thesis of dan suriyamangkol

8/7/2019 THESIS OF DAN SURIYAMANGKOL

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NON-TECHNICAL LOSSES IN

ELECTRICAL POWER SYSTEMS

A Thesis Presented to

The Faculty of the

Fritz J. and Dolores H. Russ

College of Engineering and Technology

Ohio University

In Partial Fulfillment

of the Requirements for the Degree

Master of Science

by

Dan Suriyamongkol

November 2002


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THIS THESIS ENTITLED

NON-TECHNICAL LOSSES IN

ELECTRICAL POWER SYSTEMS

by Dan Suriyamongkol

has been approved

for the Department of Electrical Engineering and Computer Sciences

and the College of Engineering and Technology

___________________________________________________

Brian Manhire, Professor

___________________________________________________

Richard Dennis Irwin, Dean

College of Engineering and Technology


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ACKNOWLEDGMENTS

First, I would like to thank Dr. Brian Manhire, my advisor, for all of his support,

insight and invaluable help during the preparation and information collection for this

thesis.

There is a large amount of information in this thesis that would not be available

without the help from the following persons. Mrs. Prachumporn Bunnak, Acting Director

of the Department of Power Economics, the Provincial Energy Authority of Thailand

(PEA), authorized unprecedented access to PEA information and operations. Mr. Barvorn

Phattanak, Assistant Manager of the Power Economics Division, who coordinated my

information gathering effort at PEA excellently. Mr. Youngyuth Sonjaiyuth, Head of the

Three-Phase Meter Installation and Inspection Group at PEA, who provided me with

great insight into electricity theft and a priceless view from the field.

At American Electric Power, I was fortunate to receive insights from William A.

Randle, John H. Provanzana, and Jack E. Carr. The World Bank proved an invaluable

resource through the report [2] by the Energy Sector Unit, sent to me by Alfred B.

Gustone.


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TABLE OF CONTENTS

ACKNOWLEDGMENTS........iii

LIST OF FIGURES......vi

LIST OF TABLES...........vii

CHAPTER 1 INTRODUCTION 1

1.1 Losses in Electrical Power Systems1.2 Loss Analysis in Power Systems1.3 Electricity Theft1.4 Past Documentation of Non-Technical Losses1.5 Conclusions and Future Work

CHAPTER 2 ANALYSIS OF LOSSES IN

ELECTRICAL POWER SYSTEMS 6

2.1 Technical Losses in Power Systems 62.2 Technical Losses: Measurement and Practical Cases 112.3 Losses With Non-technical Losses Present 19

CHAPTER 3 NON-TECHNICAL LOSSES:

ELECTRICITY THEFT 27

3.1 Brief Background on Electricity Theft 27

3.2 Methods of Electricity Theft 30

CHAPTER 4 PAST DOCUMENTATION OF

NON-TECHNICAL LOSSES 35

4.1 Provincial Energy Authority of Thailand 364.2 American Electric Power 464.3 World Bank Eastern Europe and Former Soviet Union 47


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CHAPTER 5 CONCLUSION AND SUGGESTIONSFOR FURTHER WORK 55

BIBLIOGRAPHY 58

APPENDIX A

Principles of Power Systems Analysis:

Basic Load Flow and Loss Calculations 59

APPENDIX B

Two-Bus Load Flow Analysis Programs in MATLAB 68

APPENDIX C

Transmission Line Specifications for PEA 79

ABSTRACT


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LIST OF FIGURES

2.1 Single-Line Diagram of a Simple Two-Bus Power System 9

2.2 Three-Bus Power System 11

2.3 Single-Line Diagram of a Two-Bus, Two-Load Power Systemwith Known Load and Known Transmission Line Data(Each bus can be the Slack Bus) 12

2.4 Load Demands for the Two-Bus Power System from Figure 2.3 12

2.5 Profile of Load Power Factors for Test Power System in Figure 2.3 14

2.6 Energy Losses Calculated Using the Two-Bus Test System withBus 1 as the Slack Bus and then with Bus 2 as the Slack Bus 16

2.7 Energy Losses in the Two-Bus Test System and a Comparisonbetween the Average Losses Computed Using the DetailedLoad Schedule and Losses Computed from Average Power 18

2.8 Demand and Power Factor Changes at Load 2 Caused by Non-Technical Losses

2.9 Effects of NTL on Transmission Line Losses 24

3.1 Basic Components of a Watt-hour Meter.

3.2 Early recording meters: Sangamo Gutmann type A (c. 1899-1901)watt-hour meter, left, and Westinghouse ampere-hourmeter by Shallenberger

3.3 Modern recording meters: Schlumberger J5S (1984),and General Electric I-70S (1968)

3.4 Three-phase Watt-hour Meter Connection

3.5 Parts of a Single-phase Watt-hour Meter Where Tampering Often Occur


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4.1 Breakdown of PEA Consumers Sorted by Consumption, October 2000 41

4.2 Breakdown of PEA Consumers Sorted by Numbers ofIndividual Consumers, October 2000 41

A.1 A General Connection Situation at an Arbitrary Bus(denoted Bus A, where G denotes a generator unit). 66

B.1 Single-line diagram of a two-bus, two-load power system with

known load and known transmission line data.

Each bus can be the slack bus. 73

B.2 Information Flow Through the MATLAB Load FlowAnalysis Program. 75


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LIST OF TABLES

2.1 An Example of a Loads Consumption Information 20

2.2 Summary of Effects of Adding NTL to the Two-Bus Test System 26

4.1 PEA Policies for Billing CustomersWho Perpetrated Electricity Theft 43

4.2 Meter Inspection Protocols and Schedules for PEA 44

4.3 PEA Guidelines and Schedules for ReportingMeter Inspection Results 45

4.4 Meter Tampering Found Among High Voltage Consumersin Thailand Between October 2000 and June 2001. 46

4.5 Meter Tampering Found Among Low Voltage Consumersin Thailand Between October 2000 and June 2001. 47

4.6 Extent of the Electric Utility Non-Payment Problemin Eastern Europe and Former Soviet Union Nations 52

4.7 Capacity Utilization in the Power Sector of FSU 53


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CHAPTER 1

INTRODUCTION

A news article estimated that electricity theft in the United States costs billions of

dollars a year1. Such estimates were the beginning of this research. Electricity theft is part

of a phenomenon known as non-technical losses (NTL) in electrical power systems.

This research aims to investigate the nature of non-technical losses in power systems,

their sources, the measurement of non-technical losses, some measures taken by selected

utilities to reduce them, and possibly their impact on the system.

In this introduction, a summary of the main parts of this thesis will be presented.

Chapter 2 deals with the simulation and calculation of losses in power systems and the

effects that NTL have on those losses. Various forms of NTL and the utilities measures

to counter them are presented and discussed in Chapter 4. Before that, special attention

will be given to the watt-hour meter and various ways to tamper with it in chapter 3. The

study of utilities handling and recording of NTL cases was made possible by the

cooperation provided by the Provincial Energy Authority of Thailand (PEA) for

information obtained in rural Thailand, while information on NTL and utilities reactions

in the United States was based on a series of e-mail correspondences with officials of

American Electric Power. Also, the World Bank provided some information on the

1 Bill Nesbit, "Thieves Lurk - The Sizable Problem of Electricity Theft", Electric World T&D,www.platts.com/engineers/issues/ElectricalWorld/0009/, September/October 2000


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effects of wide-scale occurrences of NTL in Eastern Europe and Former Soviet Union

(FSU) nations.

1.1 LOSSES IN ELECTRICAL POWER SYSTEMS

In order to study non-technical losses, which constitute a portion of the total

losses in electrical power systems, the logical first step is to understand the complete

picture of power systems losses. Power system losses can be divided into two categories:

technical losses and non-technical losses.

Technical losses are naturally occurring losses (caused by actions internal to the

power system) and consist mainly of power dissipation in electrical system components

such as transmission lines, power transformers, measurement systems, etc. Technical

losses are possible to compute and control, provided the power system in question

consists of known quantities of loads. In this thesis, it will be argued that the distortion of

load quantities caused by NTL will distort the computations for technical losses caused

by existing loads, thereby rendering any results ineffectual.

Non-technical losses (NTL), on the other hand, are caused by actions external to

the power system, or are caused by loads and conditions that the technical losses

computation failed to take into account. NTL are more difficult to measure because these


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losses are often unaccounted for by the system operators and thus have no recorded

information. The most probable causes of NTL are:

Electricity theft

Non-payment by customers

Errors in technical losses computation

Errors in accounting and record keeping that distort technical information

The most prominent forms of NTL are electricity theft and non-payment, which

are thought to account for most, if not all, of NTL in power systems. However, the other

two sources of NTL listed above are not analyzed thoroughly in this thesis, so their

contribution to NTL is unknown.

The methods used to perpetrate electricity theft are discussed in Chapter 3. A few

examples of documented cases of customer non-payment and the measures used to

handle them are discussed in Chapter 4.

Other forms of NTL may exist, such as unanticipated increases in system losses

due to equipment deterioration over time, but are usually ignored in any calculations.

System miscalculation on the part of the utilities, due to accounting errors, poor record

keeping, or other information errors may also contribute to NTL. These losses are

discussed in this thesis due to insufficient background information.


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1.2 LOSS ANALYSIS IN POWER SYSTEMS

Technical losses in power systems are caused by the physical properties of the

components of power systems. The most obvious examples are the power dissipated in

transmission lines and transformers due to their internal electrical resistance. Technical

losses are easy to simulate and calculate; computation tools for calculating power flow,

losses, and equipment status in power systems have been developed for some time.

Improvements in information technology and data acquisition have also made the

calculations and verifications easier.

In this thesis, a simple power flow calculation is used to study relevant aspects of

technical losses in a very simplified power system. The results of those simulations are

presented and discussed in chapter 2. The technical principles of power flow calculations

and loss analyses are briefly discussed in Appendix A, but more useful treatments of the

subject can be found in [1].

Also discussed in this thesis is the required information for successfully analyzing

power systems using load flow analysis, the practical availability of the said information,

and the effects of adding known non-technical losses to the simulated power system

analysis. Results from simulations in Chapter 2 suggest that the use of traditional

technical losses calculation tools would not be useful in NTL calculations. This is due to


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the lack of information on NTL loads attached to power systems, as well as the lack of

information on legitimately recognized loads themselves.

1.3 ELECTRICITY THEFT

All of the utilities and sources contacted by this author agreed that the dominant

component of NTL is electricity theft and non-payment [2], [5], [6], [7]. Electricity theft

is defined as a conscience attempt by a person to reduce or eliminate the amount of

money he or she will owe the utility for electric energy. This could range from tampering

with the meter to create false consumption information used in billings to making

unauthorized connections to the power grid. Common methods of electricity theft are

discussed in Chapter 3.

1.4 PAST DOCUMENTATION OF NON-TECHNICAL LOSSES

Non-payment, as the name implies, refers to cases where customers refuse or are

unable to pay for their electricity. Non-payment cases, magnitudes and some solutions are

presented in Chapter 4. All of the non-payment information provided here are courtesy of

the World Bank Energy Sector Unit [2]. Some solution approaches reported by various

organizations that contributed to the World Bank report [2] are also included.


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Electricity theft is a problem that has long been known to utilities. Chapter 4

provides summaries of policies implemented by two utility companies: the Provincial

Energy Authority of Thailand, and American Electric Power, based in the United States

of America. The summaries include the impact of electricity theft on each company, their

procedures for dealing with electricity theft, and results of revenue recovery efforts by

PEA and AEP.

1.5 CONCLUSIONS AND FUTURE WORK

The conclusions from Chapters 2, 3, and 4 are given in Chapter 5 and can be

generally stated as follows:

NTL are nearly impossible to measure using traditional power system analysis

tools. This is due to the lack of information on both NTL and the legitimate loads

in the system, which translates to insufficient inputs for any meaningful loss

calculations.

Electricity theft, a common form of NTL, involves tampering with meters to

distort the billing information or direct connections to the power system. Each

type of theft is well documented by utilities [2], [5], [6], [7].

Utilities contacted for this thesis all agreed that electricity theft is the most

prominent form of NTL, while customer non-payment can also lead to significant

problems in areas that fail to handle the situation properly [2], [5], [6], [7].


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All of the personnel interviewed for this thesis (listed in the Acknowledgement

section) also stated that due to reasons given in Chapter 2, there have been no

attempts to calculate for NTL using current measurement techniques.

Possible future work on this topic is also discussed in Chapter 5. The possible

future topics include: use of newer technologies to increase measurement capabilities,

possible cost-benefit analyses on the current measures favored by the utilities compared

with other possible measures, and more detailed examinations of the NTL causes listed

above that are not discussed here.


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CHAPTER 2

ANALYSIS OF LOSSES IN POWER SYSTEMS

Losses incurred in electrical power systems have two components: technical

losses and non-technical losses. Technical losses mean losses that happen because of the

physical nature of the equipment and infrastructure of the power systems, i.e., I2R loss

or copper loss in the conductor cables, transformers, switches, and generators. Loads

are not included in the losses because they are actually intended to receive as much

energy as possible. Technical losses can be calculated based on the natural properties of

components in the power system: resistance, reactance, capacitance, voltage, current, and

power are routinely calculated by utility companies as a way to specify what components

will be added to the systems. Though the data and tools needed for calculating losses in

power systems are available, current techniques have certain drawbacks regarding such

calculations. This issue will be addressed in the section Technical Losses in Power

Systems below. The effects of adding non-technical losses to a power system will be

examined in the section Losses with Non-technical Losses Present later in this chapter.

2.1 TECHNICAL LOSSES IN POWER SYSTEMS

Technical losses in power systems mean power losses incurred by physical

properties of components in the power systems infrastructure. A common example of


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such losses is the power loss caused by resistance of transmission lines. The average

power loss in a transmission line can be expressed as

Ploss = Psource Pload (2.1)

where Psource means the average power that the source is injecting into the transmission

line andPloadis the power consumed by the load at the other end of the transmission line.

This is a simple enough calculation, except that power and current are both time-

dependent functions and that energy not power is the quantity that gets translated into

money. Energy is power accumulated over time, or

=b

a

lossloss dttPW )( (2.2)

with a and b as the starting and ending points of the time interval being evaluated,

respectively. As a result, we need a fairly accurate description ofPloss as a function of

time to make a reliable prediction of energy loss (Wloss). And power, in a single-phase

case, with sinusoidal current and voltage can be represented by

P1- = IVcos (2.3)

with P, V and I being the average power, rms voltage and rms current of the element in

question, respectively. The term cos is the power factor of the element in question,

while is the phase difference between the voltage and the current waveforms.

From the above it can be summarized that the information needed to calculate the

average power loss sampled at an instant of time in a transmission line or an arbitrary


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element in a power system has to be one of the following sets (all variables are single-

phase, rms values and average power):

1.) Voltage across the element, resistance, orP=V2/R

2.) Current and resistance, orP=I2R

3.) Voltage, current and phase difference between the two, orP=IVcos

These sets of data and choices of calculations are the options that an engineer will

have for computing power losses in a load-flow analysis2. But in order to gain V or I,

both rms values, the voltage must be known at two ends of the element that is evaluated,

at all times or as averages. This means the terminals that feed consumer loads must be

appropriately monitored at all times using some of the more sophisticated meters that

could store and compute average and instantaneous values that the load-flow analyst is

interested in.

The information about the power sources and loads listed above are needed to

determine expected losses in the power system using load-flow analysis software. The

actual losses are the difference between outgoing energy recorded by the source (e.g., at a

substation) and energy consumed by the consumers, which is shown on the bills. The

discrepancy between expected losses and actual losses would yield the extent of non-

technical losses in that system.

2 Load-Flow Analysis is a computational tool for calculating power flow in electrical power systems (moredetails in [1]).


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Figure 2.1 Single-Line Diagram of a Simple Two-Bus Power System.

Figure 2.1 above shows a simple power system with two buses (nodes), one a

generator, and the other a load. For the simulations undertaken for this research, the

voltage, current, power, and power factor of the generator have known values at the same

time intervals, and, consequently, the current going through the transmission line. The

loss in the transmission line is easily computed using the current and transmission line

resistance values. Information of the loads power and power factor are unknown, but at

this point the information at the generator is sufficient to determine whats happening to

the transmission line using simple calculations:

I* =load

load

V

S (2.4a)

and Ploss = (V)I* (2.4b)

With Sload, Vload, Ploss, I, andR are the load apparent power, load voltage, power

loss in the transmission line, current in the transmission line, and transmission line

resistance, respectively (all values are complex values), whileI* is the complex conjugate

of the current. The same relationships hold when analyzing these quantities as phasors or

rms values. Any major calculations become unnecessary whenIcan be measured directly

LoadG

Bus 1 Bus 2I

Transmission Line


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and the transmission line properties are known, which is never true for practical power

systems. Companies that generate and distribute electricity usually measure currents that

enter and leave their facilities in order to measure the energy that is bought or sold. For

areas outside the companies facilities, i.e., residential or business consumer areas, only

peak power and accumulated energy are usually measured.

However, the low voltage transmission systems (below 24,000 volts or 24 KV)

are not as thoroughly measured because of the costs of the added metering. This is the

reason power flow solutions are used to estimate the state the various points in the

system. Power flow analysis is generally used for specifying equipment ratings after

estimating the worst-case loading scenarios.

Finding the current in the one bus going out of a metered generator is simple, but

in reality there are often many interconnected buses and many more elements in the

system. Just expanding the two-bus characterization by one step would yield a three-bus

system shown in Figure 2.2 below. Using Kirchhoffs Current Law to solve for the

currents at the bus where the two transmission lines meet,

I1 = I2 + I3 (2.5)

As in the two-bus case, the current in Transmission Line 1 is measured. To

determine the current in Transmission Line 2 (I2), however, the current going into Load 1

must to be known. This means there has to be a meter at Load 1 with the same

capabilities as the meter at the generator in order to computeI2 at desired times.


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Figure 2.2 Three-Bus Power System

More detailed analysis of technical losses and their calculations in practical power

systems can be found in Appendix A and [1].

2.2 TECHNICAL LOSSES: MEASUREMENT AND PRACTICAL CASES

A more common case worth performing calculations for is a two-bus subsystem

with loads at both busses and one bus selected as a slack bus3

with constant voltage.

This configuration is chosen for simplicity. The bus with constant voltage is presumed, as

is the case with most systems, to be the one connected to the larger system that has a

relatively infinite supply of electrical energy with constant source characteristics. The

diagram for a two-bus system is shown in Figure 2.3 below where the electrical

3 The term slack bus refers to a reference bus (or node) in the system with known voltage and phase anglenecessary for analysis of the system. The slack bus is often treated as a source that can inject infinite(relatively very large) power and energy into the system and maintain constant voltage and phase anglethroughout the analysis. In analyzing small power systems connected to larger systems, the slack bus wouldbe the point where the system is interconnected to the wider system that can inject large amount of powerand energy into the system of interest.

Bus 3

G

I1 I3

I2

Bus 1 Bus 2

Transmission Line 1

Transmission Line 2

Load 1

Load 2


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properties needed to complete a load-flow calculation for power loss in the transmission

line are provided below and in Appendix C. The load profiles for each of the two loads

are shown in Figure 2.4 below.

Figure 2.3 Single-Line Diagram of a Two-Bus, Two-Load Power System with KnownLoad and Known Transmission Line Data (Each bus can be the Slack Bus)

0

50

100

150

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300

350

400

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PowerDemand(KVA

)

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Power Demands For The Two-Bus Test Power System

Load 1 Demand, KVA Load 2 Demand,K VA

Figure 2.4 Load Demands for the Two-Bus Power System from Figure 2.3

From the system specifications discussed below, it can be seen that this test

system is a very simplified one numerically and conceptually. Each load has its own

profile, i.e., each load varies with time and has a different pattern over a period of 24

Bus 1 Bus 2

Load 1 Load 2Transmission Line


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hours. To make the test loads more realistic they are represented as two sets of power

demands with different operation schedules comparable to residential and industrial

areas. The grey profile that peaks during the daytime and drops off at night represents an

industrial load, while the black profile represents a residential load.

The load peaks are at 500 KVA for load 1 and 350 KVA for load 2, which are

reasonable levels for loads connected through 750 KVA-rated and 500 KVA-rated

transformers, respectively. The average load demands are 291.67 KVA and 153.96 KVA

for load 1 and load 2, respectively. Load power factors are shown in Figure 2.5 below,

with average values of 0.83 and 0.78 for load 1 and load 2, respectively. Transformers are

omitted from the simulation program for simplicitys sake. Transmission line resistance

and reactance values are taken from 22000-volt transmission line datasheets provided by

PEA (see Appendix C). The conductor size and line length were chosen arbitrarily from

the datasheet, with the maximum conductor size of 185 mm2 chosen to avoid overloading

the line. A line typical length of 2 kilometers (about 1.25 miles) was chosen arbitrarily.

Finally, the loads were assumed balanced between all three phases, to avoid

complex computing. This means that only the positive sequence impedance values need

be used in calculations and negative and zero sequences can be ignored.


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Load Power Factors

0

0.1

0.2

0.3

0.4

0.5

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1

0:00

2:00

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6:00

8:00

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16:00

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Time of day

PowerFactor

Load 1 Power Factor Load 2 Power Factor

Figure 2.5 Profile of Load Power Factors for Test Power Systemin Figure 2.3

Specifications of the two-bus test system (Source: see Appendix C)

Base Values4: 22000 Volts, 100 Ampere, 2.2 MVA, 220 Ohms

Transmission Line:

Resistance = 2 km * 0.175713 Ohms/conductor/km * 3 conductors

= 1.054278 Ohms = 0.004792 per unit (p.u.)

Reactance = 2 km * 0.334439 Ohms/cond./km * 3 cond.

= 2.006705 Ohms = 0.009121062 p.u.

4 The term Base Value is used in per-unit calculations; for more details, see [1].


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The test system has been used to be a source for a simple load-flow calculation

program written in MATLAB to determine the losses for the transmission line (see

Appendices A and B). The results were later compared to those obtained using the Power

Education Toolbox [10], and Power System Simulator [11]. The specifications

provided about the loads are the following: power demands of the loads at various times

of the day over 24 hours; power factor values over the same time period; the averages of

power demands and power factors. The incurred transmission losses are shown in Figure

2.6 below. The trends suggest that load number 1 is an office or workplace with a peak

demand of 400 kilowatts and the load level being high during office hours. Load number

2 is presumed to be a residential area with a peak demand of 241.5 kilowatts and load

levels that rise around time for breakfast and dinner times.

In the case where bus 1 is used as the slack bus, the average power loss in the

transmission line is around 74.53 watts, while the power loss calculated using the average

values of power and power factor is 51.69 watts.

As seen in Figures 2.4 and 2.5, the load profile changes according to the time of

the day and consumes a finite amount of energy. The load energy can also be represented

by a time invariant average demand value with the same amount of consumed energy

over the same amount of time. The point being made here is that since the utility bills

often only include energy, a number of vastly different chronological power profiles can

be introduced which end up consuming the same amount of energy.


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The MATLAB simulator was used to calculate the transmission losses for the

load demands and power factor for each hour, first using bus 1 as the slack bus, and then

with bus 2 as the slack bus. The results are shown in Figure 2.6 below. The losses based

on the average demand and power factor values were calculated only with bus 1 as the

slack bus, with results shown in Figure 2.7. The result is that the average of losses

calculated using the sum of data from individual times is notequal to the losses

calculated using the average values, as seen in Figure 2.7 below for the case where bus 1

is used as the slack bus. The reason for this inequality will be examined later in this

chapter.

Comparison of Losses Using Different Slack Buses

0

500

1000

1500

2000

2500

Time of day

Losses

(KWh)

Losses Using Bus 1 as Slack Losses Using Bus 2 as Slack

Figure 2.6 Energy Losses Calculated Using the Two-Bus Test System withBus 1 as the Slack Bus and then with Bus 2 as the Slack Bus

In the case where bus 1 is the slack bus, the total energy lost in the transmission

line each day is 6439.983 kilowatt-hours, while the energy computed using the average

power and power factor turns out to be 4466.707 kilowatt-hours. The difference is about


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1973.276 kilowatt-hours a day (30.64 % of actual loss) or, at February 2002 prices in

Athens, Ohio5, $98.68 a day.

Total Losses Calculated From Various Information

0

5000

10000

15000

20000

25000

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

No. of Days With Identical Load Power Profiles (Days)

Total Daily Losses Using Hourly Demand (Bus 1 Slack)

Total Losses Using Average Demand (Bus 1)

Losses Using Hourly Demand (Bus 2 Slack)

Losses Using Average Demand (Bus 2)

Figure 2.7 Energy Losses in the Two-Bus Test System and a Comparison between theAverage Losses Computed Using the Detailed Load Schedule and Losses Computed

from Average Power. (Note: data shown as straight line to illustrate the different levelswhen using different slack busses)

This example illustrates how determining losses in transmission lines relies on

availability of information. And the information on the loads can be obtained either by

the customer monitoring the load or the utility monitoring the junction where the load is

connected. Either way, there has to be significant investment in measurement hardware

because average values are shown to be inaccurate for calculating real losses. The

5 Energy rates are published by American Electric Power at www.aepcustomer.com/tariffs/default.htm


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average values of power factor and voltages used to compute the losses in equation 2.4a

and 2.4b, for example, are meaningless because power factor and voltages may not peak

at the same time.

The nature of most loads means that the current values must be taken at intervals

small enough to make an accurate representation of the actual load characteristics. This is

where the measurement of loss in transmission lines gets complicated. The meters

required for useful measurements of current or power factor are significantly more

expensive than the simpler kind that only records consumption over time. Meters that can

record a load power profile are used mainly at substations, power plants, and by large

consumers that manage their consumption. Most locations with these meters give

accurate descriptions of losses in high-voltage power lines where there is very little, if

any, electricity theft.

Transmission and distribution line sections that are most vulnerable to theft are

the medium- and low-voltage lines that connect to most of the consumers. These lines are

numerous and usually highly interconnected, which means that isolation of an area for

calculation is difficult. The two-bus calculations above are done with one of the buses

held constant, and there must always be a slack bus with constant known properties in

order to run load flow analyses. In medium- and low- voltage subsystems, however, the

bus voltages are often shifting along with consumer demand changes and even voltage

levels at the incoming feeders sometimes fluctuate.


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At this point, it is getting clear that making calculations for expected losses

accurately is nearly impossible in practice. This is because the data required at least in

Thailands case is very difficult to gather. Once again, refer to the list of possible ways

to calculate power above to see the data needed. The obstacle here is that meters installed

and used by Thailands utilities are all old models that only record peak power and

energy in kilowatt-hours for household loads. Even the industrial meters only record the

worst-case power factor, which has no bearing on an average much less record a profile

of power and power factor. Some meters record demands (power) at peak hours, which

again have no relationships with an average value or values that are usable in load flow

analyses.

The way to obtain a fairly accurate value of average load demand is to utilize the

information the utilities use to calculate the electric bills. The calculation requires energy

consumption accumulated up to the beginning of the time period (usually a month) and

the consumption accumulated at the end of the time period. The accumulated

consumption at the end of the period is subtracted by the accumulated consumption at the

beginning of the period. The result is the total consumption during the time period in

kilowatt-hours, and the portion of the bill for energy consumption is based on this

number.

The average demand for that same time period is the total energy consumption

divided by the length of the time period, in seconds. This information is always available


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for metered loads, because it is what the utilities revenues are based on. For example, a

load that has the consumption information listed in Table 2.1 would have the average

demand as calculated below.

Table 2.1 Example of Load Consumption Information

Date/Time (mm/dd/yy, hr:min:sec) Consumption, kilowatt-hours

Begin: 01/03/02 15:06:00 23,558,407

End: 02/01/02 13:55:30 23,634,462

Calculation results

Total time elapsed: 2,501,730 Seconds

Total energy consumed: 76,055 Kilowatt-hours

Average demand: 109,459 Watts

The average demand is not something difficult to find, as seen above, but the

problem for using this in load flow calculations is that the corresponding power factor

must be found. Power factor, as mentioned earlier, is not a quantity that is recorded by

most meters. The high-voltage or high-demand meters that record power factor exists

mainly in utilities installations or very large loads, while medium-sized loads often

record only the worst-case power factor for the purpose of billing, which is not useful

when it comes to finding the average power factor.


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2.3 LOSSES WITH NON-TECHNICAL LOSSES PRESENT

Non-technical losses are difficult to quantify. They refer to losses that occur

independently of technical losses in the power system. Two easy examples of sources of

such losses are component breakdowns that drastically increase losses before they are

replaced in time, and electricity theft. Losses incurred by equipment breakdown are quite

rare. These include losses from equipment struck by lightning, equipment damaged by

time, the elements and neglect. Most power companies do not allow equipment to

breakdown in such a way and virtually all companies maintain some form of maintenance

policies. Equipment failures due to natural abuses like snow and wind are also rare, for

equipment is selected and infrastructure designed with local weather and natural

phenomena considered.

Non-technical losses can also be viewed as undetected load; customers that the

utilities dont know exist. When an undetected load is attached to the system, the actual

losses increase while the losses expected by the utilities will remain the same. The

increased losses will show on the utilities accounts, and the costs will be passed along to

the customers as transmission and distribution charges. In a simulation discussed below,

an NTL load is added to the load at bus 2, the load that exhibits patterns similar to a

housing load, as implied by the hours that load activities increase and decrease. The

reason this load is chosen is that most NTL cases in reality are found in residential areas

or light industrial areas [2], [5], [6], [7].


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From the technical loss analysis above, the effects of an undetected load attached

to one of the buses in the two-bus test system can be measured by adding extra demand

values to one of the loads and evaluating the changed losses. The extra load may be

simulated in a simplistic way by adding a profile of demands to the bus 2 load in the form

of adding VA values to the original demand and reducing the total power factors by

subtracting a power factor contribution for each value of added load. The pf

contributions chosen here were negative because the NTL load is assumed to be

inductive, i.e., motors or light fixtures. The profile of the added NTL and the total load

and the pf contribution to the load pf at bus 2 are shown in Figure 2.8 below. The

simulation is run with bus 2 as the slack bus. The NTL pf contribution is negative at all

times because the NTL load is assumed to be inductive.

After the simulation was completed and evaluated, some notable results were

evident. First, the increase in load demand and the increase in transmission losses were

not at the same levels. This is caused by the power factor contribution of the NTL load.

Indeed, the losses increased at a greater rate than the loads. On average, the load VA

increased by about 12.67 KVA, or about 7.9 per cent, while the losses had an average

increase of 23.39 per cent. The average loss here is computed by averaging the overall

loss increase for each hour.

It can be seen from Figure 2.9 below that the increase in demand caused by NTL

would also increase transmission line loss disproportionately. Even though the increase in


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transmission loss places a greater burden on the transmission equipment, the greater

cause for concern would be the NTL load itself. During a 24-hour period, the increase in

transmission losses amounts to about 771 kilowatt-hours a day, or about $38.59. The

costs of the NTL itself during the same time period is much higher at 675,953 KW-h a

day, or $ 33,797 a day.

(a) NTL Contribution to Load 2 of the Test System

0

50000

100000

150000

200000

250000

300000

350000

400000

0:00

2:00

4:00

6:00

8:00

10:00

12:00

14:00

16:00

18:00

20:00

22:00

Time, Hrs.

Demand,

VA

Load 2 Demand, VA NTL Demand, VA

(b) Negative power factor Contributions by NTL

-0.02

-0.015

-0.01

-0.005

0

0:00 2:00 4:00 6:00 8:00 10:00 12:00 14:00 16:00 18:00 20:00 22:00

Time, Hrs.

Nega

tive

pf

Con

tributions

Figure 2.8 Demand and Power Factor Changes at Load 2 Caused by Non-TechnicalLosses


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(a) Effects of NTL on Loads and Losses

0

5

10

15

20

25

30

35

40

45

50

0:00

1:00

2:00

3:00

4:00

5:00

6:00

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8:00

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13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

Time, Hrs.

Increase,

%

Increase in Transmission Losses Due to NTL Increase in Load Due to NTL

(b) Effects of NTL on Transmission Line Losses

0

50

100

150

200

250

300

350

0:00

1:00

2:00

3:00

4:00

5:00

6:00

7:00

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19:00

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23:00

Time, Hrs.

Losses,

Watts

Losses without NTL Losses with NTL

Figure 2.9 Effects of NTL on Transmission Line Losses.


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The transmission line losses are very small compared to the loads themselves, but

the increased losses should not be ignored because they mean power dissipated in the

transmission lines as heat. When the lines get overheated, serious consequences can

follow, from loss of material strength to the weakening of insulation possibly dangerous

if the lines are in a crowded area.

The most noticeable effects of NTL, of course, are the monetary costs. In the

simulation results above, the load at bus 2 amounts to about $ 503,604 a day and the NTL

costs the utilities about $ 33,797 a day. The transmission costs due to the NTL, about $

38.59 a day, are just the transmission costs for the two kilometers of transmission lines

used in the simulation. In reality, the transmission costs would be similarly increased all

along the supply path back to the power plant, which could mean a very significant

increase depending on the distance. Table 2.2 below provides a summary of the results

obtained by the simulation of the two-bus system and the effects of NTL.

Note that once the NTL itself is taken into account, the discrepancy caused by

using average power to compute transmission losses becomes small, $4 out of nearly

$34,000. This is one of the reasons that the utility departments that work on electricity

theft interviewed for this research did not seem interested in using load-flow software.


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Table 2.2 Summary of Effects of Adding NTL to the Two-Bus Test SystemTotal daily losses Computed for each

hour in the load profileComputed usingaverage demands & pf

Transmission losses without NTL,KWH

6,439.98 4,466.70

Transmission losses with NTL,KWH

7,211.57 5,169.48

Load demand at bus 2 withoutNTL, KWH

10,061,280 10,061,280

Load demand at bus 2 with NTL,KWH

10,737,230 10,737,230

Total increased losses, KWH(increased load plus increasedtransmission loss)

676,721.59 676,652.78

Total increased losses, $ 33,836 33,832

The last issue to be addressed in this section is who pays for the NTL costs. The

transmission and distribution costs in the United States are calculated as part of the

customers bills, while in Thailand the customers are usually charged a single flat energy

rate that includes all services. The US utilities have to un-bundle the charges because

widespread deregulation in various states has made the generation and distribution

companies split into separate entities [12].

This means that in the US, the transmission and distribution losses that increased

due to NTL would be charged either to the existing customer whose power lines are

illegally tapped, or the utility, depending on the method of theft (see Chapter 3 for

details). Who pays for the NTL loads depends on how the NTL loads are connected to the

power system. If the NTL loads are connected to the systems transmission lines before

they reach the customers meters, the utilities will assume the costs of the NTL loads.

However, if the NTL loads are connected at a point beyond innocent customers meters,


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the customers will be stuck with the transmission costs and, more seriously, the increased

loads. In Chapter 3, there are lists of various types of electricity theft that include both

types of NTL described in the paragraph above.

In conclusion, the measurement of NTL and its effects on electrical power

systems as a whole using existing analytical tools would be possible only if information

about the NTL loads themselves is available to the analyst. The information would have

to include either the NTL loads power consumption profile comparable to the legitimate

loads being analyzed at the same time, as well as the NTL power factor, or power factor

contribution as in the case shown above. In interviews with experienced engineers,

technicians, and utilities officials mentioned in the acknowledgement, it is their opinion

that NTL cases cannot be directly measured because of the information gathering effort

required. After all, the people who make illegal connections to the power system are

unlikely to participate in any form of survey freely when their own illegal actions would

come to light.


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CHAPTER 3

ELECTRICITY THEFT:

A MAJOR COMPONENT OF NON-TECHNICAL LOSSES

3.1 BRIEF BACKGROUND ON ELECTRICITY THEFT

As shown in Chapter 2, non-technical losses (NTL) are difficult if not

impossible to detect using information that is typically collected by utility companies.

In some areas, the loads are not even metered or are metered communally [2], rendering

any loss calculations technical or not for that area useless. The approach used by both

utility companies contacted [2], [5], [6] involves primarily involves field staff monitoring

meters and access points in the system on a regular basis (see Chapter 4 for more details).

Sometimes this involves regular meter readers receiving special training for spotting

irregularities, and sometimes when high voltage and large consumption is involved it

involves meter technicians making dedicated meter and transformer inspection trips (see

Chapter 4).

The reason that meter inspection is the main method of NTL detection is because

the utilities consider electricity theft to be the major source of NTL and the majority of

electricity theft cases involves meter tampering or meter destruction [2], [5], [6]. The

term meter used in this and other chapters refers to the watt-hour recording meters used

in virtually every household to record and calculate electric bills by utility companies.


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The principles of operation for watt-hour meters essentially have not changed

since the 1880s and the 1890s, when the watt-hour meter was invented [3]. The basic

principle for a single-phase energy measurement meter, first commercially used in 1894,

is as follows. First, there are two coils that produce electromagnetic fluxes: a coil,

connected across the two leads, that produces a flux proportional to the voltage and a coil

connected in series with one of the leads that produces a flux proportional to the current.

The dot product of those two fluxes creates a force proportional to the load power. An

illustration of the basic components of the watt-hour meter is shown in Figure 3.1 below.

The development of these meters, technological improvements, and alternative designs,

which reflected the growing power industry in the late 19th

century, is chronicled in detail

in [3].

In early designs, such as the ones shown in Figure 3.2 below, the meters were not

enclosed and all the parts and the meter installation were easily accessible to anyone.

However, as early as 1899, the minutes of meter committees of the Association of Edison

Illuminating Companies [meter paper] showed that electricity theft was a concern early

on. In response to the committees recommendations, the following improvements

along with other efficiency and accuracy improvements were added [3]:

First, a dust- and insect-proof cover

Second, a cover and frame so shaped and retained together

as to render dishonest and curious tampering with the internal

mechanism as nearly impossible as may be.

Third, means for fully protecting from malicious tampering

the heads of all screws in the base which bind the damping

magnets, etc., in place without rendering them inaccessible to

those authorized to reach them.


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Figure 3.1 Basic Components of a Watt-hour Meter.Clockwise from top left: coil connections for voltage and current sensing elements, the

rotating disc that records consumption, and the basic construction.(Source: Bud Russell, http://www.themeterguy.com/Theory/watthour_meter.htm, 2002)

This suggests that the problem of electricity theft has obviously been around almost as

long as power systems have been around. Modern meters, such as those in Figures 3.3

below, are relatively well enclosed and have seals that would reveal tampering. However,

theft can and does occur. Most utilities train their staff to spot tampering, but sometimes

the access to the inner mechanisms can be achieved with a very small hole, possibly

drilled using small tools and done at less obvious parts of the enclosure [7].


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Figure 3.2 Early recording meters: Sangamo Gutmann type A (c. 1899-1901) watt-hourmeter, left, and Westinghouse ampere-hour meter by Shallenberger (c. 1888-1897), right

(Source: David Dahle, www.watthourmeter.com, 2002)

Figure 3.3 Modern recording meters: Schlumberger J5S (1984), and General Electric I-70S (1968) (Source: David Dahle, www.watthourmeter.com, 2002)


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3.2 METHODS OF ELECTRICITY THEFT

There are two main categories for methods of electricity theft: directly connecting

an unregistered load to a power line, and tampering with a registered loads meter in

order to reduce the size of the bill the utility charges that load. Once the meter seals are

broken, there are many things that can be done to the meter to slow or stop it. Below is a

list of various methods of electricity theft recorded by the Provincial Energy Authority of

Thailand (PEA) [6], [7].

High Voltage Meters (12kV or 24kV, 3-phase, 3 or 4-wire primary)

High voltage three-phase watt-hour meters are installed throughout the PEA

system to monitor loads that consume high volumes of energy requiring high voltage.

Three-phase watt-hour meters use the technique known as the two watt-hour meters

connection to measure consumption. Because the load is connected with high voltage and

consumes high current levels, the current and voltage sensing are achieved by using

current transformers (CT)6 and voltage taps, respectively. The schematic that illustrates

the connections is shown in Figure 3.4 below.

6 A current transformer is a device that outputs a current proportional to the load current being measured,enabling the meter to measure the load without subjecting it to large current and power levels.


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Figure 3.4 Three-phase Watt-hour Meter Connection.(Source: Bud Russell, http://www.themeterguy.com/Theory/watthour_meter.htm, 2002)

Tampering with terminal seals is by far the most common method of meter

violations, because the terminal seals are easy to reach, located immediately below the

meter itself. Once the terminals were broken, it is be simple to connect one of the control

wires or CT wires to ground, making it appear to the meter that at lease one phase does

not show voltage or current. The cases of seal tampering, both terminal and meter seals,

refer to cases where seals were broken but no visible tampering was done to the meters or

the terminals themselves.

Breaking control wires Control wires refer to the secondary wires of the current

transformer (CT). Meters for large loads measure high currents and must use CTs to step

the current level down to make it compatible with the components in the meter. Once the

CurrentTransformers(CT)

Voltage Taps

IncomingConnection

3-phaseLoad


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insulation of the control wire is broken, external taps could be connected to reduce the

current going into the meter, causing the meter to read less current than reality.

Tampering with meter seals is another common form of violation, tampering with

meter seals means the person now has access to the meter itself. There are many ways to

tamper with meters that will be discussed later.

Shorting control wires Like breaking control wires, this would divert the current

reading in the meter. In this case the current going to the meter would be zero. The effect

on the meter is immediate and obvious: with zero-current, the power and energy readings

become zero, or the accumulated consumption becomes stationary.

Breaking the voltage taps Voltage taps in the meter housing allows the meter to

read the voltage of the load. Once these are broken (or shorted to ground, or have another

line connected to it), the reading the meter gets is distorted from reality, reading a lower

voltage in cases of electricity theft. In the unlikely event that the person wants the meter

to read higher values, the voltage taps could be connected to a higher voltage level, and

result in higher consumption readings. Many meters would not work properly or would

be damaged by this type of action, because the internal equipment must operate within

rated conditions in order to function properly.


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Direct connections to the grid An obvious way to eliminate consumption records

is to bypass the meter altogether. The major obstacle to this is that most high voltage

loads are built and connected at the request of the customers, such as a new shopping

mall asking for 12-kV lines to run to the back of the property to keep the front clear.

Since the customers are the ones who ask for the connections, direct connections like this

would be fairly easy to discover. Also, not many electricians would like to subject

themselves to a hot high voltage line without the power company there to assist with

safety.

Tampering with the meter Once the meter seals are broken and theres easy access

to the meter inside the housing, and there are several things that can be done to slow or

stop the meter readings. A common way is to mechanically obstruct the spinning disc and

the axis that does the recording. Another popular action is to turn back the dials that bill

collectors eventually read. Obviously this wouldnt work for digital-display meters, but

all of the PEA-installed meters in Thailand are spinning disc type manufactured in the

1980s or before.

Switching CT wires This is a subtle and effective way to reduce electric bills.

Many models of three-phase meters use only two current transformers (CTs) to read

current data from phases A and B, and assume the load is balanced between all three

phases. In reality, large facilities like factories or offices have unbalanced loads.

Depending on the engineer who designed the load connections, this imbalance could vary


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between 10 and 20 percent of the most heavily loaded phase. C phase is almost always

the phase with the least load and lowest power factor, which is why CTs are connected to

the A and B phases. By switching the CTs or the wires from their secondary windings,

the meters current reading is altered. Switching A and B phases would result in a

reversal of phase difference seen by the meter, affecting the power factor reading, and

power/energy reading. If the CT from one of the phases is removed and placed on phase

C, the power reading is lowered.

Low Voltage Meters (220V single phase)

A low voltage watt-hour meter is based on the principles of operation discussed in

the beginning of the chapter. The parts of the meter where tampering often occur are

shown in Figure 3.5 below.

Figure 3.5 Parts of a Single-phase Watt-hour Meter Where Tampering Often Occur.(Source: Bud Russell, http://www.themeterguy.com/Theory/watthour_meter.htm, 2002)

CurrentSensingElement

VoltageSensingElement

DisruptingSpinning Disc

Tamperingwith theNeutral Line


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Direct connection to the power grid Since the meters and equipment in this

section are in the 220-volt system, where customers are mostly houses and small

businesses, a direct connection to the power grid is much easier than the high-voltage

system. Well, at least safer; a pair of rubber gloves could be all the necessary protection

and a ladder and knife all the necessary tools, as opposed to climbing up HV lines five

stories up on steel masts and being careful not to get tangled in other cables below or

inadvertent electrocution. This is by far the most common method here, used a lot by

street vendors and shantytowns. In fact, some of this writers temporary neighbors on a

construction site in Bangkok, Thailand do this.

Using alternate neutral lines The single-phase system often has only one wire

going into a house, the hot line. Neutral is usually grounded (electrically connected to

the earth) and is sometimes provided by the foundation of the house (or location, to be

more generic). So if a person could manage to use a small transformer and use that as the

neutral, the meter that uses the very same neutral source would read the incoming

voltage lower than it really is, resulting in a reduced unit count.

Phase-to-phase connection is similar to using an alternate neutral line, except that

the system voltage becomes the phase-to-phase voltage, at 240 or 380 volts, depending

on the location (240 volts for the United States).


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Meter tampering/breaking seal is basically the same thing that happens to the HV

meters, since PEA uses meters that are quite aged for the low-voltage consumers, too.

Other methods of electricity theft include: tapping off a nearby paying consumer,

damage done to meter enclosures, and using magnets to slow down the spinning discs in

the meter housing.

There are also many other methods for stealing electricity that have been

circulated on the Internet recently. Some of the suggested methods are not feasible, while

others may require too much effort or are outright dangerous [7]. This author has found

some Internet message boards full of possible methods to distort billing information at

the consumer end, such as using a Tron Box a circuit to change the phase of one of

the leads passing through the meter [7].

Methods suggested in chat rooms even include some highly far flung ideas, such

as placing enormous coils around high voltage power lines to act as transformers with

ridiculously large air gaps [4]. Interestingly, these message boards were also used by

some utilities to detect electricity theft perpetrators and track them to see if any of the

individuals fall within their areas of coverage, in effect, operating an online sting

operation7.

7 International Utilities Revenue Protection Association (IURPA), www.iurpa.org, 2002.


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CHAPTER 4

PAST DOCUMENTATION OF NON-TECHNICAL LOSSES

Cases of non-technical losses (NTL) are acknowledged and dealt with by all of

the local utilities officials and international institutions contacted for this research. These

include: Thailands Provincial Energy Authority and Metropolitan Energy Authority

(PEA and MEA, respectively); USAs American Electric Power (AEP); and the World

Bank.

Utility companies with transmission and distribution (T&D) operations that were

contacted by the author were all engaged in some form of NTL reduction policy. PEA has

a set of guidelines to prevent and respond to electricity theft that will be discussed in

further detail. AEP has a Revenue Protection department dedicated to recovering lost

revenues due to electricity theft. The World Bank is involved in infrastructure

development in many countries, which bring them in direct contact with utilities and NTL

in local service areas. A summary of the World Banks experience with NTL in Eastern

European and former Soviet Union countries in the 1990s will be provided. Finally, an

international organization, IURPA [7], focused on detecting, preventing, and reducing

NTL has been established with representatives from utilities around the world.


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4.1 PROVINCIAL ENERGY AUTHORITY OF THAILAND

The Provincial Energy Authority of Thailand (PEA) is the government-owned

utility company that provides electricity to consumers in every area of Thailand except

for Bangkok and its suburbs, which are serviced by the Metropolitan Energy Authority

(MEA). Virtually all of PEAs electricity is bought wholesale from the Energy

Generation Authority of Thailand (EGAT), another government-controlled entity. A very

small amount of electricity is sold to PEA and other consumers by local generators

located in a few industrial complexes; their effects on the PEA power system is negligible

because these local generators distribute power over very short power lines that seldom

extend beyond the industrial parks that they occupy [5], [6].

Since the companies that handle virtually all the electricity generation and

distribution in the country are government-owned, the electricity industry can be easily

described as fully regulated. Electricity rates for various regions are determined by a

board of appointed directors for each of the distribution utilities (MEA and PEA). Their

prices, in turn, are almost exclusively influenced by the supply rates governed by EGAT.

With Thailand being a net importer of crude oil the fuel of choice for starting most

generators, as well as the primary fuel for some generation the prices of crude oil often

plays a big part in EGATs pricing policies. In contrast, the coal and natural gas mines

are operated by other government entities, and hydroelectric dams are controlled by

EGAT.


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The various energy sources constitute the majority of factors that govern the price

of electricity, and all of the entities controlling the sources have political and economic

considerations unique to their own organizations. For example, the hydroelectric facilities

are constantly negotiating deals with the Department of Agriculture, which operate the

reservoirs, while refineries owned by other government and private entities can alter oil

and natural gas prices based on their own agendas and situations.

The PEA determines its prices at board-of-directors meetings, where the prices of

PEAs suppliers are the chief concern. The prices are also partly based on reports from

the Power Economics Division, the primary source of information for this research. And

the Power Economics Division is also the collection center for all the statistical

information regarding consumer billing and payments to suppliers.

In the period from October 1999 to September 2000, PEA had a total of

11,399,150 individual paying consumers, sold 53,034 Gigawatt-hours of energy, and

earned 120,811 million baht (about US$ 2,730 million, by todays exchange rates)

[5],[6]. The price of electricity averaged around 5.15 cents per Kilowatt-hour, nearly the

same per-unit price as American Electric Powers residential prices in Athens, Ohio, in

January 20028.

8 AEP prices can be found on monthly statements to consumers, or at www.aep.com.


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The various types of consumers serviced by PEA include businesses of various

sizes, houses, temporary loads such as construction, agricultural irrigation loads that

include special releases of water from the dams, governmental and subsidized loads and

back-up energy sales to clients of other providers in cases of outages. A detailed

breakdown of number of consumers and consumption levels is shown in Figures 4.1 and

4.2 on the next page. It is worth noting that, in October 2000, businesses and industries

constituted about 7 per cent of the individual consumers, but consumed nearly three-

quarters of the energy sold by PEA.

SERVICE REGIONS AND SECTORS

PEA services include transmission and distribution [5] to all provinces and areas

in Thailand not including the area covered by the Metropolitan Energy Authority (MEA),

which is the province of Bangkok. This means PEA covers most of Thailands areas,

serving a total of 11,479,555 individual metered customers, including residential areas,

businesses, government installations, irrigation facilities, and temporary and back-up

loads. Figures 4.1 and 4.2 below illustrate the breakdowns of PEA customers sorted by

consumption shares and customer types, respectively.


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Homes, over 150

Kwh.

12%

Small Businesses

8%

Medium Businesses

19%

Large Businesses

42%

Homes, under 150

KWh.

11%

Agricultural

Irrigations

under 1%

Temporary Loads

1%Backup Energy Sales

under 1%Government and

Subsidized

4%

Special Businesses

3%

Figure 4.1 - Breakdown of PEA Consumers Sorted by Energy Consumption,

October 2000 (source: PEA,Internal Quarterly Report, 2000)

Homes, under 150

KWh.

73%

Medium Businesses

under 1%

Large Businesses

under 1 %

Government andSubsidized

under 1%Temporary Loads

under 1%

Agricultural Irrigations

under 1%

Backup Energy Sales

under 1%Special Businesses

under 1%

Small Businesses

5%

Homes, over 150 Kwh.

20%

Figure 4.2 - Breakdown of PEA Consumers Sorted by Numbers of Individual Consumers,

October 2000 (source: PEA,Internal Quarterly Report, 2000)


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PROVINCIAL ENERGY AUTHORITY OF THAILAND:

PROCEDURES REGARDING ELECTRICITY THEFT

The Provincial Energy Authority of Thailand (PEA) is the state enterprise that is

responsible for providing electric utility services for end users of all sizes in provincial

Thailand. The area of service includes 72 provinces of Thailand, excluding Bangkok and

a few suburbs. Its customers include: low-voltage loads such as housing, small and

medium businesses, and small industrial sites; high-voltage loads such as large

businesses, office complexes, large industrial sites, industrial parks, large housing

communities, and government installations.

According to internal reports [5],[6], discovered incidents of meter violation a

key indicator of NTL remains relatively low. Between October 2000 and June 2001, a

total of 130 violations were found on high-voltage meters, and 2167 cases were found on

low-voltage meters. This number is very small compared to 11,399,150 total registered

users. Of course, this is a misleading presentation; registered users would not include

people who tap directly to the grid without meters. Some cases of violations may have

gone unnoticed, because inspection methods may not be sufficiently effective.

The PEA has a set of targets and schedules for inspecting meters. An inspection

team for high-voltage meters was observed for this research twice in July 2001; the team

includes inspectors from the central offices in Bangkok and drivers and local officials of

the PEA who are familiar with local sites and consumers. The local officials usually are


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selected from the group of people who conduct inspections for transformers installed for

customers, which are invariably located near the meters that are the targets of inspection.

METER INSPECTION PROTOCOLS

PEA has set guidelines and policies for dealing with electricity theft, as shown in

Table 4.1 below. Table 4.2 below shows the inspection schedules for the group

responsible for inspecting high-voltage (HV: 115 KV, 69 KV, 24 KV, and 12 KV) and

low-voltage (LV: loads with 380 V line-to-line) meters. The number of 220 V meters is

too great to make a dedicated inspection effort, so the inspection workload for those

meters goes to the unit-readers who are also trained to detect improprieties (see Chapter

3). Table 4.3 shows the regular schedule for reporting and deadlines for analyzing the

data on electricity theft collected in the field.

Table 4.1 - PEA Policies for Billing Customers Who Perpetrated Electricity Theft(Source: PEA internal memorandum, June 2001)

Billing Services Target Timeframes

1.) Billing for fines, revised rates, andmeter depreciation for large consumers

1.) Within 7 office days of receiving results

from the Evidence Department, the finesare sent out. Revised rates and depreciationbills are sent out within 15 office days.

2.) Billing for fines, revised rates, andmeter depreciation for small consumers

2.) The revised rates and fines are both sentout within 7 days of the reports of damagedmeters.3.) If the fines and bills in items 1 & 2 donot elicit any response from the consumerwithin 3 months, the case is summarizedand sent on to the legal department of therespective district office.


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Table 4.2 - Meter Inspection Protocols and Schedules for PEA (Source: PEA internalmemorandum, June 2001)

Item Goal/Schedule

1.) Regular Inspections1.1) 69 KV and 115 KV meters1.2) HV and LV meters with CTs1.3) LV meters

1.1)All meters inspected twice a year1.2)All meters inspected once a year1.3)Each year, at least 50% of all

meters in each district will beinspected

2.) Inspections of large customers with

violation records and customers inhigh risk businesses such as icefactories, hotels, etc.

2.) PEAs task forces will compile a list

and inspect all meters in these groups oncea quarter.

3.) Inspections for large customers thatare recently installed/changed

3.) All cases will be inspected within 30days of the installation/change

4.) Large customers with irregularities

4.1) Checking and isolating cases withirregular consumption or irregularbehaviors for future meter checks

4.2) Checking for irregularconsumption

4.1) The comptroller reviews consumptionand separate the irregularities within 15days of meter readings

4.2) Consumers with irregularities and

usage over one million baht($25,000) a month will be checkedimmediately

Low voltage meters are to bechecked within 15 days of therequest for checks

High voltage meters are to bechecked within 30 days

5.) Checking small consumers with 0unit readings

5.) A list of consumers with 3consecutive months of 0 unitreadings is compiled each trimester

Within the following trimester, themeters will be checked and thereasons for the 0 unit reading wouldbe reported


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Table 4.3 - PEA Guidelines and Schedules for Reporting Meter Inspection Results

(Source: PEA, internal memorandum, June 2001)

Operations and Results Report Due Dates

1. PEA operations:1.1Reports for routine meter checks1.2Reports for meters with past violations

and suspicious business groups1.3Major consumers with recent meter

installation/changes1.4Results from checking large

consumers with irregularities1.5Results from checking meters with

zero unit reading1.6Results from fine and revised rates

collections for large and smallconsumers

1. Reports of results in items 1.1 through1.6 are to be submitted to the districtoffices for each month within the 7 th ofthe following month.

2. Results reports for each district,

combined with reports from item 1.

2. Every meter-checking activity resultsand results from fines/revised rates for

each month are to be summarized andreported to the deputy head of eachdistrict. The deputy heads of districtsthen follow up and make necessarychanges in operations, then a report issubmitted for each month to theElectricity Economy Department by the15th of the following month.


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ECONOMIC CONSEQUENCES OF NON-TECHNICAL LOSSES FOR

THE PROVINCIAL ENERGY AUTHORITY OF THAILAND

According to PEA estimates [6], the 127 high-voltage meter violations found

between October 2000 and June 2001 resulted in the recovery of 4,904,021.45 units lost,

or about $245,000. The low-voltage meter violations in the same time period added up to

about $155,000 in lost revenues. These numbers reflect only the cost of producing the

stolen energy without taking into account the cost of equipment damage and payments

for the staff charged with detecting these thefts. These numbers also do not reflect energy

lost due to undetected theft. Details of electricity theft are shown in Tables 4.4 and 4.5

below.

Table 4.4 - Meter Tampering Found Among High Voltage Consumers in Thailand

Between October 2000 and June 2001.(Source: PEA, internal memorandum, June 2001)

High Voltage Consumers (Oct. 00 Jun 01)

Violation Type Cases Found

Tampering with terminal seals 69

Breaking control wires 12

Tampering with meter seals 30

Shorting control wires 5

Breaking the voltage taps 5Direct connections to grid 3

Tampering with the meter 2

Switching control wires 3

Total 127


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Table 4.5 - Meter Tampering Found Among Low Voltage Consumers in ThailandBetween October 2000 and June 2001.

(Source: PEA, internal memorandum, June 2001)

Low Voltage Consumers (Oct. 00 Jun. 01)

Violation Type Cases Found

Direct connections to grid 677

Using alternative neutral lines 541

Phase-to-phase connections 270

Meter tampering/ breaking meter seals 270Other 409

Total 2,167

The total amount of estimated recovered loss due to electricity theft in the period

between October 2000 and June 2001, about 8 million units [6], is very small compared

to the total losses of the system. The total losses of the PEA system is characterized by

subtracting the energy generated and purchased (system input) with the energy sold and

provided to some consumers without charge (system output), and the total losses amounts

to about 2.5 billion units, approximately 5.69 per cents of the system input. This means

the electricity theft found only accounts for about 0.32 per cent of the system losses, or

about 0.018 per cent of the systems energy input.

Though the NTL energy costs recovered seem to make up an insignificant

proportion of the system or even the total system losses, interviews with members of the

PEA inspection team observed for this research revealed that there are undoubtedly some

undiscovered cases of electricity theft. The undiscovered cases may be more or less than

the recovered costs. Also, the recovered costs only include the stolen energy. Other


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related costs that were not mentioned were maintenance costs, equipment damages, labor

costs, and the administrative costs for pursuing electricity theft cases.

4.2 AMERICAN ELECTRIC POWER (AEP)

AEP is a utility company that services a large area in the USA, covering nearly

200,000 square miles spanning eleven states. AEP is the largest investor owned utility in

the United States9. At AEP, the Revenue Protection department is directly responsible for

personnel training, receiving information on electricity theft from customers and staff,

analyze consumer load profiles for drastic changes compared to past trends, assessing

charges for electricity theft and equipment tampering, and if necessary prosecute

clients who endanger themselves or AEP field staff.

The main source of information AEP uses to detect and prevent electricity theft is

the meter reading staff, which is routinely trained by the Revenue Protection Department

to detect tampering with AEP equipment. According to Mr. Bill Daniel, manager of the

Revenue Protection program, AEP had revenue protection-related billings exceeding $

3.2 million annually. In the 2001 annual report available on the AEP website, AEP sold

over $41 billion worth of electricity and bought over $37 billion in the year ending

December 31, 2001. Interestingly, the same report lists $109 million under allowance

for uncollectible accounts.

9 American Electric Power, www.aep.com, 2002.


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The charges that constitute these billings include lost energy, tampering fees,

investigation fees, and interest. Customers are prosecuted under the following

circumstances:

1) the customer threatens (implied or actual) an AEP employee

2) repeat offenders

3) professionals who tamper with anothers meter for a fee

4) if law enforcement is already involved

5) the customer accesses any high voltage compartments or equipment (2.4 kV

or above)

6) the customer climbs or accesses a pole with the intent to steal electricity.

It should be noted again that the main sources of information regarding electricity

are field employees and trend analysis of customer load profiles. In his correspondence

with the author, Mr. Daniel stated that, regarding using power system analysis software

for detecting electricity theft, AEP has a large number of unmetered (flat rate)

installations that would render the resulting calculations unusable.10

In addition to AEP, a search for the phrase electricity theft on any search engine

on the Internet would yield information sites posted by utilities companies all over the

world.

10 Quoted from an electronic mail correspondence with Mr. Daniel from AEP, May 2002.


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4.3 WORLD BANK EASTERN EUROPE AND FORMER SOVIET UNION

The World Bank provides financial assistance to public utilities in many

developing countries, including countries in the former Soviet Union (FSU) and Eastern

Europe. The World Bank studied NTL in these areas in an effort to increase the

efficiency and profitability for local utilities. The results of the World Banks studies are

the sources of the summary below.

In a 1999 publication [2], the World Bank Energy Sector Unit reported on non-

payment in the electrical sector in various countries in Eastern Europe and the FSU

nations. The study covered various time spans for different countries ranging from 1992

to 1998. The main stated reason for the significant in some places very large amount

of non-payment, is the political and economic turmoil caused by the collapse of

communism and the response of the governments and the public to those changes.

The extent of the non-payment problem varies from country to country, and the

cause of the problem also varies. For example, countries with large natural energy

resources such as Russia and Ukraine continue to have problems collecting from

consumers, while countries that are dependent on energy imports have greater incentives

to solve the problem of non-payment. Household consumers are the main area of concern

in Albania, Georgia, and Armenia, while industrial consumers are the bigger problem in

Russia and Ukraine. An interesting type of non-payment is the use of cash substitutes that


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cant be converted to liquid assets by the utilities, which is a problem seen in Russia,

Ukraine, Georgia, and Armenia. The dimensions of the non-payment problem in these

countries are illustrated in Table 4.6 below.

IMPACTS

Large-scale non-payment by consumers has led to enormous consequences both at

the micro and macroeconomic level [2]. Payment default at the consumer end resulted in

transmission and distribution companies defaulting on their dues to the generating

companies, which in turn accumulate unpaid debts to energy suppliers, banks, and

employees. In some cases, the inability to pay for energy has led to rationing, such as

Georgia, which had only a few hours of electricity supply each day in 1995 [2], or

Armenia, which had supply for only two hours a day because its gas utility could not

settle debt with Turkmenistan suppliers.


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Table 4.6 - Extent of the Electric Utility Non-Payment Problem in Eastern Europe andFormer Soviet Union Nations (Source: World Bank Energy Sector Unit, Non-Payment in

the Electricity Sector in Eastern Europe and the Former Soviet Union, 1999)

Country Year Collection as %of billings

Cash as% of collections

Albania 1997 58 97Armenia 1992 1995

19961997

306562

256064

Bulgaria 19921997

7591

100100

Georgia 19961997 (Grid Co. Level)1997 (Distribution Co. Level)

577068

--3736

Hungary 19921997

8596

100100

Poland 1994 90 100Lithuania 1993

19978796

100100

Russia 19961998

7084

1617.6

Ukraine 199419961997

838691

--2018

In Russia, the utilities owe the government significant sums in taxes, while it is

estimated that the government owed even more for energy supplies. This situation created

a vicious cycle that resulted in Russian utilities being unable to pay for fuel supplies and

maintenance. Many large consumers also bartered or provided other cash substitutes for

electricity, forcing the utilities to do the same for fuel, resulting in inflated fuel prices

paid by utilities. This coupled with a drop in demand, ultimately led to a steep drop in

electricity generation utilization, the ratio of actual generation to total generation


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capacity, in Russia as well as other FSU nations with similar problems, shown in Table

4.7 below.

Table 4.7 - Capacity Utilization in the Power Sector of FSU(Source: World Bank Energy Sector Unit, Non-Payment in the Electricity Sector in

Eastern Europe and the Former Soviet Union, 1999)

Country Capacity (GW) Utilization %, 1990 Utilization %, 1994

Russia 205.6 60.1 46.9Ukraine 16.9 62.8 42.8

Lithuania 5.1 59.0

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