ nieliniowos´c´, to skutkuje to odkształceniem pozostałych sygnałów, t.j. napie˛c´ fazowych, pra˛dów fazowych czy napie˛c´ przewodowych. Do wybranych sygnałów zastosowano Szybka˛ Transformate˛ Fouriera (FTT) w celu zaprezentowania widma cze˛stotliwos´ciowego. Na tej podstawie obliczono Współczynnik Zawartos´ci Harmonicznych. (Elementy memrystorowe w układach trójfazowych)

Keywords: memristor, memristive device, memristive element, three-phase systems, nonlinear systems
Słowa kluczowe: memrystor, element memrystorowy, układy trójfazowe, obwody nieliniowe

Introduction

Theoretical definition of memristor was stated by L.O. Chua in 1971 [1][2]. It was defined as an element in which the actual value of resistance depends on the flux or charge through the element. It is capable of switching between two resistance states upon application of an appropriate voltage or current signal that can be sensed by applying a relatively much smaller sensing signal [3]. It was announced as the missing fourth fundamental passive circuit element.

In 2008 HP Laboratories reported the discovery of the element, which exhibits electrically controllable state dependent resistance [3][4]. It was a turning point in research on memristive devices. This topic became a priority for many R&D units and academic researchers. The most crucial property of memristor is the fact, that it can take two significantly different values of resistance in a stable way. This explains, why after 2008 this topic became so popular for scientists specializing in electronics, in particular memories, logic circuits and neuromorphic systems [5].

However, the applications of memrsitive devices focuses on microelectronics, that is not the one and only correct direction. In recent years the concept of so-called ’power memristor’ grows. The idea is to use memristive elements in lightning protection systems, i.e. instead of traditional varistors. In [6] author proposes a combined over-voltage protecting device consisting of a memristor connected in series with a spark gap. The memristor is applied for dissipating lightning surge energy and for breaking the short circuit current. This simple example shows, that analyzing the usage of memristive device in three-phase systems is noteworthy and can deliver a basis for further research.

A characteristic pinched hystersis loop (so-called bowtie curve) in v-i relation when applying a sinusoidal voltage to the element is also a special mark for memristors. This v-i histeresis loop always passes through the origin for any bipolar periodic input voltage [7]. The shape of the curve narrows down signifficantly with the frequency f. Beyond a certain critical frequency, the area of the loop decreases monotonically. It aims to zero with the frequency f increasing [8]. In this work, the authors decided to analyze the possibility of a usage of two-terminal memristive devices in threephase systems. It is assumed, that the system is powered by symmetrical three-phase source (i.e. set of three sinusoidal voltage sources with the same amplitude and phase shifted by /3 ) and it is loaded by serial connection of a memristor and linear resistor with the value appropriate to limit the current in the memristive element in such a way that it is set in its work area. The basic aim of this study was to deliver a trustworthy information about the behavior of the signals in a three-phase system when memristive devices occur. To simplify the case study, it is limited to the symmetrical load version. The next aim was to analyze the impact of increasing frequency f of the input signal on the signals in the system.

Linear Ion Drift Model

This model is also known as Strukov model. It is assumed, that oxygen ions drift through the memristor structure with the velocity that depends linearly on the electric field. The v-i (voltage-current) relation in this model is:

.

where M{x(t)} = Ronx(t)+Roff(1−x(t)) represents the memristance of the memristive element in Ohms.

The internal variable x(t) denotes the relative width of the low-resistance region. Its dynamics is defined by the following formula:

.

To ensure that internal variable x(t) is confined to the interval [0, 1] one can multiply the right hand side of the equation above (2) by the ideal rectangular window function defined as f(x) = 1 for x ∈ [0, 1] and f(x) = 0 for others.

The above model depends on three parameters. Ron and Roff are the minimal and maximal resistances of the element, while the parameter k represents material properties and geometrical structure of the element.

Biolek Window Function

The equation (2) defining the elements dynamics does not take into account the physical phenomenon that switching mechanism is slower while states variable is close to the border of the limiting interval. One of the method that introduces this phenomenon is the window function application.

Then the equation (2) becomes:

.

where the f(x, i) is the mentioned window function of internal variable x and current i across the element. One of the popular window function is proposed by Biolek et al. [9], where the function f(x, i) is defined as:

.

where p is an even integer and 1 (·) represents a unit step function.

In this work a modified version of Biolek window is used, in which the absolute value of the expression under the power p is taken [10]. This permits using odd values of p also. Than, the Strukov model with the Biolek window is defined as:

.

The window function (4) introduces an additional integer parameter p to the Strukov model.

Simulations

All the simulations, results of which are presented in section below, were carried out in Matlab environment. Prepared simulation software gives the opportunity to measure and plot all of the signals in three-phase system, ie. voltage of the neutral point, phase voltages, phase currents, delta voltages and neutral wire current. It is possible to simulate both three-cord and four-cord systems, but in this paper only results for three-cord system are presented. The diagram of the circuit considered in the simulations is shown on Fig. 1. User can also set the specific value of phase wire resistance, as well as neutral wires resistances for four-cord case. Simulations for non-symmetrical loads, as well as for non-symmetrical three-phase sources are also possible. One can set an amplitude and phase shift for each phase voltage source separately. But this opportunity is not taken into account in this paper.

Fig.1. Diagram of the circuit considered in the simulations.

Results of the simulations for different frequencies are described in section below. For all simulations Linear Ion Drift Model with Biolek Window was used. This model bases on phenomena, that take place in real memristive element, so it is the most appropriate for that experiments.

Results

The main goal of the experiments was to show, how theoretically symmetric three-phase system behaves in terms of existing non-linear memristive elements. The simulations were made for the input phase voltages with RMS value 4V and linear resistance 1kΩ in series to memristor in order to limit the current in the element the same way, like in real measurements.

Fig.2. Internal variable x for memristors in phases A, B and C. Input signal frequency f = 1Hz.
Fig.3. Neutral point voltage. Input signal frequency f = 1Hz
Fig.4. Phase currents. Input signal frequency f = 1Hz.
Fig.5. Phase voltages. Input signal frequency f = 1Hz.

In this paper we focus on experiments made for the three-cord system. The frequency of input signals varies from 1 Hz to 500 Hz. Fig. 2 to 7 present the output parameters of the system for the frequency 1 Hz. To reduce the influence of the initial parameters all time series presented in the article shows the results of the simulation after some time of evaluation.

Shape of the internal variable x impacts on actual value of the resistance of memristor. This causes high non-linearity, which reveals in the shape of neutral point voltage signal. Since it is non-sinusoidal, all other signals in the system are non-sinusoidal. It is not obvious to find any conclusions for that results, but surely one can observe, that signals of the phase B are deformed in least significant way. This is confirmed in the shape of v-i curve (hysteresis loop), which is less pinched for phase B, than for the others. It is interesting that this phenomenon does not depend on different initial states values.

Fig.6. Time series of delta voltages for input signal frequency f = 1 Hz.
Fig.7. Hysteresis loop for phase voltages and currents for input signal frequency f = 1Hz.

Delta voltages (line voltages) are measured between connection nodes of linear resistor and memristor in each phase. Clearly, they are less deformed than other signals. An interesting observation may occur, when analyzing a frequency spectrum of the reported signals. In order to achieve it, the authors propose to perform a FFT (Fast Fourier Transform) on the signals. An answer of FFT for a chosen signal (phase A current) is shown on Fig. 8. It is important to notice the DC factor which value is on the level of second harmonic frequency. As it was mentioned earlier, the experiments were lead for wider range of frequencies.

As it is impossible to present graphs for all measured signals, authors decided to compare only chosen signals for higher frequencies – phase currents and v − i relation.

As one can see, the higher frequency, the more linear behavior of the memristive element. For frequencies 100 Hz and higher, the system behaved like fully linear system, so presenting graphs for them seems to be pointless. The general rule observed is, that the shape of the pinched hysteresis loop narrows down with increasing the frequency. For frequencies 500 Hz and higher it is straight line, so the memristor behaves as regular linear resistor.

Fig.8. Fast Fourier Transform of iA(t) current for input signal frequency f = 1Hz.
Fig.9. Time series of the phase currents for input signal frequency f = 5Hz.
Fig.10. Hysteresis loop for phase voltages and currents for input signal frequency f = 5Hz.
Conclusions

The authors performed also simulation results for four-cord systems, but because of limited space, it will be published in separate paper in near future. Presented results confirm the theoretical evidence, that memristor v − i characteristic tends to linear with increasing frequency. Moreover, for lower frequencies high non-linearity is observed. It motivated the authors to calculate a Total Harmonic Distortion (THD) parameter for chosen signals in order to show the degree of deformation of the signal versus frequency. In Tab. 1 the results for phase current iA are presented. Furthermore Tab. 1 contains RMS and mean values of iA. It is worth to notice that for low frequency f = 1Hz the value of the current is ca. 2.5 times higher than for the higher frequency f = 500 Hz. Also interesting is the fact of presence of DC factor which also tends to zero when the frequency increases.

Fig.11. Time series of phase currents for input signal frequency f = 20Hz.
Fig.12. Hysteresis loop for phase voltages and currents for input signal frequency f = 20Hz.
Fig.13. Time series of the phase currents for input signal frequency f = 50Hz.

In future work the measurements on real three-phase systems with memristive load is planned. Experimental research is the natural way to verify the results of analytical simulations. In order to achieve this a precise phase-shifting module needs to be design and build.

Fig.14. Hysteresis loop for phase voltages and currents for input signal frequency f = 50Hz.

Table 1. Basic parameters of phase A current iA vs frequency f

.

Acknowledgment: This work was supported by the National Science Centre, Poland, grant no. 2015/17/B/ST7/03763.

REFERENCES

[1] Chua L. O.: Memristor. The missing circuit element, IEEE Trans. Circ. Theory, vol. 18, no. 5, pp. 507–519, 1971.
[2] Chua L. O.: The fourth element, Proc. IEEE, vol. 100, no. 6, pp.1920–1927, 2012.
[3] Gandhi G., Aggarwal V., Chua L. O.: The first radios were made using memristors!, IEEE Circuits and Systems, vol. 13, no. 2, pp. 8–16, 2013.
[4] Strukov D., Snider G., Steward D., Williams R.,: The missing memristor found, Nature, vol. 453, no. 7191, pp. 80–83, 2008.
[5] Sacchetto D., Gaillardon P.-E., Zervas M., Carrara S., De
Micheli G., Leblebici Y.: Applications of Multi-Terminal Memristive Devices: A Review, IEEE Circuits and Systems, vol. 13, no. 2, pp. 23–41, 2013.
[6] Horváth I.: Simulation of a memristor-spark-gap model for lightning protection purposes, Tehnicki Vjesnik, vol. 21 (5), pp.1047–1050, 2014.
[7] Pickett M., Strukov D., Borghetti J., Yang J., Snider G., Stewart D., Williams R.: Switching dynamics in titanium dioxide memristive devices, Journal of Applied Physics, vol. 106, 074508, 2009.
[8] Adhikari S., Sah P., Kim, H.,Chua L.O.: Three fingerprints of memristor, IEEE Trans. on Circ. and Syst. I: Regular Papers, vol. 60, no. 11, pp.3008–3021, 2013.
[9] Biolek Z., Biolek D., Biolkova B.: Spice model of memristor with nonlinear dopant drift, Radio Eng., vol. 18, no. 2, pp. 786–790, 2015.
[10] Garda B., Galias Z.: Modelling sinusoidally driven selfdirected channel memristors, Proc. ICSES 2018, Cracow, Poland, pp.19–22, 2018.


Authors: Ph.D. Piotr Zegarmistrz, Ph.D. Bartłomiej Garda, Department of Electrical and Power Engineering, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków, Poland, email: pzegar@agh.edu.pl; bgarda@agh.edu.pl


Source & Publisher Item Identifier: PRZEGLA˛D ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 1/2020. doi:10.15199/48.2020.01.03

Power Exchange in Smart Grids Integrating Renewable Energy

Published by MEKKAOUI Ali1, LAOUER Mohammed2, YOUNES Mimoun1,
University of Sidi Belabes, Algeria (1), University Center of Naama, Algeria (2)


Abstract. Smart grids are essentially characterized by reliability and energy efficiency so we can optimize the performance of the electrical system to ensure safe and reliable operation. This paper discusses smart grids in a future generation context and to value this goal, we consider a new model of hybrid system combining solar and wind energy. In order to automate and ensure a wide distribution of the transmission and distribution network we will consider the bidirectional transfer of electricity and information solution. Our task in this work is to envisage an electrical power system connected to different consumers who can themselves produce electrical energy. Renewable energies will be present both at the level of the network in general and the subscribers which will allow a power exchange between the different actors.

Streszczenie. W artykule analizowano sieć typu smart grid nowej generacji będącą hybrydą energi fotowoltaicznej i wiatrowej. Uwzględniono możliwość dwukierunkowego transferu energii. Uwzględniono też różne typy odbiorców, w tym także tych wytwarzających energię. (Wymiana mocy w sieci typu smart grid z odnawialnymi źródłami energii)

Keywords: Active power, Renewable energy, Smart grids, Optimization.
Słowa kluczowe: sieć typu smart grid, odnawialne źródła energii

Introduction

The limits of global fossil and nuclear fuel resources have prompted an urgent search for alternative sources of energy. Therefore, a new way to balance supply with demand is needed without the use of coal, gas or other generators. The smart grid will therefore play the role of an important system that will integrate renewable energy sources and move from dependence to fossil fuels, while respecting the balance of power produced and consumed.

The state of balance between production and consumption in current power systems must be checked at all times and in all places. Except that to be done, we will be in the obligation to control the transit of powers at any point of the network. The increased demand of power and the unexpected extension of the network disrupt the exchange of powers in real time. Is there a way to control, check and finally make the decision to ensure better management of electrical energy without there being a major failure? Otherwise, the system will be in a critical or even catastrophic situation. The answer to this question is implicitly given by using Smart Grids.

The Smart Grids provide the ideal solution to our problem, although they are a very interesting variant of energy saving. The conventional system must be modified because other components will appear and add to the existing power system to make it more complex and difficult to manage. The Smart Grids community relies on three different systems that provide unidirectional management from upstream to downstream. To know:

• The conventional and renewable energy generation systems,
• The local system,
• The transversal system.

The latter, is very important because it consists of active distribution networks and transport, controlled and adjusted in real time between supply and demand for energy.

The combination of these three systems is therefore the smart grid and responds to the priorities of the new electricity economy that can be summarized into three major conventional, renewable use values and the demand of the local system.

In addition, the following actions must be fully required:

• The integration of renewable and intermittent energies and new electrical uses,
• The flexibility of production and consumption for the reduction of the electric tip,
• Two-way flow of information and energy flows between the three system levels.

The future Smart Grid power grid is a dynamic network that aims at two-way power transit, largely linking small-scale renewable energy production systems at the consumer level and the larger electric power generation grid, thereby facilitating customer participation in energy management generation (consumption / consumption) in real time while raising the optimal performance of the operation of the power system [1]. Frequency and active power are the main parameters showing the stability of any conventional power grid [2]. The conventional power grid and computer and communication technologies are combined to control the active power flow to have a stable, reliable and efficient power grid.

Description and modelling of the hybrid system wind / solar
Regarding the wind system

Many studies have reported on this system and in particular the wind turbines [3]. The wind turbine model selected considers the characteristics of the wind speed as a function of the power output. The latter is given by [4- 5]:

.

where Pm is the mechanical output power of the turbine, Cp is the performance coefficient of the turbine, λ is the tip speed ratio of the rotor blade, β is the blade pitch angle, ρ is the air density, A is the turbine swept area and Vwind is the wind speed.

The model of performance coefficient Cp (λ,β) is taken from [4] and given by:

.

Where: constants C1 to C6 are the parameters that depend on the wind turbine rotor and the blade design, λi is a parameter given in (3).

.

So, Equality (1) can be normalized and simplified for specific values A of λ and as in (4):

.

where Pm_ pu is the power in per unit of nominal power for particular values A of λ , Vwind _ pu is the power gain of the base wind speed and Cp _ pu is the performance coefficient.

The based wind speed is the mean value of the expected wind speed in m/s .

Regarding photovoltaic system

For more than 30 years [6], the model of the photovoltaic system recommended is to consider the circuit consisting of a photo-current, a diode, a parallel resistance (leakage current) and a series resistance; the assembly is represented in Fig. 1. By applying Kirchhoff laws on the circuit, we can deduce the voltaic current which is given by [7]:

.

where Ipv is the photovoltaic current, IGC is the light generated current, Io is the dark saturation current dependent on the cell temperature, e is the electric charge e = 1.6*10-19 C , Vd is the diode voltage, K is the Boltzmann’s constant K = 1.38*10-23 J/K , F is the cell idealizing factor, Tc is the cell’s absolute temperature, Rp is the parallel resistance.

Knowing, on the other hand, that the photo-current depends essentially on the solar irradiation and the temperature of the cell, given by [7].

Fig.1. Single diode PV cell equivalent circuit.
.

where μsc is the temperature coefficient of the cell’s short circuit current, Tr is the cell’s reference temperature, Isc is the cell’s short circuit current at a 25oC and 1KW/m2 , G is the solar irradiation in KW/m2 .

Furthermore, the cell’s saturation current varies (Io) with the cell temperature, which is described as [6]:

.
.

where I is the cell’s reverse saturation current at a solar radiation and reference temperature, Vg is the band-gap energy of the semiconductor used in the cell and Voc is the cells open circuit voltage.

Intelligent energy management systems

When a network has the capacity to effectively manage the actions undertaken by all the actors involved in the exchange of electrical powers (producers / consumers) and to ensure at the best of times a competitive electricity price, will talk about the smart grid. The main objective to achieve is to have low losses and a better quality of electrical energy. Such a network must include a smart meter, a smart home, a city server, and main server [8- 9].

Smart metering

The smart meter is the important component in the smart grids [10]; it consists of a bidirectional telecommunication subsystem to an information tele collection center. Its construction technology permits automatically to collect diagnostic data, consumption, available energy metering and transfer of this data to a central database [11].

Town server

For better management of electrical energy, the smart grids must be equipped with a city server. It will now have the ability to make any decision concerning all of its users through a central computer. To communicate with the primary server, it uses the public telephone network energy. It consists of a central computer and a complete server, capable of making decisions for all its users. It uses the public switched telephone network to communicate with the main server [12- 13].

Main server

It communicates in bidirectional way with smart home meters. Once the data is collected, It must be processed to validate it and finally stored in a central database [14- 15].

Analysis and control of active power

The collection of the energy consumption information of a smart home by the smart meter is sent to the command and control center [16]. The data generated by the smart meter is transmitted to a data aggregation. This aggregator could be an access point or gateway. The public electricity service or the distribution station and the intelligent communication is responsible for the transmission of the collected data. Fig. 2.

Fig.2. Power and information exchange in a smart grid

We can illustrate our study from a global diagram showing the different elements of a smart grid involved in the exchange of electric powers, as shown in Fig.3.

Fig.3. Flow chart of smart system.

Results and discussion

Our goal is to consider an electrical power system connected to the different consumers who themselves can generate electrical power. Renewable energies will be present both at the level of the network in general and the subscribers.

Fig.4. First house simulation results

The 24-hour extended load curve of house 1 is described in Fig. 4 (red color). The power exchange with the outside is represented by the residual power curve resulting from the difference between the power delivered by the wind turbine of the house 1 of the order of 4 kW and its power consumption (green color). Based on simulation results, we note the following situations:

• Between 00 h 00 and 06h 00 the house1 consumes a power of 0.5 KW, remains autumn and gives a residual power of 3.5KW to the electrical grid.

• A first peak appears around 6:00 am until 8:00 am reaches a value of 3KW; the house 1 is still isolated and provides the power grid with a power surplus of 1KW.

• Between 08h00 and 12h:00 the house consumes a power of 1KW and injects to the electrical system a surplus power of 3KW.

• A second peak reappears around 12:00 pm until 02:00 pm reaching a value of 2KW which reduces the surplus power to 2KW. The latter increases and holds a value of 3KW between 02:00 pm and 7:00 pm.

• A third bigger peak appears around 7:00 pm until 23h: 00 reaching a value of 5KW thus exceeding the production capacity of house 1. The difference is ensured by the electrical grid.

Fig.5. Second house simulation results

The exchange of electrical power between house 1 and house 2 is possible because house 1 has a residue of power. The charging curve of house 2 is in red, the power delivered by the house 1 is in green and the additional power supplied by the electric network in blue.

Based on simulation results, we note the following situations in Fig. 5:

• Between 00h00 and 08h:00 the house 2 consumes a power of 1KW provided by the house 1 thus reducing the surplus of the house 1 the remainder of which is made available to the need.

• At 8:00 am the consumption of house 2 increases and reaches a value of the order of 2KW which will always be powered by the house 1.

• A peak consumption is observed at 19h00 until 23h: 00 which involves the power grid to satisfy the electrical energy demand of the house 2.

Fig.6. Third house simulation results

The extended load curve over 24 hours of the house 3 is given by Fig. 6 in red color. The power exchange with the outside is represented by the residual power curve (in green color) which results from the difference between the power delivered by the solar energy of 4KW and the power consumed by the house 3. According to The results of simulations, we note the following situations:

• Between 00:00 and 06:00 in the morning house 3 consumes a power of 0.5 KW which is delivered by the electricity grid.

• The presence of the first peak from 06h: 00 to 08h00 of the order of 3KW is ensured by the electricity grid.

• The sun makes its appearance from 08h 00, at this moment the house 3 consumes a power of 1KW which will be delivered by its solar energy. Then house 3 remains autumn and gives a residual power of 3KW until 19h: 00.

• A second consumption peak of 6KW is observed from 20h 00 until 23h00, which involves the power grid to satisfy the energy demand of the house 3.

Fig.7. Fourth house simulation results

Fig. 7 shows the load curve (red color), the curve of the solar energy produced by the house 3 (green color) and finally the curve of the electricity network (blue color).

Based on simulation results, we note the following situations:

• Between 00h00 and 06h: 00 the house 4 consumes a power of 1KW which is delivered by the electrical network.

• A first peak appears from 06h00 to 08h:00 reaching a value of 4KW but always ensured by the electricity grid.

• From 08:00 to 19:00 the house 4 is fueled by the energy coming from the house 3 despite the presence of the second peak of consumption which is of the order of 3 KW.

• A third peak of consumption is observed at 20:00 until 23:00 which of the order of 6KW this energy is supplied by the electrical network.

Conclusion

It is very interesting to understand the transfer and the exchange of electrical energy between the different actors participating in this action. This article clearly explains the integration of renewable energies into the conventional electricity grid for better and intelligent management of home energy. The simulation of such a system consisting of houses and the existing electricity network has provided the answer, so long awaited, explaining the interest brought by the smart grid. Our simulation clearly explains the contribution of the houses in the network stability in the sense of its relief in case of the strong demand. Thus, we can conclude that smart grids offer a radical solution to the reliable and continuous operation of the entire system.

REFERENCES

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Authors, Ali Mekkaoui, Pr. Younes Mimoune, University of Sidi Belabes, Algeria and Pr. Mohammed Laouer, University Center of Naama, Algeria, Email: mekkaouiali70@gmail.com, younesmi@yahoo.fr laouer@yahoo.fr


Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 96 NR 12/2020. doi:10.15199/48.2020.12.17