Power Quality Blog

General Reference – Modeling for Transient Analysis

Published by Electrotek Concepts, Inc., PQSoft Case Study: General Reference – Modeling for Transient Analysis, Document ID: PQS0316, Date: July 18, 2003.

Abstract: Transient voltage and currents are a result of sudden changes within the electric power system. Opening or closing of a switch or circuit breaker causes a change in circuit configuration and the associated voltages and currents. Simulations provide a convenient means to characterize power quality problems, predict disturbance characteristics, and evaluate possible solutions to problems. They should be performed in conjunction with monitoring efforts and measurements for verification of models and identification of important power quality concerns.

The document provides an overview of transient modeling for system studies.

INTRODUCTION

Transient voltage and currents are a result of sudden changes within the electric power system. Opening or closing of a switch or circuit breaker causes a change in circuit configuration and the associated voltages and currents. A finite amount of time is required before a new stable operating point is reached. Lightning strokes to exposed distribution circuits inject a large amount of energy into the power system in a very short time, causing deviations in voltages and currents which persist until the excess energy is absorbed by dissipative elements (surge arresters, load resistance, conductor resistance, grounding system, etc.). A principal effect of both these events is a temporary departure of power system voltage and current from the normal steady-state sinusoidal waveforms.

All transients are caused by one of two actions:

− connection or disconnection of elements within the electric circuit
− injection of energy due to a direct or indirect lightning stroke or static discharge.

Opening or closing of switches is a very common occurrence, whether it be normal cycling of loads at the utilization level, or utility operations on the transmission and distribution system. Lightning and static discharge are less common, but the potential effects are obvious. The mechanism may also be unintentional, as with initiation of a short circuit.

Transient overvoltages and overcurrents are classified by peak magnitude, frequency, and duration. These parameters are useful indices for evaluating potential impacts of transients on power system equipment. The absolute peak voltage, which is dependent on the transient magnitude and the point on the fundamental frequency voltage waveform at which the event occurs, is important for dielectric breakdown evaluation (e.g. equipment insulation strength). Some equipment and types of insulation, however, may also be sensitive to rates of change in voltage or current. The transient frequency, combined with the peak magnitude, can be used to estimate the rate of change.

Transient characteristics are dependent on the combination of initiating mechanism and the electric circuit characteristics at the source of the transient. Circuit inductances and capacitances – either discrete components such as shunt capacitance of power factor correction banks or inductances in transformer windings, or stray inductance or capacitance because of proximity to other current carrying conductors or voltages – are responsible for the oscillatory nature of transients. If the dominant circuit elements are known, transient frequencies can be easily calculated, as with the case of utility capacitor switching. In many instances, where small inductances and capacitances associated with circuit conductors may predominate, transient frequencies are more difficult to calculate.

Natural frequencies within the power system depend on the system voltage level, line lengths, cable lengths, system short circuit capacity, and the application of shunt capacitors. On utility distribution circuits (4.16-34.5kV), transient frequencies between 300 Hz and 3 kHz are common. The lower frequencies occur when there are distribution capacitor banks and the higher frequencies are associated with the distribution lines themselves. In industrial and commercial utilization circuits (e.g. 480 volts), dominant natural frequencies between 5 kHz and 100 kHz are found (much lower frequencies will dominate if 480 volt capacitors are used). Transient frequencies in residential wiring systems (110/220 Volts) range from 50 kHz to 250 kHz. For comparison purposes, the series inductance and shunt capacitance of a typical power cord forms a resonant circuit with natural frequencies between 500 kHz and 2 MHz.

MODELING FOR TRANSIENT ANALYSIS

The Electromagnetic Transients Program

The most widely used program for transient analysis is the Electromagnetic Transients Program (EMTP). The EMTP is used to simulate electromagnetic, electromechanical, and control system transients in multiphase power systems. It was originally developed, in the late 1960’s, by Hermann Dommel at Bonneville Power Authority (BPA). Since then, there has been significant developments by groups all over the world.

The EMTP is a general-purpose computer program for simulating high-speed transient effects on electric power systems. The program features an extremely wide variety of modeling capabilities encompassing electromagnetic and electromechanical oscillations ranging in duration from microseconds to seconds. Examples of its use include switching and lightning surge analysis, insulation coordination, shaft torsional oscillations, ferroresonance, and HVDC converter control and operations.

The program initially comprised about 5000 lines of code, and was useful primarily for transmission line switching studies. As more uses for the program became apparent, BPA coordinated many improvements to the program. As the program grew in versatility and in size, it likewise became more unwieldy and difficult to use. One had to be an EMTP aficionado to take advantage of its capabilities. The development of a personal computer version of the program has helped to improve the usability, however, a typical user may find that it requires many man-years of effort to become proficient.

The EMTP is used to solve the ordinary differential and/or algebraic equations associated with an “arbitrary” interconnection of different electrical and control system components. The implicit trapezoidal-rule (second order) integration is used on the describing equations of most elements that are modeled by ordinary differential equations. The result is a set of real, simultaneous, algebraic equations, which are solved at each time-step. These equations are written in nodal-admittance form, and are solved by ordered triangular factorization.

Studies involving use of the EMTP have objectives that fall in two general categories. One is design, which includes insulation coordination, equipment ratings, protective device specification, control systems design, etc. The other is solving operating problems such as unexplained outages or equipment failures.

Program Inputs

EMTP requires input data to describe the electrical network, control system information, initial conditions, the simulation case (time step size, duration of simulation), and the output requirements. The electrical network data is based on individual elements (lines, transformers, capacitors, etc.). Detailed descriptions of the data requirements for each element supported and the other data case requirements are provided in the EMTP User’s Guide. The basic elements of a data case are listed below.

− Time step size, length of time to be simulated
− Lumped branch data – resistance, inductance, capacitance
− Traveling wave models for transmission lines
− Nonlinear elements (current/voltage or current/flux points)
− Synchronous machine models
− Control system information (TACS – Transient Analysis of Control Systems)
− Desired outputs

One commonly used method for the creation of EMTP data files deals with use of “template” files. These files provide the necessary formatting and allow the user to concentrate on the data preparation. An example of template style data is illustrated below.

Program Outputs

The main output of an EMTP simulation consists of the magnitude vs. time points for node voltages (illustrated in Figure 1), differential voltages (node–node), and branch currents. Other outputs from the transient case can also be calculated by EMTP (energy, power, etc.) but it is generally easier to let the output processing program generate these supplemental signals from the actual voltage and current data.

The program performs a full steady state solution to develop initial conditions for the linear elements in the model. The initial conditions used for nonlinear elements depend on the specific model involved. The output from the steady state solution is also available in different levels of detail and can be very useful for debugging the model.

The various output quantities available include:

− Steady-state phasor solution – branch voltages and currents, bus voltages, power loss, and power flows

− Data points for bus voltages, branch voltages, branch currents, branch energy dissipation, machine variables, and control system variables

− Voltage magnitudes and angles as a function of frequency (frequency scan option)

− Statistical summary data for statistical cases

Figure 1 – Example EMTP Node Voltage Output Waveform

Study Procedure

The following is a suggested procedure for using EMTP to perform distribution system transient studies:

− Identify Study Objectives. The objectives will dictate the frequency range of interest, the modeling requirements, the variables to be investigated, and the types of output that are needed from the simulation.

− Determine Frequency Range of Interest. The frequency range will determine the type of component models required for the study, the required time step size, and the duration of the simulation. Some guidelines for determining the frequency range of interest and the impact on the required component models are provided in the Modeling Guidelines section of this report.

− Develop System Model. The extent of the system model depends on the capacitors and/or lines to be switched and the frequency range of interest. Obviously, it would be desirable for the model to include the entire system so you could just switch the device(s) of interest. However, the solution times for a very large model becomes excessive, and there is often limited improvement in accuracy beyond a more reduced model around the circuit of interest.

− Draw Connection Diagram and Label Buses. The bus labels will be used in the EMTP data file for identification.

− Develop Component Models. Each component model (transmission line, distribution feeder, transformer, capacitor, breaker, etc.) will depend on the frequency range of interest and the specific transient event being evaluated.

− Run a Steady State Solution Case. This case will verify system connectivity and provides a sanity check for many of the system components.

− Estimate Expected Results. This can be done from previous studies, from the literature, or from hand calculations. It is important to know what to expect from the simulation so that major problems can be identified quickly.

− Sensitivity Analysis for Important Variables. Important variables from the simulation should be evaluated to determine their impact on results. These could include breaker closing instants, transformer saturation, line length, capacitor size, etc.

− Develop Solutions. Possible solutions (i.e. pre-insertion resistors) are evaluated and design specifications are developed.

Simulation Process

The process for completing a transient simulation (shown in Figure 2) consists of first collecting and developing the necessary data to represent the circuit to be modeled. Often this system representation is completed by “describing” the interconnection and component values in a simple ASCII text file. This text file method is a hold-over from earlier times, when the data was read line-by-line with a card reader. After the data file (.DAT) has been created, it is submitted to the EMTP solver. The solver reads the data file, line-by-line, and reports any significant errors (to be discussed in greater detail in an upcoming section). Satisfied that the case will solve the EMTP generates a matrix representation of the interconnected system. Typically, solution of both a steady-state case and a transient case occur.

There are two forms of EMTP output available for viewing. First, an ASCII text output (.OUT) file is produced. This file contains a summary of how the EMTP interpreted the input data file (useful for debugging component values), a connectivity table, full output of the steady-state case, and the requested output for the transient case. This transient output is also stored in a binary file (.PL4) for post processing and viewing.

Figure 2 – EMTP Computer Simulation Process

Developing a System Model

One of the most important problems associated with developing a system model is: “How much of the system do I need to model?” Unfortunately, there are no rules to guide a user, it is often more of a feel that is developed over time. A good starting point for switching studies is to model one or two buses back from the switched bus. However, even this simple guideline fails from time-to-time. Perhaps the best method for determining the appropriate system model is to start with a small simple circuit that accurately represents the phenomena, and then add more of the system details to determine their impact on the solution result. Another factor in the system modeling question is model/simulation accuracy. Very often the goal of the study will determine the model complexity:

Selection of the time step is one of the most important decisions an EMTP user must make. Improper time step selection is analogous to selecting a monitoring device that samples a waveform at a slow enough rate that the transient of interest is partially or completely missed. There needs to be a balance between computational effort and accuracy when the time step is selected. The selection, much like the modeling question, is more of a feel then a hard and fast rule.

Frequency Ranges for EMTP Simulations

The study of electrical transient phenomena involves a frequency range from DC to about 60 MHz. Typically, electromagnetic phenomena involves frequencies above the power frequency, and electromechanical phenomena involves frequencies below the power frequency. Transient phenomena appear as transitions from one steady-state condition to another. The primary causes of these transitions are switching operations and lightning. Generally, the frequency of the resulting disturbance will fall somewhere in the following range (Table 1):

Table 1 – Frequency Range for Power System Transients

Model Verification

The single most important tool that the user has for verifying the EMTP case results is a basic knowledge of power system transients. Field test results, technical papers, basic textbooks, and more experienced engineers can all help. The textbook by Allan Greenwood, Electrical Transients in Power Systems, is a useful reference and it is recommended that the user review the basics of the phenomena before attempting to simulate it with the EMTP. Learning by doing can be very frustrating and applying the simulation results can be risky, when the user does not feel comfortable with the results of the study.

When verifying the results of an EMTP case, the user should always check the input parameter interpretation and network connectivity table. The steady-state solution should be checked to verify known quantities, such as bus voltage, branch currents, etc.

Pre-switching steady-state waveforms should be examined for characteristic harmonic content and the waveform should be allowed to reach a stable condition before any switching is done.

An example of this is the interaction between capacitor switching and adjustable-speed drives (ASDs). There are actually two transients events that occur during the simulation, however it only the second event – capacitor switching – that is of any interest. The first event, ASD starting, should be allowed sufficient time to reach a stable operating point before the capacitor is switched. There are a number of methods for accomplishing this task, however, at times the easiest method is to simply let the simulation run long enough to stabilize.

Evaluation and Presentation of Results

Upon completion of the transient simulation case, an evaluation of the accuracy of the results is required. As previously mentioned, it is desirable that the user have a basic understanding of the phenomena of interest. In essence, the user should know what the result should be (or at least a good idea of what the waveform should look like) before completing the case. In reality, however, this is not always the case, so it becomes even more important that the user have confidence in the accuracy of the data file.

Simulation results are generally presented in the form of overvoltage and overcurrent quantities. Overvoltages are generally quantified in per-unit of the maximum crest (peak) line-to-ground voltage. This applies for both line-to-line and line-to-ground transient voltages.

Presentation of simulation results may take a number of different forms (i.e. graphical, tabular, etc.). It may be just as important to present the result in a way easily understood by the audience, as it is to complete the simulation correctly. Failure of either results in no action taken.

The main output of an EMTP simulation consists of the magnitude vs. time points for node voltages (previously illustrated in Figure 1), differential voltages (node-node), and branch currents. Other outputs from the transient case can also be calculated by EMTP (energy, power, etc.) but it is generally easier to let the output processing program generate these supplemental signals from the actual voltage and current data. The various output quantities available include:

− Steady-state phasor solution – branch voltages and currents, bus voltages, power loss, and power flows
− Data points for bus voltages, branch voltages, branch currents, branch energy dissipation, machine variables, and control system variables
− Voltage magnitudes and angles as a function of frequency (frequency scan option)
− Statistical summary data for statistical cases

In addition, study results may take the form of summary tables and/or graphs that illustrate the results for multiple simulations. For example, one common method for presentation of results is in the form of an overvoltage vs. variable graph. The “variable” may be quantities like line length, transformer size, capacitor size, choke size, etc. It is much easier for the audience to understand the impact of a specific variable on the overvoltage range using this method (as opposed to page after page of simulation waveforms).

REFERENCES

Electrical Transients in Power Systems, Second Edition, A. N. Greenwood, John Wiley and Sons, New York, 1991.

Electromagnetic Transients Program (EMTP) Rule Book, Version 2.0, vol. 1, vol. 2, EPRI EL-6421-L, Electric Power Research Institute/DCG, June 1989.

Electromagnetic Transients Program (EMTP) Revised Application Guide, Version 2.0, EPRI EL-7321, Electric Power Research Institute /DCG, November 1991.

Electromagnetic Transients Program (EMTP) Primer, EPRI EL-4202, Project 2149-1, Electric Power Research Institute, September 1985

GLOSSARY AND ACRONYMS
ASD: Adjustable-Speed Drive
CT: Current Transformer
EMTP: Electromagnetic Transients Program
HVAC: High-Voltage Air Conditioning
MOV: Metal Oxide Varistor
PF: Power Factor
PWM: Pulse Width Modulation
TVSS: Transient Voltage Surge Suppressors

A Methodological Proposal for Monitoring, Analyzing and Estimating Power Quality Indices: the case of Bogotá-Colombia

Published by L. E. Gallego, Student Member IEEE, H. Torres, Member IEEE, F.A. Pavas, Student Member IEEE, D.F. Urrutia, Student Member IEEE, G. A. Cajamarca, and D. Rondón, Student Member IEEE.

Abstract—The Estimation of Power Quality (PQ) indices has a vital importance on the development of national PQ standards not only because provides truthful information about PQ conditions in our facilities, but also because permits to establish, with an own criterion, the values for the limits of the most common PQ disturbances. This paper proposes a methodology for the estimation of PQ indices based on statistical sampling and weighting factors techniques which are applied for commercial and industrial customers in the city of Bogotá. In addition, some strategies for the classification of the type of customer as well as some final obtained values of PQ indices in Bogotá are presented.

Index Terms— Power Quality, Indices, PQ disturbances, PQ monitoring, Statistical Sampling.

I. INTRODUCTION

ELECTRIC power quality has become an important issue in electrical system operation in last decades and has recently acquired an special interest due to the increasing use of new technologies such as power electronics, microprocessor-based controllers and other nonlinear devices. Consequently, many types of steady state disturbances as harmonic contamination, frequency variations and voltage fluctuations have been introduced to electrical supply networks. On the other hand, the deregulation of electric power industry in many countries has implied a restatement of the concept of power supply service. The introduction of issues such as competitive power markets and non regulated customers implies that the conditions in the relationship utilities-customers are now more demanding. In fact, the new criteria in power supply service go farther than simply providing reliability in service but also maintaining sinusoidal waveforms of voltage and current signals at rated values of amplitude and frequency.

On the other hand, regulating power quality issues based on foreign experiences that strongly differ from the own conditions seems not to be a practical solution. In addition, translation of standards without a previous knowledge of the electrical environment in which these standards are planned to be applied could lead to counterproductive measures. In this way, some power quality surveys are documented in the international literature [1]-[6], with the aim of defining particular electrical environments.

Thus, the research group on Acquisition and Analysis of Signals PAAS-UN of the National University of Colombia carried out a research project with an active participation of the major power supply company in Bogotá-CODENSA E.S.P-, the Colombian Institute of Technical Standards-ICONTEC- and the Regulatory Commission of Gas and Electricity-CREG. The main objective of this project was the monitoring and analysis for the estimation of statistically reliable PQ indices, initially for the city of Bogotá, and subsequently for the rest of the country.

II. PROBLEM DEFINITION

In the international literature exist some standards about PQ [13][14]. In Colombia, some by law regulations [15][16] have established criteria about some Power Quality issues, defining minimum values for reliability indices and establishing criteria of responsibility and economical reimbursement by the reliability of the supplied service. However, these reliability indices are just a part of the evaluation of Power Quality and reflect the lack of knowledge about the real state of the PQ disturbances in the distribution networks. In addition, due to the sensitivity of many commercial and industrial loads, reliability service is no longer indicated by the frequency and duration of interruptions occurring on the distribution system [17].

In Colombia, and specifically in Bogotá, there are no reliable PQ data that permit the estimation of PQ indices such as, sags, swells, flicker, harmonic pollution, transients, etc.

This is not to say that there is a lack of PQ monitoring data, on the contrary, there is a lot of widespread information resulting from particular case studies, but a lack of PQ data acquired in a systematic and planned manner that permit the estimation of PQ indices statistically reliable.

III. CLASSIFICATION OF CUSTOMERS

As a successive approach to the problem of evaluating PQ indices, a methodology for classifying and locating residential, industrial and commercial customers was developed. Two different methodological alternatives were explored. The first alternative consist in studying the Territorial Ordering Plan – TOP- for the city of Bogotá and the second alternative consist in classifying customers using available data provided by the local power supply company.

A. Territorial Ordering Plan – TOP

Taking into account that the present research project looks for a PQ characterization depending on the type of customer (residential, industrial or commercial), the built-up parameters and the use of soil represent important starting points in order to achieve any customer classification.

As a first alternative, the territorial ordering plan TOP for the city of Bogotá was explored. In general, TOP gives some ideas about the development and expansion plan of urban zones according to planned economic activities providing an organized growth of the city. As a result of this stage, a map with different layers representing and locating commercial, industrial or residential zones in the city was obtained. It is important to note that several zones of the city were not properly classified as a certain type of customer because of their non-definable economic activity. These zones are called here as “mixed zones”. The map above mentioned is shown in Fig. 1.

Fig. 1. Map showing the location of types of customers according to TOP.

B. Classification of customers using power consumption data

The second alternative attempts to classify customers by means of the available data provided by the local power supply company. This data contains information about circuit identification, rated voltage, type of demand, number of customers connected by circuit, etc.

Two criteria were relevant in the analysis of this information: number of customers and power consumption.

The former attempts to describe the impact in Power Quality due to the number of sources of the same type producing any PQ disturbance. The latter describes the influence in PQ due to the level of power consumption data providing an idea of the effect of injecting PQ disturbances to the system by a high power consumption load[18]. By this means, an ordering of the most representative circuits of the distribution network following both criteria was achieved, obtaining two different lists of circuits for each type of customer. An additional correlation was made between each pair of lists depending on the type of customer in order to select those circuits that were the most representative in both criteria (number of customers and power consumption level). In that way, a list of about 20 circuits for each type of customer was selected to be monitored during the measurements stage.

It is important to mention that not only a commitment between number of users and power consumption is important, but also their geographical location inside the city. With this purpose, the city was divided in three zones: north zone, downtown zone and south zone, and the selected circuits were clustered according to the substation that feed them. This clustering permit to observe the relevance of each type of consumption depending on the geographical zone and made easier the elaboration of a systematic monitoring plan.

IV. STATISTICAL SAMPLING

A description of the statistical sampling tools is presented in this section. These statistical tools were used with the aim of determining the size of a representative sample of each type of customer, given some intervals of confidence and some errors in the estimation of PQ indices.

Considering a sample of n elements, a characteristic in study y and the variable y_k representing the mentioned characteristic in the k-element, is possible to calculate the sample media y and the sample variance s² as follows [13]:

In general terms, the estimation of the sample size requires a previous knowledge of the population variance. This variance may be estimated based on a preliminary or pilot sample which could vary on size. In the case of big-size pilot samples, a normal distribution should be assumed and in the case of small size pilot samples a t-student distribution should be adopted [13]. For the last case, the estimation error e and the sample size s_n should be calculated as:

where variable t_1-α represents a t-student probability distribution value depending on the confidence level α.

The pilot sample consisted in a set of case studies achieved in industrial and commercial customers without overcoming the number of 30 studies; therefore a t-student distribution with n-1 degrees of freedom was used. Moreover, the number of total customers was considered high enough that the approach of infinite population size was considered valid. The confidence level and the estimation error were set in 95% and 20% respectively; in other words, the mean of a PQ index μ was estimated having a 95% of confidence that its value remains in the interval from 0.8μ to 1.2μ. Some statistical results for several PQ indices based on the pilot sample for commercial and industrial customers are shown in tables I and II respectively.

It can be observed from Tables I and II that the sample size necessary to estimate PQ indices is mainly determined by the index presenting the major variance. In this case the major variance is presented in the TDD index as it is expected. It is important to highlight that the lower error estimation, the higher the sample size, implying practically an approximately inverse quadratic relation between the error estimation and the sample size.

The final obtained sample size for commercial and industrial customers were 37 and 45 respectively, for a total of 82 measurements. It is important to note that working with a lower error (for instance 10%), implies to multiply by four the sample size (about 320 customers including commercial and industrial) which is a high number of measurements considering that the minimum monitoring period for some indices is 1 day. In addition, in a measurement plan is usual to discard some registers due to the lack of consistence in data, equipment failure or simply because some PQ events such as sags, swells, transients or flicker do not occur during monitoring; therefore, many times is necessary to carry out a major number of measurements in order to obtain the minimum required and reliable measurements. By this means, the error estimation value was set in 20 %.

TABLE I STATISTICAL PARAMETERS BASED ON A PILOT SAMPLE FOR COMMERCIAL CUSTOMERS

TABLE II STATISTICAL PARAMETERS BASED ON A PILOT SAMPLE FOR INDUSTRIAL CUSTOMERS

V. MONITORING

This section describes some details about the monitoring set up, the equipments used, the criteria in data analysis and the monitoring planning during the development of this project.

A. Equipment and monitoring set up

With the purpose of achieving the measurements it was important to maintain some common characteristics in monitoring. These characteristics are related to the point of measurement, the period of monitoring, and a common programming of the equipment. In general, the measurements were carried in low voltage side (<600V) at the PCC (Point of Common Coupling), the period of monitoring was planned in order to register PQ events in a typical duty cycle, over passing in most of the cases a period of 8 hours. Concerning to the programming of the equipment, the same triggers set up were maintained. Basically, four PQ analyzers were used during the monitoring as follows: AR4, AR5, AEMC and TOPAS1000. Several differences are present among these different equipments, especially in the memory capacity, which allows registering PQ events in different levels of resolution.

B. Data Analysis per customer

Due to the different equipments, several indices could be obtained directly from the software of each PQ analyzer. However, this methodology implies different ways of obtaining PQ indices with no control of the calculus in the software. In order to avoid this “black box” situation, the data was extracted from the equipment in a text file and was processed in a common manner for all the equipment depending on the PQ index. As a result of this methodology a PQ index per customer is obtained depending on the disturbance as it is explained next.

1) Voltage Unbalance

Voltage unbalance is defined as the maximum deviation from the average of the three-phase voltage, divided by the average of the three-phase voltages, expressed in percent. Following this methodology, a voltage unbalance profile must be obtained from the monitoring by calculating a voltage unbalance value in each monitoring interval. In order to obtain an estimation of this index per customer it was necessary to build a cumulative probability distribution for voltage unbalance and by means of the criterion of 95%, it was possible to determine which value of voltage unbalance was not surpassed during the 95% of the monitoring period.

2) Sags and Swells

Sags and swells are non-stationary phenomena, therefore it is not possible to build a cumulative probability distribution during a monitoring because of the lack of data; this led to estimate the index per customer as a simple mean of the sags and swells events in per unit p.u.

3) Total Harmonic Distortion THD

A profile of Voltage THD should be obtained along the period of monitoring. It is possible to build cumulative probability distributions for each profile depending on the phase. Again, the criterion of 95% was used for each profile, and the maximum value among the three phases is chosen as the estimation of this index per customer.

4) Total Demand Distortion TDD

This index is based on both THD values for current and the fundamental of the peak demand current. This peak demand current is calculated as the annual average of the maximum monthly demand current [14]. Unfortunately, the period of monitoring is not a year, but a day or at least a duty cycle, therefore, it was assumed that the behavior shown in the current profiles was the same during a year. In this way, this peak demand current is calculated as the average of the maximum current for each monitoring interval. Once this value is calculated, the procedure to estimate this index is similar to that followed in the THD index per customer.

5) Power Frequency variations

In general terms, these power frequency variations are uncommon and the estimation of this index was treated as a single mean value.

6) Flicker – P_st

This index was calculated by using a P_st profile obtained from the monitoring. The P_st values were transformed in a cumulative probability distribution and the value of the index
was estimated using the criterion of 95%, in other words, the value of P_st that was not surpassed during the 95% of the monitoring period.

7) Current Unbalance

The estimation of this index for each customer is similar to that followed for the voltage unbalance.

8) Power Factor

The power factor were divided in inductive and capacitive for each customer and a single mean value of the Power factor profiles were used as the final index.

9) Neutral Currents

This index was calculated as a ratio between the neutral current and the average of the three-phase currents. Once again, a profile was obtained and the criterion of 95% based on a cumulative probability distribution was used for estimate the value of this index.

C. Monitoring Plan

Given that the distribution of industrial, commercial and residential customers is non uniform along the city, it is not representative to program an equal number of measurements for the different geographical zones described in section III. Hereby, the city was divided in a grid with the aim of determining the spatial distribution for each type of customer. As a result of this distribution, it was possible to assign a different number of measurements depending on the geographical zone. The results are shown in Table III. It is important to note that a monitoring or measurement is a register in an individual customer that last at least a duty cycle.

TABLE III SPATIAL DISTRIBUTION AND REQUIRED MONITORINGS ACCORDING TO THE TYPE OF CUSTOMER

VI. ESTIMATION OF PQ INDICES

In general terms, the problem of estimation of PQ indices consist on estimating a value for a specific PQ equivalent index for the entire city, based on the values of the data analysis per customer described in numeral B of section V.

Power quality in a specific node of the utility system is affected by the contributions of all users connected to that node; consequently, the value of a particular PQ index must be calculated taking into account these contributions. In addition, contribution of different users are generally not uniform because of their power consumption, frequency response, harmonic spectra, etc., hence, calculation of total indices must account for such characteristics.

On the other hand, PQ disturbances have their characteristic spectra and could be studied focusing the analysis in those frequencies. Monitoring equipment allow sampling voltage and current waveforms, consequently, frequency spectra can be estimated using a finite number of components [15]. We suppose that sampling frequency and the number of cycles registered are correctly selected to obtain frequencies related to PQ disturbances under study, such us flicker, harmonics, interharmonics, etc. Available equipment can register disturbances with frequencies between 0 and 3kHz.

The equations used to calculate the value of PQ indices use a one-phase equivalent, applicable only under a balanced condition, which is a very rare situation, moreover, when signals with frequency components different to fundamental frequency are present [16]. Nevertheless, this is a good approach to obtain more accurate values of PQ indices.

A. Classification of PQ indices

In order to estimate the value of a particular PQ index it is important to take into account the topology of the distribution network. The proposed distortion indices are valid just for the case of radial distribution systems.

The PQ indices estimation must account for the particularities of each PQ disturbance. For this purpose, the authors propose a classification of the PQ indices in voltage-related indices and current-related indices.

B. Voltage-related indices

Voltage-related indices are related to Voltage disturbances and their values do not strongly depend on the power consumption of the customer. The proposed way of calculating these types of PQ equivalent indices is similar to that of an r.m.s value, as it is shown in (5):

where
Ind_EQ : Voltage-related equivalent index.
Ind_i : Voltage-related index of a single customer i.
N : Number of customers.

In case of obtaining non-sparse values for the voltage-related indices, the rms value may be approached to a mean value as it is shown in (5).

The voltage-related indices finally considered were short-duration voltage variations (sags and swells), long-duration voltage variations, power frequency variations, flicker, voltage unbalance and voltage harmonic distortion.

C. Current-related indices

Current-related indices are related to Current disturbances and their values strongly depend on the power consumption of customers. The value of an equivalent index for PQ disturbances such as current harmonic distortion must be calculated in a different way from that used to estimate voltage-related indices. The reason for this difference is based on the fact that customers with grater power consumptions inject greater distortions to the distribution network as well.

The proposed way of calculating these types of PQ equivalent indices uses a quadratic weighting of customer’s power consumption, as it is shown in (6):

where
S_Li : Maximum power consumption of customer i.
Ind_EQ : Current-related equivalent index.
Ind_i: Current-related index of a single customer i.
N : Number of customers

The current-related indices finally considered were current unbalance, current harmonic distortion, power factor and neutral currents.

VII. ANALYSIS OF RESULTS

As it was mentioned before, the aim of the study is to estimate values for PQ indices using measurements and available information about the distribution system network. Monitoring provides information about PQ phenomena and power consumption. The final calculation of PQ indices took into account the total number of measurements (121) which were preprocessed and some measurements were discarded due to data errors. This number of 121 measurements differs from the initial 82 measurements required in section IV due to the availability of additional PQ monitors during the monitoring stage, which led to smaller estimation errors (<15%).

From the PQ indices considered in IEEE 1159 [14], only the transients category was not included in the final results because of some technical requirements as sampling rates and memory capacity in the PQ monitors, that hindered the collection of reliable transient waveforms. In addition, other indices were finally considered such as power factor, neutral currents, and current unbalance, providing important information about some Power quality related problems.

In this manner, the PQ indices were obtained depending on the type of customer and the geographical zone within the city. For the purpose of presenting the final results, the PQ indices were divided in two groups: voltage-related indices and current-related indices.

A. Voltage-related indices

As it was mentioned before, these indices are related to Voltage disturbances and consider short-duration voltage variations (sags and swells), long-duration voltage variations, power frequency variations, flicker, voltage unbalance and voltage harmonic distortion. The results are shown in Table IV.

According to the study, the expected value of a sag event in Bogotá is 0.64 p.u. which could led to undesirable shutdown events, especially in some automated industrial processes, that may have a considerable economic impact. On the other hand, the expected value of swells of 1.06 seems not to be a problem, because this value is within the common operation range of equipment. In addition, none of the customers experienced long-duration voltage variations or power frequency variations.

In the case of flicker, the results shown that P_st values for Bogotá are practically exceeded for the industrial customers according to IEC 61000-4-15 [17] and for the total case the P_st value is just over the limit (1.01).

TABLE IV VOLTAGE-RELATED INDICES FOR INDUSTRIAL AND COMMERCIAL CUSTOMERS

With respect to voltage harmonic distortion, the results shown that for the total case, the expected value of THD (4.1%) do not exceed the limit proposed by the Standard IEEE519[14]. Moreover, the large individual voltage harmonics are 3^o, 5^oand 7^o. However, this THD expected value should be complemented with the percentage of customers who are out of the limit proposed by IEEE 519, which for the case of Bogotá is 12%. In this manner, the convenience and the possible economic impact of adopting IEEE519 limit values in a national standard should be established.

In addition, most of the measured THD values are in the range of 3-5 %, which means that the THD is close to the IEEE519 limit value, and can be reached in a few years if no corrections are implemented.

Finally, the value of voltage unbalance index seems not to be a problem because this values is less than 2%, which is the limit value proposed by the standard IEC 61000-2-2 [18].

B. Current-related indices

As it was mentioned before, these indices are related to current disturbances and consider current unbalance, current harmonic distortion, power factor and neutral currents. The results are shown in Table V.

TABLE V CURRENT-RELATED INDICES FOR INDUSTRIAL AND COMMERCIAL CUSTOMERS

According to the study, the expected value of current unbalance in Bogotá is 39.2% which is an indicative of some bad practices in the design of electrical installations, that could led to some related PQ problems.

About current harmonic distortion, the results shown that for the total case, the expected value of TDD is 12.5%. Moreover, the large individual current harmonics are 5^o, 7^o and 11^o. Similarly to the case of harmonic voltage distortion this TDD expected value should be complemented with the percentage of customers who are out of the limit proposed by IEEE519, which for the case of Bogotá is 19%. Obviously the TDD value for each customer were compared with IEEE519 values taking into account the ratio between the short circuit current and the maximum demand load current (I_sc/I_L) at the Point of Common Coupling PCC.

For the measurements in which the PCC do not coincided with the point of the measurement (Low voltage side), -for instance PCC located at the high voltage side-, the value of TDD were recalculated taking into account the connection group of the transformer in order to consider the flux of zero-sequence harmonics to the distribution network.

Again, this percentage of customers out of the IEEE519 limits helps to establish the convenience and the possible economic impact of adopting IEEE519 limit values in a national standard, because that 19% of customers “out of limits” should either install harmonic mitigation equipment such as compensators, active filters, etc., or should change their old-fashion industrial equipment, which is a common situation in a developing country that implies great investments.

VIII. CONCLUSION

A methodology for acquiring PQ data in a systematic and planned manner in order to estimate PQ indices statistically reliable was presented. This methodology accounts for a classification of customers according to power consumption levels and geographical location. Some statistical tools were used for determining the size of a representative sample and a suitable planning of monitoring as well. A methodology is proposed for calculating values associated to PQ indices based on the existing relation between PQ disturbances and power consumption. Consequently, the obtained values for certain PQ indices in Bogotá-Colombia are presented. This project is a contribution to the knowledge of Power Quality conditions in Colombia and an effort for establishing the limit values for the most common PQ disturbances with the aim of contributing to local by law PQ regulations.

REFERENCES

[1] M. Goldstein and P. D. Speranza, “The quality of U.S. commercial ac power,” in Proc. IEEE INTELLEC, 1982, pp. 28–33.
[2] M. B. Hughes and J. S. Chan, “Canadian National power quality survey results,” in Proc. EPRI PQA’95, New York, NY, May 9–11, 1995.
[3] D. Dorr, “Point of utilization power quality study results,” IEEE Trans. Ind. Applicat., vol. 31, pp. 658–666, July/Aug. 1995.
[4] D. D. Sabin, T. E. Grebe, and A. Sundaram, “Surveying power quality levels on U.S. distribution systems,” in Proc. 13th Int. Conf. Electricity Distribution (CIRED’95), Brussels Belgium, May 1995.
[5] F. D. Martzloff and T. S. Gruzs, “Power quality site surveys: Facts
fiction and fallacies,” IEEE Trans. Ind. Applicat., vol. 24, pp. 1005–1018, Nov./Dec., 1988.
[6] M.Fayyaz; S.Mumtaz,S.;“A sample power quality survey for emerging competitive electricity market in Pakistan” Multi Topic Conference, IEEE INMIC 2001. Technology for the 21st Century. Proceedings. IEEE International 28-30 Dec. 2001 pp 38 – 44.
[7] IEC 60000-1-1 Electromagnetic compatibility (EMC) – Part 1: General – Section 1: Application and interpretation of fundamental definitions and terms.
[8] IEEE Recommended Practice for monitoring Electric Power Quality. IEEE Std 1159
[9] Resolution CREG 070 of 1998. Commission of Regulation for Gas and Electricity of Colombia. Available online: http://domino.creg.gov.co/PUBLICAC.NSF/Indice01/Resoluci%C3%B3n-1998-CREG070-98
[10] Resolution CREG 096 of 2000. Commission of Regulation for Gas and Electricity of Colombia. Available online: http://domino.creg.gov.co/Publicac.nsf/Indice01/Resoluci%C3%B3n-2000-CREG096-2000
[11] R. C. Dugan, Brooks D. L, M. Waclawiak, A. Sundaram, “Indices for Assessing utility distribution system rms variation performance”. IEEE Trans. On Power Delivery, Vol . 13, No. 1, pp 254-259. January 1998.
[12] Electrical Power Systems Quality. R Dugan, M McGranaghan and W. Beaty. 1st ed. McGraw Hill. 1996.
[13] A. Moreno, F. Jauffred. “Elementos de probabilidad y estadística”. Alfaomega. 1993.
[14] IEEE Recommended practice and requirements for harmonic control in Electric Power Systems. IEEE std 519-1992
[15] A. Oppenheim, R. Schafer. “Discrete-time signal processing”. Prentice Hall. 1989
[16] J. Arrillaga, C.P. Arnold. “Computer analysis of power systems”. John Wiley and Sons. 1995
[17] IEC 61000-4-15 Electromagnetic Compatibility (EMC) – Part 4. Testing and measurement techniques – Section 15: Flickermeter – Functional and design specifications. 2003
[18] IEC 61000-2-2. Electromagnetic compatibility (EMC) – Part 2-2: Environment – Compatibility levels for low-frequency conducted disturbances and signalling in public low-voltage power supply systems. 2002

All the Authors are with the Electrical Engineering Department, National University of Colombia – Research program on acquisition and analysis of signals PAAS UN. Bogotá –Colombia (e-mail: lgallegov@unal.edu.co).

This research project conducted by the research program on Acquisition and Analysis of signals of the National University of Colombia-PAAS UN is a contribution for the determination of PQ indices in order to be included in the Colombian PQ standard.

This work was supported by the Colombian council of science and technology – COLCIENCIAS, CODENSA E.S.P, CREG and ICONTEC.

Overview of ISO/RTOs

Published by Mike Ross, Senior Vice President, Government Affairs and Public Relations, Southwest Power Pool. Date: February 16, 2017

Presented by WIRES – a national coalition of entities dedicated to investment in a strong, well-planned and environmentally beneficial electricity high voltage transmission system in the US.

Feeder Lightning Transients

Published by Electrotek Concepts, Inc., PQSoft Case Study: Feeder Lightning Transients, Document ID: PQS1101, Date: March 15, 2011.

Abstract: Lightning strokes to exposed utility transmission or distribution circuits can inject a significant amount of energy into the power system in a very short time, causing deviations in voltages and currents which persist until the excess energy is absorbed by dissipative elements (e.g., arresters). This case study presents a distribution feeder lightning transient overvoltage evaluation.

FEEDER LIGHTNING TRANSIENT CASE STUDY

A utility distribution system lightning transient analysis case study was completed for the system shown in Figure 1. The case study investigated the potential for severe high frequency transient overvoltages on distribution feeder primary and customer secondary buses during a lightning strike on the feeder primary. The power conditioning mitigation alternative of MOV surge arresters was also evaluated.

The simulations for the case study were completed using the PSCAD^® program. A high-frequency transient model was created to simulate the lightning transients and resulting overvoltages and arrester energy duties. A high-frequency model was required to accurately represent the very high lightning transient frequencies. The lightning surge was assumed to be a current source with a very fast rise time (e.g., 8×20μsec).

The modeled circuit consisted of a 138 kV utility substation supplying a 50 MVA, 138kV/34.5kV substation transformer. A high frequency, distributed parameter transmission line model was required to accurately represent the traveling wave (reflections) effects during the lightning transient. Two 34.5 kV distribution feeders were included in the model. The first feeder consisted of 5-mile and 15-mile overhead feeder segments that were modeling using the distributed parameter transmission line model. The second feeder included 3-mile and 9-mile underground cable segments that were modeled using the frequency dependent cable model. Both line and cable constants were determined and the data was used to help validate the system model.

Traditional inductive transformer models generally look like an open circuit to the very high frequency lightning transients. Therefore, the 60 Hz transformer model can be improved by adding capacitances between windings and from the windings to ground. This type of model will act as a capacitive voltage divider to transfer a portion of the surge from the primary to the secondary windings. Bushing and winding capacitance values for the substation and customer step-down transformers were assumed based on typical data. Other substation equipment, such as circuit breakers and instrument transformers, are represented by their stray capacitances to ground. Typical stray capacitance values of substation equipment are provided in Annex B of IEEE Std. C37.011.

Figure 1 – Illustration of Oneline Diagram for Lightning Transient Overvoltage Evaluation

Lightning is a weather-related phenomenon that is often thought to be the principal cause of most high frequency transients. Energy from lightning strokes may enter the power system in several ways. A direct stroke to exposed equipment (e.g., overhead distribution feeder) is the most obvious. Because of the high-frequency and high-energy associated with a lightning flash, it is also possible for significant energy to be coupled into the power system from indirect strokes as well. Finally, in situations where more than one ground reference exists, it is possible for the potential difference generated by conduction of stroke current to ground to be conductively coupled into equipment. This can be especially important for computer and communications equipment.

Susceptibility of the power system to lightning is best characterized statistically, since the occurrence rate and stroke current magnitudes of lightning ground flashes is otherwise impossible to predict. Based on years of observations, the incidence of cloud-to-ground lightning flashes has been related to the level of thunderstorm activity, or isokeraunic level, in a general region. Magnitudes of lightning stroke currents range from 2 kA to 200 kA, although the probability of very small or very large magnitude is low. The average lightning surge current is approximately 30 kA.

When lightning strikes a portion of the power system directly, a voltage impulse equal to the product of the stroke current and the equivalent surge impedance of the power system will be created. The surge will propagate in all directions on the power system, dividing amongst all available paths at terminations. Energy may also be coupled into circuits that are not directly connected to the stricken system. The rapid rate-of-rise and high magnitude impulse will result in operation of surge arresters or flashover of line or equipment insulation. The high energy associated with a direct strike to the power system can easily exceed the withstand capability of surge arresters or other protective devices since they are not designed for this severe contingency.

Transient surges coupled into the power system from indirect strokes will propagate in a similar manner. While utility system protective equipment will operate properly and be able to withstand such an occurrence, there are mechanisms by which the effects of the indirect stroke can affect customer utilization equipment. High currents diverted into the grounding system by surge arresters will raise the potential of a local ground grid well above that of “true earth.” This “ground potential rise” (GPR) is of no consequence for equipment referenced only to the affected grid; there are situations however, where connections to remote ground references can result in misoperation or equipment damage under these conditions. Shielded communications and data circuits may be especially susceptible. Circuits connecting nearby buildings may be exposed to GPR should the building ground grids be separated electrically and one of them is struck by lightning. Under these conditions, an “isolated” computer ground can be a source of damaging or even lethal voltages and for this reason should never be used.

When evaluating these disturbances, it is important to remember that the stress on equipment is based on the impulse magnitude and duration plus the magnitude of the fundamental component at the instant of the impulse. The most common cause of impulsive transients is lightning. Due to the high frequencies involved, impulsive transients are generally damped quickly by resistive components in the circuit (e.g., conductor and transformer resistance). These transients are most prevalent very close to the disturbance that causes the transient (e.g., lightning, switching event, etc.) and there can be significant differences in the transient characteristic from one location within a facility to another.

Figure 2 shows two representative lightning current waveforms commonly used in transient simulation studies. The figure shows a 20 kA—1.2×50 μsec and a 20 kA—8×20 μsec lightning stoke current characteristic. The simulation was completed using the PSCAD program.

Figure 2 – Example Representative Lightning Current Waveform

The first simulation (Case 1) case involved a lightning strike to the 34.5kV feeder #1 at the Customer #1 primary bus (Phase A) with no MOV arresters included in the model. The specifications of the lightning current waveform were a 10 kA magnitude and an 8×20 μsec characteristic. The simulated lightning current waveform is shown in Figure 3.

Figure 4 shows the resulting feeder primary voltage for Case 1. The peak transient voltage with no arresters included in the model was 243.7 kV. The waveform illustrates voltage reflections from the ends of the overhead feeder and underground cable segments. Figure 5 shows the corresponding substation bus voltage, which has a peak voltage magnitude of 192.5 kV and Figure 6 shows the Customer #1 secondary bus voltage, which has a peak voltage of 3212.9 V.

A 27 kV MOV arrester was included on the primary winding of the Customer #1 transformer for Case 2. The assumed ratings for the arrester included:

Rated Voltage (Duty Cycle): 27 kV
Maximum Continuous Operating Voltage (MCOV): 24.4 kV
Maximum Energy Discharge Capability: 2.0 kJ/kV_{rated MCOV}
Maximum Energy Discharge Capability: 48.8 kJ
10kA, 8×20μsec Discharge Voltage: 73.1 kV

Figure 3 – Lightning Surge Current Waveform for Case 1

Figure 4 – Feeder Primary Voltage Waveform for Case 1

Figure 5 – Substation Bus Voltage Waveform for Case 1

Figure 6 – Customer Secondary Bus Voltage Waveform for Case 1

Case 2 involved a lightning strike to the 34.5kV feeder #1 at the Customer #1 primary bus with the 27 kV MOV arrester included in the model. Figure 7 shows the resulting feeder primary voltage. The peak transient voltage with the arrester included in the model was 70.1 kV, which was approximately equal to the arrester’s 10 kA discharge voltage.

The simulated arrester energy duty was 8.0 kJ, which was approximately 16% of the assumed energy capability. Figure 8 shows the corresponding Customer #1 secondary bus voltage, which has a peak voltage of 961.5 V.

A low voltage surge arrester was included on the secondary winding of the Customer #1 transformer for Case 3. The assumed ratings for the arrester included:

Rated Voltage (Duty Cycle): 277 V
Maximum Continuous Operating Voltage (MCOV): 305 V
Maximum Energy Discharge Capability: 2,200 J
10kA, 8×20μsec Discharge Voltage: 910 V

Case 3 involved a lightning strike to the 34.5kV feeder #1 at the Customer #1 primary bus with both the primary and secondary arresters included in the model.

Figure 9 shows the resulting feeder primary voltage. The peak transient voltage with the primary arrester included in the model was 70.1 kV. Figure 10 shows the corresponding Customer #1 secondary bus voltage with the secondary arrester included in the model. The peak voltage was reduced from 961.5 V to 672.8 V. The energy duty for the secondary arrester was less than 10 J.

Figure 7 – Feeder Primary Voltage Waveform for Case 2

Figure 8 – Customer Secondary Bus Voltage Waveform for Case 2

Figure 9 – Feeder Primary Voltage Waveform for Case 3

Figure 10 – Customer Secondary Bus Voltage Waveform for Case 3

SUMMARY

This case study summarized a distribution feeder lightning transient overvoltage evaluation. A high-frequency transient model was created to simulate the lightning transients and resulting overvoltages and arrester energy duties. A high-frequency model was required to accurately represent the lightning phenomena. Surge arresters were evaluated as the power conditioning alternative.

REFERENCES

“IEEE Recommended Practice for Monitoring Electric Power Quality,” IEEE Std. 1159-2009, IEEE, June 2009, ISBN: 978-0-7381-5940-9.
“IEEE Application Guide for Transient Recovery Voltage for AC High Voltage Circuit Breakers Rated on a Symmetrical Current Basis,” IEEE Std. C37.011-1994, IEEE, ISBN: 1 55937-467-5.
“Electrical Transients in Power Systems,” Allan Greenwood, Wiley-Interscience; Second Edition, April 18, 1991, ISBN: 0471620580.
R.C. Dugan, M.F. McGranaghan, S. Santoso, H.W. Beaty, “Electrical Power Systems Quality,” McGraw-Hill Companies, Inc., November 2002, ISBN 0-07-138622-X.

RELATED STANDARDS
IEEE Std. 1159, IEEE Std. C37.011

GLOSSARY AND ACRONYMS
ASD: Adjustable-Speed Drive
CF: Crest Factor
DPF: Displacement Power Factor
PF: Power Factor
PWM: Pulse Width Modulation
THD: Total Harmonic Distortion
TPF: True Power Factor

Steel Plant Transformer Operational Issues

Published by Tadeusz GLINKA¹,², Marek GLINKA²
Politechnika Śląska w Gliwicach (1), BOBRME Komel (2)

Abstract. Design of steel-plant furnace three-phase transformer (110 kV/(350 to 500) V, 50 kA) and its operating conditions are described in the paper. After three months of operation this transformer failed. Cause of failure, its course and damage to transformer winding are presented. Recommendations for transformer winding design and its installation and protection are given.

Streszczenie. W artykule opisano budowę trójfazowego transformatora piecowego 110 kV/(350 do 500) V, 50 kA i warunki jego pracy w miejscu zainstalowania. Transformator, po trzech miesiącach pracy, uległ awarii. Opisano przyczynę awarii, jej przebieg i uszkodzenie uzwojenia transformatora. Podano zalecenia dotyczące wykonania uzwojenia transformatora i zalecenia dotyczące jego zainstalowania i zabezpieczenia. (Problemy eksploatacyjne transformatora hutniczego).

Keywords: steel plant furnace transformer, transformer failure, transformer repair, transformer protection.
Słowa kluczowe: transformator piecowy, awaria transformatora, naprawa transformatora, zabezpieczenie transformatora.

Transformer’s design and installation

Steel plant transformers are electrical devices providing electrical energy needed in the manufacturing process. The processing requires current control and this is achieved by voltage control (regulation). Usually this is a step voltage control. The necessity of continuous voltage control, that is controlling output voltage when transformer is on load, is a feature distinguishing steel plant transformers design from power engineering transformers (unit and distribution transformers). In case of power engineering transformers, service manuals have been elaborated [1]. The current paper describes a steel plant transformer used to heat liquid steel in the continuous casting processing line. Here the converter’s liquid steel is reheated and ameliorated in ladle arc furnace of 300 Mg holding capacity. The furnace is supplied from two transformers, the main transformer (#1) and booster transformer (#2) connected as shown in Figure

Transformers are placed in a common tank and they constitute one supply circuit with step-controlled voltage. The ratings are as follows: power: (40 000 ÷ 26 327) kVA; primary winding W1: 110 kV; (209,9 ÷ 138,2) A; control windings W2-W3: 15238 V; / (840 ÷ 754) A;
secondary winding W4: (514 ÷ 304) V; /(44,9 ÷ 50) kA. The primary winding (W1, marked as high tension voltage GN) of transformer #1 is star-connected and supplied from 110 kV distribution substation by a cable line c. 3 kms long. The distribution substation bus voltage is stepped up and equal to 119 kV. Large power synchronous machines operate in the plant so that the network is overcompensated.

Transformer bay in distribution substation is equipped with a circuit breaker (WS1), disconnector and surge limiters. The secondary winding (W4, marked as DN – low tension voltage) embraces both columns of transformers #1 and #2 and is delta-connected; it is carried outside transformer chamber via bus and connected to furnace electrodes with bundles of elastic wires. Voltage control is achieved with the help of medium voltage winding (winding W2), which is placed in transformer #1 core. Winding W2 is equipped with taps connected with on-load tap changer. There are 13 taps. The control winding W2 supplies the primary winding W3 of booster transformer #2. W2 and W3 windings are star-connected; the neutral points of both star arrangements are connected and earthed via 17 Ω resistance.

The short-circuit voltage between winding W1 (high tension) and winding W4 (low tension) for tap #1 (output voltage 304 V) is equal to 10.93 %, while for tap # 13 (output voltage 514 V) is equal to 7.46 %. The circuit breaker switch (Q1) in medium voltage circuit connects control winding W2 of main transformer (#1) and primary winding W3 of booster transformer (#2). Surge limiters are installed at both sides of Q1 circuit breaker switch. Contactors rated at 1200 A are used as short-circuiting switches 3KM and 4KM of low tension winding W4. They are placed in transformer chamber. The QW short-circuiting switch is a remotely-operated disconnector and is placed outside the transformer chamber.

Fig. 1. Electrical scheme of furnace transformer circuit

W4 winding output terminals and short-circuiting switches 3KM, 4KM and QW are connected by 4 meters long copper cable of 95 mm² crossection. This cable runs over transformer tank. Transformer and accompanying devices are placed in a brick chamber in plant manufacturing house.

During normal operation of ladle furnace, the QS1 breaker is closed, the circuit breaker Q1 is closed, and the short-circuiting switches 3KM, 4KM and QW are open. Furnace electrodes current control is accomplished by tap changer present in transformer tank. The switch-over of the transformer from normal (on-load) operation to idle run (no-load) is conducted in accordance with following sequence of events:

Q1 circuit breaker is tripped (opened); this causes decrease in load and electrode arc goes out, since booster transformer 2 is not supplied and its secondary winding W4 acts as a reactor with a large inductance,
electrodes are automatically raised,
contactor 3KM is closed and this causes short-circuiting and earthing of DN circuit via resistors R = 1.6 Ω; short circuit state lasts for 3 seconds,
contactor 4 KM is closed, which causes direct short-circuiting and earthing of DN circuit, 3 KM contactor is opened,
if necessary, disconnector QW is closed; this is done by the servicemen eg. when electrodes are lengthened or if current paths connecting DN winding with the electrodes are subjected to maintenance.

Disconnector QW, which doubles the function of short-circuiting switch 4KM is located outside the transformer chamber, since for safety reasons the servicemen must be able to observe the condition of disconnector knife contacts and to make sure that the current path is earthed; only then the maintenance can be performed.

The switchover to ladle transformer normal operation is done by opening the short-circuiting switches QW and 4KM, switching the circuit breaker switch Q1 on and lowering the electrodes until the electric arc is started. The power switch QS1 is coupled via auxiliary contacts with circuit breaker Q1 so that they are interlocked. The circuit breaker Q1 is in turn coupled via auxiliary contacts with short-circuiting switches 3KM, 4KM i QW; this coupling prevents switching Q1 on if DN circuit is short-circuited.

Transformer failure

The investigated transformer was brand new when it was installed and put into operation in July. The failure occurred in October, so it operated only three months. The failure took place during switching the transformer from no-load state to on-load operation. When switch Q1 was closed, emergency cut-off took place, via power switch Q1 installed on the switchboard. The QS1 switch was tripped after 70 ms has passed. The gas-filled protection was also actuated (this breaker constituted the second stage of transformer protection) as well as protections on both medium tension (SN) windings. The surge limiters installed at both sides of Q1 breaker did not operate. The short-circuiting switch 4KM was on and cable connecting low tension winding (DN) with the short-circuiting switch was burned out (gone). The transformer operated in shorted circuit. The bushing insulators were burned and completely damaged by electric arc.

Fig. 2. View of transformer tank cover; locations of bushing insulators and arcing faults are marked

Electric arc occurred between insulators 3A – 2B and 3B – 2C, as shown in Figure 2. Traces of burning by electric arc were also observed at DN winding leads. This arc caused three-phase arcing fault of main transformer SN winding. The measurements conducted sometime after the failure showed that main transformer SN winding had been damaged. The chromatographic tests of gases dissolved in transformer oil and gases obtained from gas-flow relay showed existence of internal short-circuit in the transformer.

Transformer was then moved to the plant where it had been manufactured. When it was taken out of the tank and partially disassembled the following observations were made:

high tension (110 kV) W1 winding had not been damaged,
medium tension (SN) W2 winding of main transformer had been damaged by electrodynamic forces,
medium tension (SN) W3 winding of booster transformer had not been damaged,
low tension (DN) W4 windings of both transformers had
not been damaged

Description of W2 winding damage

W2 winding consists of two layers. The first layer lies immediately next to transformer’s core and is a reversible control winding with 6 taps. The second layer is the basic medium tension winding SN. In phases A B and C the basic winding was pushed up and the control winding down, by 8 to 15 centimetres. Moulding rings made of Elkon transformer plywood broke into several parts and screws keeping the winding in place were driven into the Elkon rings and bent. As a result of insulation layers shift the insulation was locally damaged. Short-circuiting of control circuit (one tapping step) occurred in phases A and B in the very locations where insulation had locally failed. Short-circuiting sites showed small insulation burn-outs and copper melting.

Why did failure occur?

The interlocking between circuit-breaker Q1 and short-circuiting switch 4KM were set up with help of auxiliary contacts. When auxiliary contacts of 4KM switch were closed, then they blocked tripping (switching on) of Q1 circuit breaker and vice versa. Dust with insulating properties is produced and emitted during continuous casting process. The transformer chamber was not air-tight. Dust was able to get into the chamber and, since electrical devices operating in the chamber were live, the chamber was never cleaned. Dust was deposited on auxiliary contacts of 4KM short-circuiting switch and, in time, the contacts became isolated and did not block Q1 circuit switch. Therefore when the short-circuiting switch 4KM was on, the circuit breaker Q1 could have been switched on likewise. Transformer tank cover, the bushing insulators and the wires were all coated with dust. When circuit breaker Q1 was switched on and lower tension winding DN was short-circuited, the electrodynamic forces generated by short-circuit current were such, that the transformer cover was dislodged and the dust cloud rose into air. The short-circuit current at DN side was calculated to be equal to c. 230 kA and current density in short-circuiting cable was equal to c. 2400 A/mm². With this current density, the copper wire melted after c. 50 ms; between the ends of burned wire electric arc was generated and this caused copper evaporation. Electrodynamic forces present in the arc ejected the copper particles onto the DN winding terminals and to SN bushings. The space between bushings became conductive and this led to arc-type short-circuit between insulators 3A-2B i 3B-2C as shown in Figure 2. This is a short-circuit of main transformer (transformer #1), and this transformer’s short-circuit rated voltage is very small. The short-circuit current rose, and electrodynamic forces generated in the windings increased in proportion to squared current value. The main transformer was not designed to withstand this type of short-circuit.

What errors were committed?

After analysing transformer operating conditions, transformer’s suitability to supply voltage and its design, we get the impression that several undesirable events took place at the same time. These events can be enumerated as follows:

errors in transformer design assumptions,
design and construction defects,
and the greatest errors, which constituted direct cause of failure: transformer’s operating conditions and the setup of contactors’ interlocking.

Transformer design data

The primary (high tension) winding was designed for rated voltage equal to 110 kV. The supply voltage was 199 kV, that is 8.2% higher than rated voltage; hence the short-circuit current went up by 8.2% as well and the electrodynamic forces generated in winding rose by 17%. The second error related to transformer chamber and its lack of dust-tightness. The plant manufacturing house, where continuous casting processing line is located, is full of dust created during manufacturing processes. This dust freely flowed into transformer chamber, mainly through ventilation ducts and deposited itself on all devices present inside the chamber. Electrical devices operating in the chamber were live, so that the chamber was never cleaned and dust not removed.

Transformer design and construction defects

The control winding W2 has been designed with taps. When tap is connected into the circuit, only part of the winding operates and it is placed non-symmetrically in the column in relation to primary winding W1 (Fig. 3). This asymmetry is particularly significant in case of tap No.1. This tap was connected during the investigated short-circuit event.

During second stage of short-circuit, the ampere turns of W1 and W2 windings were equal to each other, this may be concluded from theory of transformers [2,3]. The said asymmetry generates magnetic fields in transformer window: longitudinal field B_y and transverse field B_x, The interaction of these fields and windings current produces electrodynamic forces, this is shown in Figure 3. Figure 3 is of course only a model illustrating generation of forces F_x i F_y, and in particular axial force F_y which became the destructive force. The F_y might be smaller if the active part of W2 control winding at each tap was distributed uniformly along the column height, since the B_x flux density component is then minimum (see Fig. 4).

Fig. 3. Active parts of transformer #1 (marked) during the short-circuit-event; directions of electrodynamic forces are shown and distribution of flux density in transformer window

Errors in control and protection circuit

The biggest error and the direct cause of the failure was a mistake made during the design of control and protection circuits. The interlocking of circuit breaker Q1 and short-circuiting stitch 4KM was prone to failure. The other error was placing of short-circuiting switch 4 KM directly in transformer chamber and locating the earthing cable (from W4 terminals to 4KM switch) on the transformer tank surface.

Fig. 4. Correct execution of transformer #1 control winding

Conclusions

Transformer failure has been analysed thoroughly and in detail by experts. Their recommendations were:

to set up second interlocking between circuit breakers Q1 and 4KM, eg. based on current measurements in holding coils of Q1 and 4KM breakers (obligatory measure),
to connect earthing cable to DN (low tension) current cables outside the chamber; short-circuiting switches 3KM and 4KM should be installed outside the chamber (obligatory measure),
high tension winding W1 should be manufactured for rated voltage equal to 120 kV,
taps of control winding W2 should be distributed along the column height (as shown in Fig. 4); the clamping of moulding Elkon rings should be changed from pointwise to surface-wise; the ring holding should be strengthened (thickened),
transformer chamber should be sealed, air-blast should be introduced and chamber pressure kept at all times above the ambient (manufacturing room) pressure (obligatory measure).

Transformer after overhauling has been operating without further failure for 15 years.

The question arises whether investor of continuous casting processing line should had got experts’ opinion on line design before it was erected. Was failure (and resultant high repair costs) necessary to order such opinions?

Analysis of transformer failure leads to general conclusion, that in case of serious economic investments proper verification of designs is a must. Experts verifying the designs should analyse in detail both planned operation of devices and their behaviour in case of all possible failures and hazards.

Paper has been elaborated within the framework of research project of Narodowe Centrum Nauki, project number 6025/B/T02/2011/40.

REFERENCES

[1] Gutten M., Kucera S., Šebök M., Analiza niezawodności transformatorów mocy z uwzględnieniem przetężeń i prądów zwarciowych, Przegląd Elektrotechniczny, 7 (2009)
[2] Horiszny J., Numeryczne obliczenia prądu włączania transformatora energetycznego, Przegląd Elektrotechniczny, 10 (2004)
[3] Kuśmierek Z., Współczynnik obciążenia transformatora zasilającego odbiorniki nieliniowe i jego pomiar, Przegląd Elektrotechniczny, 6 (2004)
[4] Ramowa Instrukcja Eksploatacji Transformatorów, Energopomiar – Elektryka, Gliwice 2001, ISBN 83 916040-0-4
[5] Васютинсқий С. Б., Вопросы теории и расчета трнсформаторов, Издательство „Энергия”, 1970
[6] Zakrzewski K., Modelowanie pól elektromagnetycznych w projektowaniu transformatorów, Przegląd Elektrotechniczny, 3 (2002)

Autors: prof. dr hab. inż. Tadeusz Glinka, Politechnika Śląska, Zakład Maszyn Elektrycznych i Inżynierii Elektrycznej w Transporcie, ul. Akademicka 10, 44-100 Gliwice, Branżowy Ośrodek Badawczo Rozwojowy Maszyn Elektrycznych KOMEL, ul. Roździeńskiego 188 40-203 Katowice E-mail: Tadeusz.Glinka@polsl.pl; dr n. med. Marek Glinka, Branżowy Ośrodek Badawczo Rozwojowy Maszyn Elektrycznych KOMEL, ul. Roździeńskiego 188, 40-203 Katowice, E-mail: mag@iq.pl

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review), ISSN 0033-2097, R. 88 NR 7a/2012

Transmission 101: The Fundamentals of High Voltage Transmission

Published by Adriann (Andee) McCoy, Vice President, Western Region, Smart Wires
Email: Andee@smartwires.com
Date: February 16, 2017

Presented by WIRES – a national coalition of entities dedicated to investment in a strong, well-planned and environmentally beneficial electricity high voltage transmission system in the US.

Effect of Synchronous Closing Control on Capacitor Energizing Transients

Published by Electrotek Concepts, Inc., PQSoft Case Study: Effect of Synchronous Closing Control on Capacitor Energizing Transients, Document ID: PQS0903, Date: October 15, 2009.

Abstract: The application of utility capacitor banks has long been accepted as a necessary step in the efficient design of utility power systems. In addition, capacitor switching is generally considered a normal operation for a utility system and the transients associated with these operations are generally not a problem for utility equipment. These low frequency transients, however, can cause problems for low voltage power electronic-based loads.

Adjustable-speed drives are susceptible to dc link overvoltage trips caused by utility capacitor switching. In general, an increase in input inductance (choke or isolation transformer) will reduce the possibility of nuisance tripping. However, if the customer has power factor correction capacitors on the same bus, it may be necessary to take additional remedial actions. This case study investigates the potential for voltage magnification and nuisance tripping during utility capacitor bank switching on a 24kV distribution system.

INTRODUCTION AND MODEL DEVELOPMENT

Transient overvoltages and nuisance tripping of a customer’s adjustable-speed drive during utility capacitor bank switching was studied for the system shown in Figure 1. The case involved determining overvoltage transients during uncontrolled capacitor bank switching as well as an evaluation of the effectiveness of synchronous closing control. The accuracy of the system model was verified using three-phase and single-line-to-ground fault currents and other steady-state quantities, such as capacitor bank rated current and voltage rise.

Figure 1 – Oneline Diagram for the Synchronous Closing Evaluation Case Study

A typical 10 hp customer adjustable-speed drive was included in the simulation model to determine the potential for nuisance tripping of the drive when a 1.8 MVAr, 25.56kV capacitor bank is switched at either the substation bus or at a location that is 2/3 of the feeder length. The energizing frequency for the 1.8 MVAr, 25.56kV distribution capacitor bank with a source strength of 68 MVA may be approximated using the following expression:

The steady-state voltage rise for this case may be approximated using the following expression:

A maximum voltage rise design limit of 3% would mean that the largest capacitor bank that can be switched at the substation for the studied circuit would be approximately 2 MVAr. Installation of a larger substation capacitor bank, such as 6 MVAr, would result in an excessive steady-state voltage rise (8.8%) and would likely require a circuit reconfiguration.

SIMULATION RESULTS

The effectiveness of synchronous closing control on the capacitor bank switch was evaluated in a series of cases that varied the timing error from an ideal voltage zero closing. Synchronous closing is independent contact closing of each phase near a voltage zero. Previous analysis has indicated that a closing consistency of ±1.0msec provides overvoltage control comparable to properly rated pre-insertion resistors. The success of a synchronous closing scheme is often determined by the ability to repeat the process under various (system and climate) conditions.

Simulation results are summarized in Table 1. The maximum transient overvoltage (refer to Figure 2) at the 25.56kV bus when energizing the 1.8 MVAr capacitor bank at the substation bus was 1.26 per-unit. Typical overvoltage magnitude levels range from 1.1 to 1.5 per-unit for smaller substation and feeder capacitor banks. The maximum transient overvoltage (refer to Figure 3) at the customer’s 480V bus was 1.09 per-unit. The resulting dc voltage on the 10 hp adjustable-speed drive in the customer facility was 665 volts (refer to Figure 4) which is lower than the assumed trip level of 780 volts, so it is assumed that the drive will not trip for this case.

Table 1 – Summary of Simulation Results for Synchronous Closing Evaluation

Figure 2 – Substation Bus Voltage during Capacitor Bank Energization

Figure 3 – Customer’s 480 Volt Bus Voltage during Capacitor Bank Energization

Figure 4 – ASD dc Link Voltage during Capacitor Bank Energization

Figure 5 shows the resulting 25.56kV bus voltage for the worst-case synchronous closing control case with a +1.0msec error. The maximum transient overvoltage is reduced from 1.26 per-unit to 1.03 per-unit. The customer’s 480 volt bus voltage is reduced from 1.09 per-unit to 1.01 per-unit and the dc voltage on the 10 hp adjustable-speed drive is reduced from 665 volts to 632 volts. The maximum transient overvoltage (refer to Figure 6) at the 25.56kV feeder location when energizing the 1.8 MVAr capacitor bank at 2/3 of the feeder length was 1.32 per-unit. The maximum transient overvoltage at the customer’s 480V bus was 1.18 per-unit. The resulting dc voltage on the 10 hp adjustable-speed drive in the customer facility was 699 volts, which is lower than the assumed trip level of 780 volts, so it is assumed that the drive will not trip for this case.

Figure 5 – Substation Bus Voltage with Synchronous Closing Control

Figure 6 – Feeder Voltage during Capacitor Bank Energization

Figure 7 shows the resulting 25.56kV feeder voltage for the worst-case synchronous closing control case with a +1.0msec error. The maximum transient overvoltage is reduced from 1.32 per-unit to 1.05 per-unit. The customer’s 480 volt bus voltage is reduced from 1.18 per-unit to 1.03 per-unit and the dc voltage on the 10 hp adjustable-speed drive is reduced from 699 volts to 661 volts.

Figure 7 – Feeder Voltage with Synchronous Closing Control

SUMMARY

Observations and conclusions for this case study include:

1.The devices and equipment being applied on the power system are more sensitive to power quality variations than equipment applied in the past. New equipment includes microprocessor-based controls and power-electronic devices that are sensitive to many types of disturbances. Controls can be affected, resulting in nuisance tripping or misoperation as part of an important process, or actual device failure can occur.

2.Capacitor bank switch selection and configuration will generally depend on switch capabilities (e.g., short circuit interrupting and capacitance switching ratings), mitigation device selection (e.g., pre-insertion vs. synchronous closing), site considerations, and an economic evaluation.

3.Transient overvoltages at the substation bus and feeder capacitor bank location when energizing the 1.8 MVAr capacitor bank were 1.26 per-unit and 1.32 per-unit respectively. These values are well below arrester protective levels for the simulated system and the simulated adjustable-speed drive did not trip for both cases without and with synchronous closing control.

4.Transient overvoltages associated with energization of the 25.56kV capacitor bank can be reduced with the application of synchronous closing control. The resulting overvoltages at the substation bus and feeder capacitor bank location were 1.03 per-unit and 1.05 per-unit respectively. In addition, the resulting overvoltages at customer’s 480 volt bus were also reduced, thereby significantly reducing the probability of localized customer problems due to sensitive equipment or low voltage power factor correction.

5.For the studied system, it is unlikely that the energization of a 1.8 MVAr capacitor bank at either the substation bus or feeder location will create transient overvoltages severe enough to cause problems for customer systems.

REFERENCES

G. Hensley, T. Singh, M. Samotyj, M. McGranaghan, and T. Grebe, Impact of Utility Switched Capacitors on Customer Systems Part II – Adjustable Speed Drive Concerns, IEEE Transactions PWRD, pp. 1623-1628, October, 1991.

G. Hensley, T. Singh, M. Samotyj, M. McGranaghan, and R. Zavadil, Impact of Utility Switched Capacitors on Customer Systems – Magnification at Low Voltage Capacitors, IEEE Transactions PWRD, pp. 862-868, April, 1992.

Electrotek Concepts, Inc., Evaluation of Distribution Capacitor Switching Concerns, Final Report, EPRI TR-107332, October 1997.

RELATED STANDARDS
IEEE Std. 1036-1992

GLOSSARY AND ACRONYMS
ASD: Adjustable-Speed Drive
PWM: Pulse Width Modulation
MOV: Metal Oxide Varistor
TVSS: Transient Voltage Surge Suppress

PQ Monitoring in Selected Networks of Czech Republic

Published by Petr KREJCI¹, Pavel SANTARIUS¹, Radovan HAJOVSKY¹, Richard VELICKA¹, Radim CUMPELIK²
VSB – Technical University of Ostrava, Czech Republic (1), CEZ, a.s., Czech Republic (2)

Abstract. In the paper, the results of the complex monitoring of selected PQ parameters during 12 years will be summarized together with the comparison of the changes of parameters after three years on all voltage levels (HV, MV and LV) in the power company CEZ in the North Moravia Region. In addition the results of annual continual monitoring for one selected locality on MV level will be presented in the paper.

Streszczenie. W artykule przedstawiono wyniki kompleksowej, trwającej 12 lat, obserwacji wybranych parametrów jakości energii elektrycznej oraz porównanie zmian podstawowych parametrów po 3 latach w sieciach o różnych poziomach napięć (WN, SN i nn) w przedsiębiorstwie energetycznym CEZ w rejonie Północnych Moraw (Monitorowane jakości energii w wybranych sieciach w Republice Czeskiej).

Keywords: Power quality, harmonics, flicker, unbalance.
Słowa kluczowe: Jakość energii, harmoniczne, fluktuacja napięcia, asymetria.

Introduction

The electrical power quality is assessed by the CSN EN 50 160 standard via 13 parameters of voltage. Extensive use of appliances with non-linear characteristics in LV distribution networks (appliances such as TVs, computers, copy machines, compact lights, etc.) is substantially deteriorating to quality parameters of electrical energy supplied.

In the former regional power company SME, a.s. (currently member of the CEZ group) in the Czech republic, there was, in 1997, a complex monitoring of selected parameters of voltage quality initiated for distribution networks of this company. Step by step, individual supply
nods 110 kV for all 6 supply areas of the company were measured. The whole cycle is rendered in 3-year cycles, so, as of 2010, the fifth measurement cycle is being rendered (with 1 year time-out in 2009). So, that is how, step by step, information on changes in periods of three years is being measured.

The method of power quality evaluation

In the power company CEZ (in the North Moravia Fig. 1) the monitoring of a number of selected parameters of the quality of electrical energy (harmonics, flicker, unbalance) is being done in cooperation with research laboratories of the Department of Measurement and Control and Department of Electrical Power Engineering, Faculty of Electrical Engineering and Computer Science, VSB – Technical University of Ostrava.

Fig. 1. The North Moravia Region, the Czech Republic

Monitoring of the power quality was gradually done in individual parts of the company. The measuring was done in a complex way within the HV, MV and LV distribution. The program of complex quality of electrical energy evaluation was done in 59 LV distribution transformer station. The composition of consumption in the LV network was similar in all measured localizations – i.e. a mix of family houses and blocks of flats and small services.

In accordance with the Standard CSN EN 50 160, the measuring and evaluation of the power quality of single points was done in one week intervals, while the parameters of quality were evaluated for 10 minute intervals in the course of measuring. The measurement is separated to 6 stages. As individual parts of the company have 8-10 feeding nodes 110 kV, the monitoring was organized in half-year cycles, thus the whole program lasted for 3 years.

In single feeder points they evaluate measured data in all phases and on all voltage levels:

Selected voltage harmonics (3., 5., 7., 9., 11.)
Flicker
Unbalance

The trends of changes of the selected parameters

As it was stated, the monitoring of the quality parameters was started in 1997 in all feeding points and was done during three years. In 2002 the second cycle of monitoring was completed in the same sites, therefore it is possible to evaluate the trends of change during three years. In 2005 the third cycle and in 2008 the fourth cycle of monitoring was completed and in 2010 the fifth cycle of monitoring was started after 1 year time-out in 2009.

In the Table 1 the changes of the selected quality parameters are summarized (selected harmonics, flicker and unbalance) during the first 3 years in the LV, MV and HV network. In the Table 2 and Table 3 the changes of the selected quality parameters are summarized during the second and the last 3 years. Ref. [1]

Table 1. Trends of changes of the selected quality parameters between 1^st and 2^nd cycle (in years 1997-2002)

Table 2. Trends of changes of the selected quality parameters between 2^nd and 3^rd cycle (in years 2000-2005)

Table 3. Trends of changes of the selected quality parameters between 3^rd and 4^th cycle (in years 2003-2008)

Evaluation of the trends of development of the selected quality parameters

As for harmonics, the results are relatively positive, the values of individual harmonic components are significantly below the values of compatible levels, changes after 3 years are minimal. As for unbalance, the changes are also quite small.

As for flicker, in years 1997-2002 the situation was worse, the increase of P_st and P_lt parameters was relatively low in relation to the level 1,0 (10-16%), but in relation to the
real values the increase was significantly higher (around 40%). But in years 2000 – 2005 there was stabilization or even decrease of flicker parameters.

The fourth cycle of measurement indicates rather stagnation of quality parameters. On the Figure 2 and on the Figure 3 there are shown 95% values of 5^th harmonic and flicker of 4 cycles of measurements in the LV distribution and values of 5^th harmonic and flicker in LV, MV and HV networks in the fifth cycle of monitoring. Ref. [2]

Fig.2. 5^th harmonic and flicker (P_lt) in some LV networks

Fig.3. 5^th harmonic and flicker (P_lt) in some LV, MV and HV networks in the fifth cycle of monitoring

Quality parameters monitoring at all times

As of 2001, there are analyzers QWave (manufactured by LEM) fitted to distribution points of 110 kV so as it is possible to register as much information on individual parameters of voltage quality and events in the distribution system, as possible. QWave Power measures, simultaneously, all voltage quality parameters and compares it with the limit values according to the CSN EN50160 standard, and furthermore, it also renders the current analysis. QWave Light is a simplified version, evaluating only current for its all guaranteed and indicative parameters.

The rules for operation of distribution networks (DN) contain Annex 3 (Quality of electrical power in the distribution system, manners of determination and evaluation). Based on these rules, there must be quality analyzer of the electrical power supply fitted at all times, as of January 1, 2006, for all HV supply terminals, and as of January 1, 2007, for all supplies from DN 110 kV. The data acquired by these analyzers are being continuously processed and archived. Ref. [2]

On the Figure 4 you can see the illustration of the continuously monitoring power quality parameters at the selected place OS-8 MV distribution network. On the diagram there are also placed the results acquired by the cyclic monitoring at the same place as it was described in the previous part of the contribution. For example, you can see that the values of flicker acquired by the cyclic monitoring makes approximately one quarter of the maximal value acquired by the yearly monitoring.

Fig.4. Flicker (P_lt) in MV network OS-8

Use of intelligent electrometers for monitoring of quality parameters

Characteristic parameters of voltage within low and high voltage networks are introduced in the standard ČSN EN 50160. The revised normative ČSN EN 50160 further defines parameters for very-high voltage networks.

Current intelligent electrometers usually provide data that is not in compliance with the normative mentioned above, but they afford relevant data for energy companies usable in operation.

As for usage in operation of distribution, the most crucial issues are long-term monitoring of voltage deviations and their evaluation in compliance with standard ČSN EN 50160. Further important values are overvoltage, falls and short-time blackouts typically with 1s sample period (thus quite not in accordance with ČSN EN 50160). Yet this data can give a power company relevant information, because events longer than 1 second still report about the conditions of distribution network and during the changes (usually rising) they indicate the error states. Unfortunately, these data are recorded as events, but the number or logged events are limited and set low.

Harmonics and THD, even evaluated until low frequencies only (till 10^th or 25^th harmonic multiple), can provide relevant information. For example, when the third harmonic element rises, it can indicate the problem of power transformer. A significant rise of any harmonic or
THD indicates the problem with resonances in distribution network.

Conclusions

In the paper above there are summarized the results of a long-term monitoring of the selected power quality parameters of the distribution networks together with the evaluation of the trends of change in the three years periods and results of continual monitoring PQ in selected MV distribution network.

The biggest changes were registered for flicker, in years 1997-2002 the situation was worse, the increase of P_st and P_lt parameters was relatively low in relation to the level 1,0 (10-16%), but in relation to the real values the increase was significantly higher (around 40%). But in years 2000 – 2005 there was stabilization or even decrease of flicker parameters.

The results from continuously monitoring of power quality parameters manifest that the measured values can differ during the year and therefore the continuously monitoring is well-founded.

Current intelligent electrometers usually provide data that is not in compliance with the normative mentioned above, but they afford relevant data for energy companies usable in operation.

Acknowledgment

This contribution was supported by the Czech Science Foundation (No. GA ČR 102/09/1842).

REFERENCES

[1] Santarius P., Krejci P., Spacil D., Vasenka P. Power Quality Problems in Regional Distribution Networks in the Czech Republic. Conference “EPQU 2007”, Barcelona, Spain
[2] Santarius P., Krejci P., Chmelikova Z., Ciganek J. Long-term Monitoring of Power Quality Parameters in Regional Distribution Networks in the Czech Republic. Conference “ICHQP 2008”, Wollongong, Australia

Authors:
Doc. Ing. Petr Krejci, Ph.D., petr.krejci@vsb.cz
Prof. Ing. Pavel Santarius, CSc., pavel.santarius@vsb.cz
Ing. Radovan Hajovsky, Ph.D., radovan.hajovsky@vsb.cz
Ing. Richard Velicka, Ph.D., richard.velicka@vsb.cz
Ing. Radim Cumpelik, radim.cumpelik@cez.cz
VSB – Technical University of Ostrava
17.listopadu 15, 708 33 Ostrava – Poruba, Czech Republic

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review), ISSN 0033-2097, R. 88 NR 7b/2012

Distribution System Transient Measurement Data Evaluation

Published by Electrotek Concepts, Inc., PQSoft Case Study: Distribution System Transient Measurement Data Evaluation, Document ID: PQS1012, Date: October 15, 2010.

Abstract: This case study presents a utility distribution system transient measurement data analysis. The distribution system included a number of feeders that supplied a mix of residential, commercial, and industrial customers. The causes of the transients measured during the monitoring period included capacitor bank switching, transformer energizing, single-phase faults, recloser operations, switch failures, and current-limiting fuse operations.

INTRODUCTION

A utility distribution system transient measurement data analysis case study was completed for the system shown in Figure 1. The 12.47 kV utility substation included a 30 MVA, 69 kV/12.47 kV step-down transformer and a number of distribution feeders that supplied a mix of residential, commercial, and industrial customers. There was a 6,000 kVAr, 12.5 kV capacitor bank at the substation bus that was energized using a synchronous closing control switch. In addition, each of the distribution feeders had a number of fixed or switched capacitor banks being used for power factor correction and voltage control.

The monitoring period was for one year and utilized power quality instruments that sampled voltages at 256 points-per-cycle and currents at 128 point-per-cycle. The sampling rate allowed characterization of low-to-medium frequency oscillatory transients. The measurement analysis was completed using the PQView® program. The causes of the transients measured during the monitoring period included capacitor bank switching, transformer energizing, single-phase faults, switch failure, recloser operations, and current-limiting fuse operations.

Figure 1 – Illustration of Oneline Diagram for Transient Measurement Data Evaluation

MEASUREMENT RESULTS

Figure 2 shows the measured voltage (per-unit) and current (A) waveforms during uncontrolled energization of the pole-mounted 600 kVAr capacitor bank on feeder #1. The measurement site was PQ2. The capacitor bank was switched on-and-off each day using time clock controls in an attempt to maintain a relatively constant voltage profile. The peak magnitude of the measured transient voltage was 1.09 per-unit and the principal frequency for the capacitor energizing waveform was approximately 650 Hz. The capacitor bank was energized using three single-phase mechanical oil switches with a pole span of approximately 3-5 cycles.

Typical voltage magnitude levels for switching distribution capacitor banks range from 1.3 to 1.5 per-unit and typical transient frequencies generally fall in the range from 300 to 1000 Hz. Power quality problems related to utility capacitor bank switching include customer equipment damage or failure, nuisance tripping of adjustable-speed drives or other process equipment, transient voltage surge suppressor failure, and computer network problems.

Figure 2 – Illustration of Feeder Capacitor Bank Energizing

Figure 3 shows the measured current waveform during back-to-back capacitor bank switching on feeder 2. Energizing a shunt capacitor bank with an adjacent capacitor bank already in service is known as back-to-back switching. High magnitude and frequency currents will flow between the capacitor banks when the second capacitor bank is energized. The measurement site was PQ3. The waveform shows the current that flows between the two 1,800 kVAr capacitor banks when the second capacitor bank is energized with the first capacitor bank already in service. The magnitude of the peak current was 600 A and the principal frequency was about 2.0 kHz.

The high-frequency inrush current may exceed the transient frequency momentary capability of the switching device (e.g., ANSI Std. C37.06-2000) as well as the I²t withstand of the capacitor fuses. It may also cause false operation of protective relays and excessive voltages for current transformers (CTs) in the neutral or phase of grounded-wye capacitor banks.

Figure 3 – Illustration of Back-to-Back Capacitor Bank Energizing

Figure 4 shows the measured 12.47 kV distribution feeder current waveform before-and-after energization of the pole-mounted 900 kVAr capacitor bank on feeder #3. The capacitor bank was switched on-and-off each day at the same time using a time clock control. The measurement site was PQ4.

The peak transient current for the capacitor bank energization portion of the event was 460 A. Insertion of the 900 kVAr capacitor bank creates a harmonic resonance that results in higher levels of current distortion. The steady-state total harmonic current distortion (I_THD) after energization of the capacitor bank was 13.26%.

Utilities switch capacitor banks in-and-out of service routinely to provide voltage support and to improve power factor. One potential disadvantage of capacitor bank switching is the effect that such an operation can have on the topology of the system. Switching capacitor banks into mostly inductive circuits can tune the natural frequency of the circuit closer to harmonic frequencies that might be prevalent on the system. Obviously, this can be a significant problem, possibly resulting in severe voltage and current distortion, increased losses, and overheating of system equipment.

Figure 4 – Illustration of Capacitor Bank Energizing and Harmonic Resonance

Figure 5 shows the measured voltage (per-unit) waveforms during energization of the substation 6,000 kVAr capacitor bank on feeder #1. The capacitor bank was switched using synchronous closing control. The measurement site was PQ1. The magnitude of the transient voltage at the substation bus was 1.06 per-unit.

Synchronous closing is independent contact closing of each phase near a voltage zero. To accomplish closing at or near a voltage zero (avoiding high prestrike voltages); it is necessary to apply a switching device that maintains a dielectric strength sufficient to withstand system voltages until its contacts touch. Although this level of precision is difficult to achieve, closing consistency of ±0.5 milliseconds should be possible. Previous research has indicated that a closing consistency of ±1.0 millisecond provides overvoltage control comparable to properly rated pre-insertion resistors. The typical transient overvoltage range for synchronous closing control would be between 1.05 and 1.20 per-unit depending on the capacitor bank rating and a number of other system parameters.

The success of a synchronous closing scheme is often determined by the ability to repeat the process under various (e.g., system and climate) conditions. Adaptive, microprocessor-based control schemes that have the ability to learn from previous events address this concern. The primary benefits of this capability are the control’s ability to compensate for environmental factors and the increased reliability (less maintenance) that can be achieved. Grounded capacitor banks are controlled by closing the three phases at three successive phase-to-ground voltage zeros (60° separation). Ungrounded banks are controlled by closing the first two phases at a phase-to-phase voltage zero and then delaying the third phase 90 degrees (phase-to-ground voltage zero).

Figure 5 – Illustration of Capacitor Bank Energizing with Synchronous Closing

Figure 6 shows the measured voltage (per-unit) and current (A) waveforms during a ferroresonance event on feeder #4. The measurement site was PQ5. The magnitude of the ferroresonant voltage at the monitoring location was 1.42 per-unit. The cause of the ferroresonance event was an unbalanced operation caused by a single-phase fuse operation on a customer step-down transformer.

Ferroresonance is a term generally applied to a wide variety of interactions between capacitors and iron-core inductors that result in unusual voltages and/or currents. In linear circuits, resonance occurs when the capacitive reactance equals the inductive reactance at the frequency at which the circuit is excited. Iron-core inductors have a nonlinear characteristic and therefore a range of inductance values. This relationship may lead to a number of operating conditions where the inductive reactance does not equal the capacitive reactance, but very high and damaging overvoltages occur.

If high voltages accompany the ferroresonance, there could be electrical damage to both the primary and secondary circuits. Surge arresters commonly fail during this condition. Arrester failures are related to the heating of the arrester block, and at times, the failures can be catastrophic, with parts being expelled from the arrester housing. In a typical power system, ferroresonance occurs when a transformer becomes isolated on a cable section in such a manner that the cable capacitance appears to be in series with the magnetizing characteristic of the transformer. An unbalanced switching operation is required to initiate the condition. Ferroresonance cannot always be entirely avoided. However, steps can be taken to reduce the probability of occurrence.

Figure 6 – Illustration of Distribution Feeder Ferroresonance

Figure 7 shows the measured current (A) waveform during a transformer energizing event on feeder #4. The measurement site was PQ5. The peak magnitude of the primary inrush current at the monitoring location was 46 A and the duration of the event was approximately 10 cycles. The cause of the transformer inrush was a recloser operation during circuit restoration.

Energizing saturable devices (devices with magnetic cores), such as power transformers, results in inrush currents that are rich in harmonic components. The inrush current interacts with the system impedance vs. frequency characteristics to create a voltage waveform that can have significant harmonic components for the duration that the inrush current is present. Transformer inrush current typically decays over a period on the order of one second.

This phenomenon combines concerns for harmonic current distortion and transient voltages. The harmonics of concern are low order (dominated by the 2^nd through the 5^th harmonics). If the circuit has a high impedance resonance near one of these frequencies, a dynamic overvoltage condition results that can cause failure of arresters and problems with sensitive equipment.

This problem is typically limited to cases of energizing large transformers with large power factor correction capacitor banks (e.g., arc furnace installations or other large industrial facilities). The solution to problems with dynamic overvoltages is to make sure that the conditions causing the system resonance are not present when the transformer is energized. This could mean making sure a capacitor bank is out of service whenever a large transformer is energized.

Figure 7 – Illustration of Transformer Inrush during Circuit Restoration

Figure 8 shows the measured voltage (per-unit) waveform during the operation of a current-limiting fuse (type 25K CL) on feeder #4. The measurement site was PQ5. The maximum peak arc voltage for the event was approximately 140% (1.40 per-unit). The fault was cleared by the fuse in approximately ½ cycle.

Current-limiting fuses are often used in electrical equipment where the fault current is very high and an internal fault could result in a catastrophic failure. There are various designs, but the basic configuration is that of a thin ribbon element or wire wound around a form and encased in a sealed insulating tube filled with a special sand. The tube is constructed of stout material such as a fiberglass-epoxy resin composite to withstand the pressures during the interruption process without rupturing. The element melts in many places simultaneously and, with the aid of the melting sand, very quickly builds up a voltage drop that opposes the flow of current. The current is forced to zero in about ¼ cycle.

The main purpose of current-limiting fuse is to prevent damage due to excessive fault current. They have the beneficial side effect with respect to power quality that the voltage sag resulting from the fault is very brief. The voltage sag is so short that not many industrial processes will be adversely affected. Therefore, one proposed practice is to install current-limiting fuses on each lateral branch in the high fault current region near the substation to reduce the number of sags that affect industrial processes.

Figure 8 – Illustration of a Current Limiting Fuse Operation

Figure 9 shows the measured current (A) waveform during an arcing fault on feeder #1. The
measurement site was PQ4. The fault occurred during a thunderstorm and it was cleared in
approximately 4 cycles by a recloser on an adjacent feeder.

Arcing faults are quite common on distribution and transmission feeders. These types of faults are usually caused by lightning strikes to the circuit, tree limbs contacting the circuit, or animals contacting the circuit. Arcing faults often contain a significant third harmonic component. Consequently, the arcing voltage waveform often has a “flat-top” appearance, resembling a square-wave. The arcing current typically exhibits a continuous ringing. This characteristic can be attributed to the ringing between the system inductance and capacitance as the voltage changes suddenly as occurs with the step change of a square-wave.

With respect to arcing faults, thunderstorms subject distribution systems to double jeopardy. Not only does the lightning associated with the storm create the potential for flashovers, but the wind associated with the storm increases the chance of tree limb contact. An example of an arcing fault voltage is shown in Figure 10, which shows a measured voltage waveform during an arcing fault on a feeder #3. The fault occurred during a storm that was caused by a tree limb being blown into one phase of the distribution line.

Figure 9 – Illustration of a Current Waveform during an Arcing Fault Event

Figure 10 – Illustration of a Voltage Waveform during an Arcing Fault Event

Figure 11 shows the measured current (A) waveform during a capacitor switch failure on feeder #1. The measurement site was PQ2. The maximum transient current magnitude for the event was approximately 790 A. Many similar transient waveforms were recorded at the monitoring site during a one-week period. These events showed that the switch performance had continue to deteriorate.

As the capacitor switch began to fail, abnormal events including arcing and pre-striking occurred. These were the initial warning sign that a more serious failure was about to occur. Closer examination of the waveform indicated that the pole of the switch did not properly close, possibly bouncing. This abnormal event resulted in two distinct energizations. First, the pole bounces, making a connection temporarily, but it does not latch. This results in an arc that extinguishes as the contacts pull apart. As the switch continues to close, however, the pole finally latches, and the capacitor bank was energized.

Figure 11 – Illustration of a Current Waveform during a Capacitor Bank Switch Failure

SUMMARY

This case study summarized a distribution system transient measurement data analysis. The causes of the transients measured during the monitoring period included capacitor bank switching, transformer energizing, single-phase faults, recloser operations, switch failures, and current-limiting fuse operations.

REFERENCES

IEEE Recommended Practice for Monitoring Electric Power Quality,” IEEE Std. 1159-1995, IEEE,
October 1995, ISBN: 1-55937-549-3.
R.C. Dugan, M.F. McGranaghan, S. Santoso, H.W. Beaty, “Electrical Power Systems Quality,”
McGraw-Hill Companies, Inc., November 2002, ISBN 0-07-138622-X.

RELATED STANDARDS
IEEE Std. 1159, IEEE Std. 1100, IEEE Std. 446, ANSI Std. C84.1

Smart Meter and Cost Experiment

Published by Mehmet Sait CENGİZ¹
University of Yüzüncü Yıl (1)

Abstract. System that all stakeholders compound the activities (production, transmission, distribution, sale, consumption) to product and to consume quality, constant, reliable and economic electric energy is called Smart Grid (SG) in electric. SG, which its most important component smart meter (Smart Metering-SM), are advanced energy metering devices that give more information than traditional energy meters and that measure the consumption of electric energy. It includes integration techniques and various software applications depending on characteristics of SM electric network. In this study, by giving information about infrastructure of automatic meter, AMI installation levels and its integration to system are explained. An experiment proving the advantages that SM provides to system and consumer has been made and its results have been interpreted.

Streszczenie. Układy typu smart meter dają znacznie więcej informacji zużytej energii niż klasyczne liczniki. W artykule przedstawiono infrastrukturę i metody dołączenie do sieci. (Eksperyment dotyczący zastosowania I kosztu licznmika typu smart meter)

Keywords: smart grids, power grids, smart meters, distribution grids.
Słowa kluczowe: smart grid, smart meter.

Introduction

SM solution to meet the needs of metering can be remotely set for electric distribution companies; it provides a clear and advanced metering infrastructure (AMI) [1]. AMI solution is an infrastructure that allows electricity distribution companies to display subscribers who sell energy and consume energy, to manage electricity consumptions, to measure the power quality, to increase reliability of distribution and that provides to meet completely the requests of operations, engineers, subscriber services and market regulatory supreme board in the field [2].

Even though automatic meter reading and its infrastructure (AMI) is one of the key works of Smart Network, SG is beyond the meter reading. Distribution Management, System Optimization and Energy Management System that has spread to the entire network should stand back of AMI so that electricity distribution system can efficiently support its own established system. AMI (Automatic Meter Infrastructure) solution allows electricity distribution company to realize a single SG application as modular and to make march forward and develop this system in time on its own request and then spread to entire network; or, by building a complete SG system, distributor company can begin to benefit from all of the advantages of smart network at once, without having any integration problem [3].

While AMI (Advanced Metering Infrastructure) is defined as transmission and management of energy over a network infrastructure in line with demand or in a regular way, bidirectional data exchange comes into question in advanced infrastructures [4]. In this way, not only transfer of data of energy consumption but also transmission of the other data that could be transmitted by center, such as cutoff and opening at the same time or reflecting the product selection to clients, is provided. SMs are the most important component of AMI. Installation of AMI should not be considered only as assembling or installation of meters. In advance of this, sufficient time and resource should be planned for planning, feasibility and design study of business processes [5]. In addition, throughout the entire process, institutional change and settlement should be managed in such a way as to meet the needs of distribution companies. In the projects to establish AMI, all of the following stages or a part of them, according to the needs of clients, should be made real [6].

AMI installation stages;

Planning of AMI infrastructure
Creation of Architecture
Revision of Business Processes
Creation of Functional Requirements
Evaluation of Suppliers and Solutions
Installation of Infrastructure and Making it Real

Distribution companies, primarily, should plan the factors related to infrastructure. Afterwards, beginning with installation of meters in the field, determination of functional and technical architecture consisting of communication infrastructure and central data acquisition systems and integration points should be done. After putting AMI systems into practice, it is required that to redesign the business processes that will change under distribution and retail sale operations and to demonstrate new business processes. To achieve the required results, it is important to redesign the business process by taking possible changes into account. In this direction, after analyzing current business processes and purposes, redesign should be performed. In next phases, installation of meters and dissemination studies should be practiced.

Concept And Effects Of Smart Grid

Through AMI, not only consumption information but also information about failure and cut-off are transmitted to centre. In this way, network operator can carry out wealth management (failure repair-maintenance system) in a more efficient way [9]. SM system that is a part of AMI consists of five main factors:

1.Home Network: Through the system that is also called Home Area Network (HAN), commands came from AMI provide to manage the other devices at home. For example; in a space where electricity price is cheaper, electric vehicle can be remotely charged (from work place, vacation, etc.) and home can be heated. More importantly, as a result of remote commands production based on solar and wind energy can be followed. In this way, unlicensed production can be practiced more efficiently. In timeframes when electric prices are favorable, energy can be stored through remote commands by HAN application.

2.Meter owner endpoints: SMs take part in connection points of production station, free consumers and the other consumers. In particular, practicing bidirectional data transmission in consumer side is one of the most important factors of smart network.

3.Network: Data obtained by meters are transmitted over communication infrastructures such as GSM/GPRS, BPL (Broadband Over Power Line) or PLC (Power Line Communication) and then reached to data base in centre of distribution network.

4.Data center: MDM (Meter Data Management) system, where the data transmitted from field are cleaned, incomplete data is completed and takes its final form by treated, is in here. Meter Data Management System (MDM) informs us about fault-maintenance management, customer services-invoicing, prediction-load follow-up, market management, distribution operations and investment planning.

5.Back office and management: All data obtained by smart meters are evaluated in the background and required decisions are made by achieving analytic reports. In this direction:

Distribution Network Management: Making decisions of new investment, fault repair-maintenance follow-up and planning,
Meter reading, opening and cut-off: Carrying out retail sale services in a cost-efficient, central and consistent way.
Invoicing and customer services: Remote invoicing, leak check or determination of decline at consumer consumption, checking the data of meter before invoice issue are practiced.

The most important acquisition of SG investments is reducing the cost and increasing the efficiency [10,11]. In the U.S.A and many European countries, SG and SM investments are preferred [12]. In our country, however, SG investments are called under the title of automatic meter reading system (OSOS) and becomes a current issue to transmission and distribution networks. OSOS is composed of remote reading of data automatically and data verification after transferring to a central system, completing the incomplete data and transmission to relative stakeholders in a proper format [13]. Through increased competition in the sale of energy, distribution companies that want to offer better service for their clients (product development, less cut-off), to reduce leaks and to move one step forward in wealth management should cross into SG investments without losing time.

Historically saving descriptive identity data related to SM, data of assessment and invoicing ( total active and reactive energy indices, periodical data of the highest demand, load profile curves ) and meter status information ( calibration time, low battery warning, opening warn of connector and case cover) in data centers will provide great advantages to
have chances to report in different dimensions, to follow the measurement points timely and accurately and also to reduce loss leakage in large measure by feeding invoicing systems with consistent data [14,15]. Advantages are provided by SMs to system can be queued as :

• It provides steady and future guaranteed communication. It provides all of the required band width that will meet SG needs ( including the electric selling operation from hibrid automobiles to electricity distribution company) of AMI and sections.

• It provides inclusive network and operation management. To be able to display SG infrastructure provides a complete cycle management involving trouble shooting and maintenance management [16].

• Automatic data acquisition makes gain storage and analyzing ability. It manages meter data acquisition by providing standard interfaces to Meter Data Management of electricity distribution companies [16].

• It provides efficient communication solution in terms of cost. This solution communicate with many technologies including that broadband over power lines (BPL) by each Smart Transducer. Due to electricity distribution company communicate by using its own network with BPL technology, cost unit is lower [16].

Smart Meter Application Experiment

Remote meter reading systems that is one of the initial steps of SG system are found in many countries including Turkey. Many international companies that want to have a voice in future and/or infrastructure of these systems, installed web portals and act in common with electricity distributors. In this context Google, by PowerMeter system, offers an opportunity you to see your instant consumption and invoicing through a “Google Attachment” in a live presentation when you surf in the internet. Besides, savings of many consumers practiced by using this system has been indicated on website. Sample screen display indicating the detailed load graphic by Google Powermeter program is illustrated on Figure 1 [17,18].

Fig. 1. Google Powermeter attachment screen display and detailed load graphic

In the same way, Microsoft has also begun to provide service its users by Hohm. In the study made by system of Microsoft, system offers a survey about a home and devices in that home, after this an average consumption appears. Microsoft system has the possibility of recording manually invoices of consumers apart from remote reading system by SM. Distribution of load consumption of a sample home in Microsoft Hohm, is illustrated on Figure 2 [19].

Fig. 2. Screen display of Microsoft Hohm and distribution of a sample home consumption

Fig. 3. Daily load usage from a site that uses Tweet-a-Watt

In the study that is made with reference to the idea that there will be a quite market for these systems in Turkey, through systems that could be found easily on internet, electricity consumption is read over wattmeter and then can be published on websites like Tweeter [20]. On “Tweet-a-watt” site that is one of the systems in question, consumption graphics are published with a system that costs 90 $ in average. Consumption graphic that shows daily load usage for any client, is illustrated on Figure 3 [21].

For this system, in Turkey, experimental status of such a system is obtained by wattmeter and electronically tuned sockets. While there is no “smart network” study in our country yet, there is a study about the advantages in case of a smart network and dimensions of demand side attendance. For this, by measuring the devices in a home through Wattmeter, instant load and hourly load values obtained. At this stage, in the experiment for demonstration purposes, data recorded transiently as if there is a remote reading system with smart meter. Information about instant loads, devices of the house, option of remote tuning are in Table 1.

Table 1. Instant loads, devices in the sample house and options of remote tuning.

In here, while it depends on choice of consumer which tools will be turned off automatically, in a real system it is possible to control these sockets through electronic control devices can be installed into the sockets in the house. Average load consumption curve of a house in one day, has been obtained and is illustrated on Figure 4.

Fig. 4. Average load consumption curve of a house in one day

To see and demonstrate advantages of smart meters in consideration of these load consumptions, a comparison based upon one time and multi-time tariffs has been made. It is seen that using multi-time tariff over this system and consumption increases the cost to be paid. Due to client is at his home around 17:00 o’clock and maintains all the main activities until 24:00. A large part of hours when consumption is around the top level corresponds to the interval that energy price is the highest. Therefore, this client consumes the electricity in peak time, in other words, in the most expensive moments. To prevent this situation, smart meters can be used.

Table 3, for April of 2013, illustrating one-time and multi-time tariffs of public company TEDAŞ that is the biggest distribution company of our country, is in below. In table 2 also costs which occur on the basis of daily, monthly and annual as a result of being priced of the same consumption by one time and multi time tariff.

Table 2. 7 January 2013 dated electricity sale prices of TEDAŞ per tax-free KWh [22].

If loads that can be adjusted in consumption profile are transferred through programmable sockets to time zones in which consumption is more economic, in other words, in case of using SM, A severe load decline is provided by providing automatically to start dishwashers and washing machines up after 22:00. Besides, when electronic sockets are programmed in order to laptops would make battery consumption in puant consumption time and would charge in the end of puant, ultimate consumption, in a system that SMs check in, is like in Table 3.

Table 3. After shifting consumption times of devices can be tuned by SM.

The same amount of consumption before SM using, while monthly electric bill is 31,8 $ in one-time, annual consumption is 42,2816 $ in three-time consumption. In such a consumption, it is paid 32.95 % more. However, it becomes advantageous by including SMs in the system, is paid 21,8469 $ instead 31,8 $. Therefore, without making any limitation with the same consumption, it is paid 31.3 % less due to programming feature of smart meter. Consequently, while it is paid annual 381,6 $ in invoicing by one-time meter that is considered as the minimum cost, it is paid 262,1636 $ by multi-time meter in the system with smart meter. In other words, every consumer can economize 9.9544 $ per month and 119,4563 $ per year in total. SM usage has two-way advantage. These are economizing 9.9544 $ per month and moreover making network control easy by contributing to decline of puant load in the hours when power demand is huge in terms of network.

Conclusions

As a result of privatization of distribution companies, requirement of legal disintegration, increasing competition and technologic requirements , SM/SG necessity comes into prominence in distribution sector of Turkey. In this direction, distribution companies and the other stakeholders should be ready for change and transformation. SMs provide the following benefits to electricity distribution companies:

• Operational Cost Reduction: It allows to collect meter data of distribution companies and to reduce meter reading expenses based on work force. through this, distribution companies will have chance to reduce transport costs that occur against to subscriber telephones or fault reports by remote monitoring the subscriber interruptions.

• Revenue Protection: By providing real-time and clearer invoice details, it removes need of monthly invoice prediction. This model supports, on behalf of revenue protection, both prepayment systems and systems that cuts remotely electricity of subscribers who don’t pay their invoices. In conclusion, it supports application of “Energy Robbery Determination” to reduce deficiencies of distribution companies.

• Demand Management: It collects data from network and subscribers, one by one, for advanced level of pricing policies of electricity distribution companies such as pricing according to time when subscribers use electricity within day and/or pricing according to critical peak rates. In addition, it allows subscribers of distribution companies to see their own consumption amounts and to change their life styles in order to reduce or change load rates.

• Home Area Network – HAN: AMI solution provides remote control for distribution companies. By means of this, additional services such as remote opening-closing of meter, Internet connection service, security and automation of home, could be done.

As it can be seen through experiment that is carried out, SM usage has benefit in two way. These are reducing of price that will be paid monthly by consumer and moreover making network control easy by contributing to decline of puant load in the hours when power demand is huge in terms of network.

REFERENCES

[1] Har t DG. Using AMI to realize the smart grid. In: Proc. IEEE Power and Energy Society General Meeting – Conversion and Delivery of Electrical Energy. 2008. p. 1–2.
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[16] Cengiz M.S., Rustemli S., Almali M. N. The Advantages of the Applicability of New Generation Sectionalisers and Reclosers Over the Pole “Przeglad Elektrotechniczny” (Electrical Review), R. 89 NR 2a/2013, pp:155-159. 2013.
[17] Google.org PowerMeter, http://www.google.org/powermeter
[18] Images of Google PowerMeter, No Business Model, Katie Fehrenbacher, 2 Haziran 2009, http://earth2tech.com/2013/01/05/images-of-googlepowermter
[19] Microsoft Hohm, 3 Ocak 2013, http://www.microsofthohm.com/Recommendations/
[20] Tweet-a-Watt kits now available, Adafruit Industries Blog, http://www.adafruit.com/blog/2013/01/02/tweet-awatt-kits-nowavailable
[21] Tweet-a-Watt, http://wattcher.appspot.com/history?user=adawatt@gmail.com
[22] TEDAS Elektrik satıs tarifeleri, http://www.tedas.gov.tr/tarifeler_xls/2013_trf/tarife.xls

Authors: Lecturer Mehmet Sait Cengiz, Department of Baskale Technical Vocational School, Yuzuncu Yil University, Van/Turkey, E-mail: msaitcengiz@gmail.com

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 89 NR 11/2013