SlideShare uma empresa Scribd logo
1 de 6
Baixar para ler offline
ISSN: 2278 - 1323
International Journal of Advanced Research in Computer Engineering and Technology (IJARCET)
Volume 2, Issue 6, June 2013
www.ijarcet.org
2085
Determination of Nontechnical Losses via
Matlab Environment
Sonika Agrawal1
, Vijay Bhuria2
Department of Electrical Engineering, Madhav Institute of Technology and Science,
Gwalior (M.P.) 474005, India
Abstract---Total energy supplied by the
distribution utility does not reach to the consumer
end. An extensive amount of energy is lost in the
transmission and distribution system because of
Technical and Non Technical losses. In power
system the losses which cannot be predicted or
calculated in advance known as non-technical
losses. These losses are due to poor revenue cash
flow, huge over-heads, unmanaged peak Load /
Demand, large commercial losses due to poor
billing.
The purpose of this paper is to investigate
Nontechnical Losses and its economic consequences
in power sector with the help of a case study and
MATLAB Simulation in power system.
Keywords---Electricity Act-2007, Non Technical
Losses (NTL), Prepaid Energy Meter.
I. INTRODUCTION
India faces endemic electrical energy and peak
shortages. These shortages had a very injurious effect
on the overall financial growth of the country. In 1966-
67 the transmission and distribution losses in our
country, were around 15% which after increasing
gradually to 28.36 % by 2012-13.
In Indian scenario transmission and distribution losses
percentage has been high to a certain extent. The term
“distribution losses” refers to the difference between
the amount of energy delivered to the distribution
system and the amount of energy customer is to be
paid. However, as per sample studies carried out by
autonomous agencies including TERI, these losses
have been estimated to be as high as 50% in some
states. In a recent study carried by SBI capital markets,
The Transmission and Distribution losses have been
estimated as 58%[1].The Transmission and
Distribution losses in the advanced Countries of the
world ranging from 4-12%. Though, the Transmission
and Distribution losses in India are not comparable
with advanced countries because the system operating
conditions are different in different countries. To study
non-technical losses, which comprise a fraction of the
total losses in electrical power systems, the first step is
to understand the entire image of power system losses.
Power system losses can be divided into two
categories: technical losses and non-technical losses.
Technical losses are 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. 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 calculation failed to take into account.
NTL are more difficult to measure because these losses
are often unaccounted for by the system operators and
thus have no recorded information.
The project region chosen for this study was the Kalpi
Bridge, Morar, Gwalior district, Madhya Pradesh
because it is not only rural but also an urban area.
II. ANALYSIS OF NON TECHNICAL LOSSES
As NTL (nontechnical losses) cannot be computed
easily, while it can be estimated from preliminary
results, i.e. the result of technical losses are first
computed and subtracted from the total losses to obtain
the balance as NTL. The technical losses are computed
using suitable load-flow studies simulated under
MATLAB environment. Even though some electrical
power loss is unavoidable, steps can be taken to ensure
that it is minimized. Some measures have been applied
to this end, including those based on technology and
those that rely on human effort and ingenuity. The
technical losses would be computed with the help of
case studies of Gwalior and then impact of non
technical losses on them is shown.
Consider the transmission line length to be 3 km. The
following are the specifications of a simple two bus
system which is needed to complete a load-flow
calculation for power loss in the transmission line are
given below:
Base Values: 11000 Volts, 100 Ampere, 1.1 MVA,
110 Ohms
Transmission Line Resistance = 3 km × 0.266432
Ohms/conductor/km ×3 conductors
= 2.3978 ohms ( ) = 0.021799 per unit ( p.u.)
ISSN: 2278 - 1323
International Journal of Advanced Research in Computer Engineering and Technology (IJARCET)
Volume 2, Issue 6, June 2013
www.ijarcet.org 2086
Transmission Line Reactance = 3 km × 0.348692
Ohms/cond./km × 3 conductors
= 3.1382 = 0.028529 p.u.
Table I .Load Profiles for Industrial & Residential load
Time
(Hrs)
Industrial
Load(KVA)
Power
Factor
of
Load
1
Residential
Load(KVA)
Power
Factor of
Load 2
1 60 0.91 33 0.81
2 65 0.91 31 0.81
3 85 0.91 50 0.81
4 87 0.87 35 0.87
5 93 0.89 25 0.86
6 101 0.90 40 0.76
7 125 0.87 85 0.73
8 150 0.81 75 0.74
9 231 0.76 100 0.80
10 235 0.76 60 0.83
11 255 0.76 50 0.85
12 265 0.76 55 0.82
13 275 0.76 30 0.81
14 310 0.76 60 0.86
15 310 0.76 45 0.89
16 310 0.81 55 0.82
17 260 0.81 90 0.76
18 180 0.81 100 0.72
19 140 0.87 125 0.69
20 100 0.89 150 0.66
21 85 0.90 170 0.82
22 70 0.91 80 0.80
23 60 0.90 75 0.85
24 55 0.90 65 0.92
A load profile of 24 hours has been shown for ease and
the further calculations have been done with the help
of Newton-Raphson method. Figure2.1 shows the
variation of industrial and residential loads during
24hours.
Fig.2.1 Load variations over 24 hours
Fig.2.2 Variation of power factor over 24 hours
As shown in table I, the industrial load has its peak
demand during day times and the residential load
demand is more during morning and evening hours.
The load peaks are at 310 KVA for load1 and 170
KVA for load 2. The average load demands (sum of
peak values / no. of hours in a day) are 162.79 KVA
and 70.16 KVA for load 1 and load 2, respectively.
Load power factors are shown in Figure 2.2.
Resistance and reactance values of transmission line
are taken from the datasheet of 11kv transmission line.
To avoid overloading in the transmission line the
conductor size and line length were chosen arbitrarily
from the datasheet with the maximum conductor size
of 120mm2
.
Figure2.3 and 2.4 shows the graph of active and
reactive power losses respectively.
Fig.2.3 Active power losses
Fig.2.4 Reactive power losses
ISSN: 2278 - 1323
International Journal of Advanced Research in Computer Engineering and Technology (IJARCET)
Volume 2, Issue 6, June 2013
www.ijarcet.org 2087
III. NONTECHNICAL LOSSES ADDITION
As shown in the case study, non technical losses are
complex to calculate because it contains a major
portion of transmission & distribution losses. Non
technical losses can also be viewed as undetected load
of customers that the utilities don’t know. 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. From the various studies, it has
been concluded that NTL constitutes 2-3% of the total
system losses. Thus calculations have been shown by
adding 3% of the original KVA demand to one of the
bus and the modified results have been shown using
MATLAB simulation. Hence the total increase in
losses has been calculated. The extra load profile with
negative power factor addition is shown in the table II.
Table II. Extra Load Profile with Negative Power
Factor Addition
Time(Hrs) NTL
Load(KVA)
added at Bus 2
NTL Load
Power
Factor
1 2.92 -0.0247
2 3.01 -0.0247
3 4.15 -0.0247
4 3.80 -0.0265
5 3.55 -0.0259
6 4.40 -0.0235
7 6.12 -0.0218
8 6.90 -0.0231
9 10.00 -0.0241
10 9.01 -0.0251
11 9.25 -0.0259
12 9.75 -0.0245
13 9.20 -0.0242
14 11.01 -0.0259
15 10.45 -0.0267
16 10.80 -0.0239
17 10.25 -0.0226
18 8.26 -0.0215
19 7.96 -0.0222
20 7.25 -0.0218
21 7.90 -0.0235
22 4.65 -0.0240
23 4.41 -0.0250
24 3.80 -0.0275
Here the power factor contributions chosen are
negative because the NTL load is assumed to be
Inductive, i.e., motors or light fixtures. The extra load
and negative power factor addition to second bus are
shown in figure 3.1 and 3.2respectively.
Fig.3.1 NTL addition
Fig.3.2 Power factor additions
The simulation is run with bus 1 as the slack bus. The
NTL power factor is negative all times because of
inductive NTL load assumption. After the simulation
was done and evaluated, some remarkable results were
evident. The active & reactive power losses along with
NTL in transmission lines are shown in figure 3.3 and
3.4 respectively. The maximum active power losses
occurred as shown in graph are 633.9512 watts
maximum reactive power losses are while 829.6708
Watts.
Fig.3.3 Active losses with NTL
ISSN: 2278 - 1323
International Journal of Advanced Research in Computer Engineering and Technology (IJARCET)
Volume 2, Issue 6, June 2013
www.ijarcet.org 2088
Fig.3.4 Reactive losses with NTL
IV. COMPARISON OF LOSSES
With the addition of NTL to one of the load, the
overall system losses will increase. This large increase
is due to only small addition i.e. only 3% load. Mainly
reactive power losses have higher range than active
power losses. The two losses are compared with the
help of waveform shown in Figure 4.1 energy
consumption divided by the length of the time period,
in seconds. This information is always available for
metered loads, because it is what the utilities’ revenues
is based on.20
Fig.4
.1 Comparison of active power losses
Fig.4.2 Comparison of reactive power losses
Due to power factor contribution of the NTL load the
increase in load demand and the increase in
transmission losses are not at the same levels. In fact,
the losses increased at a larger rate than the loads. The
average load here is computed by averaging the overall
loss increase for each hour. The Figure 4.3 shows the
net per unit increase in losses at bus 2 where as
percentage increase of load and losses due to NTL are
also shown in Figures 4.4 and 4.5 respectively.
Fig.4.3 Per unit increase in losses
Fig.4.4 Percentage increase in load
Fig.4.5 Percentage increase in losses
Fig.4.6 Total increase in losses
However the increase in transmission loss places a
greater burden on the transmission equipment, the
greater cause for concern would be the NTL load itself.
ISSN: 2278 - 1323
International Journal of Advanced Research in Computer Engineering and Technology (IJARCET)
Volume 2, Issue 6, June 2013
www.ijarcet.org 2089
The total power losses in the transmission line are
shown in the Figure 4.6 which is sum of NTL active
power and losses increase due to NTL. 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.
At this point, it is getting clear that making
calculations for expected losses accurately is nearly
impossible in practice. 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 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 net summary of the
simulations result will be shown in table III.
Table III. Net Result Summary
SUMMARY OF
LOSSES
CALCULATION
ON AVERAGE
BASIS (units)
Losses without
NTL(watts)
97.9751
Losses with NTL(watts) 118.6527
Increase in losses(watts) 20.6776
%Increase in
losses(watts)
21.1049
P.U. load power at Bus 2
without NTL(watts)
0.06378
P.U. load power at Bus 2
with NTL(watts)
0.006391
Increase in load(watts) 3774.8
%Increase in load(watts) 6.6941
Total increased
losses(watts)[NTL Real
power+ Increased
transmission lines)
3795.4
From the above results it has been cleared that
reducing non technical losses will make sure that the
cost of electricity to the supplier will be reduced. The
cost of the electricity to the customer will therefore
also reduce, as the customers will not have to pay for
the non technical losses in the electricity distribution
network.
V. CONCLUSIONS
The measurement of technical and non technical losses
and its effects on electrical power systems as a whole
using existing analytical tools would be possible only
if information about the technical and NTL loads
themselves is available to the forecaster. Precisely
estimating losses in distribution systems is becoming
ever more important, as regulatory thinking shifts from
input-based to output-based methods. Also private
companies become more involved in the distribution
segment of the electricity industry.
Replacement of the faulty energy meters would further
reduce the non technical loss (i.e. the energy
expenditure tendency is higher if the meter is faulty).
The average energy expenditure of a consumer with a
faulty energy meter is 23 per cent more than their tariff
level. This fact indicates a serious loss of revenue to
the board. In this work, it was decided to take a two
bus system with one bus as slack bus and load is on
another bus. The load profiles of simple industrial area
and residential area has been taken. Then a small
percentage (3 %) of NTL has been added to one of the
load and the increased load and losses have been
shown with the help of Newton-Raphson load flow
method and MATLAB. Here negative power factor
contributions are chosen because the NTL load is
assumed to be inductive. All the simulation results
have been shown in the form of line diagrams clearly.
The readings of one full day have been taken. Then a
case study of one small area has been carried out to
determine the extent of non technical losses in that
area. For one full month The total units supplied and
total units billed have been thoroughly measured. Then
their difference is used to determine the extent of non
technical losses in that area. The loss calculation after
addition of 3% load without NTL on average basis is
97.9751 watts and the losses with NTL become
118.6527 watts. There is 20.6776 watts increase in
losses which is around 21.1049 % of total losses.
At the end, it has been concluded that utilities will
have to concentrate on reducing technical and non
technical loss.
Reducing these losses ensure that the cost of electricity
to customers will be reduced and in turn the efficiency
of the distribution network will be enhanced. Local
bodies can play a main role in the effective utilization
of electrical power. Hence, it is clear that it is
tremendously important to bring the awareness of
authorities to the up till now neglected area of rural
power distribution system. It is also clear that such
measures are essential for finding a least cost and time
bound solution to the problem of energy shortage in
MP.
ISSN: 2278 - 1323
International Journal of Advanced Research in Computer Engineering and Technology (IJARCET)
Volume 2, Issue 6, June 2013
www.ijarcet.org 2090
REFERENCES
[1] Navani, J.P., Sharma, N.K., SapraS. (2004).
“Technical and non-technical losses in power
system and its economic consequence in
Indian economy”, International Journal of
Electronics and Computer Science
Engineering, 1(2), 757-761.
[2] Isha Awasthi, Ritu Agarwal, “Implementation
of Simulink in Protection of Transmission
Lines”, International Journal of Advances in
Electrical and Electronics Engineering,
(IJAEEE), ISSN: 2319-1112), Vol. 01, No.
02, pp.195-202, (2012).
[3] Fourie, J.W. and Calmeyer, J.E., "A statistical
method to minimize electrical energy losses
in a local electricity distribution network,"
AFRICON, 2004, 7th AFRICON Conference
in Africa, vol.2, no., pp. 667-673, 15-17 Sept.
2004.
[4] R. Alves, Member, IEEE, P. Casanova,
E.Quirogas, 0. Ravelo, and W. Gimenez
Reduction of Non-Technical Losses by
Modernization and Updating of Measurement
Systems 1-4244-0288-3/06/$20.00 ©2006
IEEE.
[5] Charles A. Gross, Power System Analysis
(Second Edition). John Wiley & Sons, New
York, 1986; pp. 255 – 298, and pp. 304 – 322.
[6] Annual report of power and energy division
of planning commission, government of India,
New Delhi, 2011-12.
[7] “All India Electricity Statistics”, Central
Electricity Authority, Ministry of Power,
Government of India, New Delhi, 2011-12.
[8] Electricity Sector in India, “Key world energy
statistics”, 2012.
[9] A report on Madhya Pradesh Madhya Kshetra
Vidyut Vitaran Company Limited (A wholly
owned Govt. of MP Undertaking) RfP
(Revised) for Appointment of Distribution
Franchisee for Distribution and supply of
electricity in Gwalior Town.
[10]Dan Suriyamongkol, “Non technical losses in
electrical power systems”, A Report presented
to OhioUniversity ,November 2002.
[11]Tejinder Singh “Analysis of non technical
losses and its economic consequences on
power system – A case study of Punjab state”,
A report presented to Thapar University, June
2009.
.
7 19 21 23

Mais conteúdo relacionado

Mais procurados

Energy, economic and environmental analysis of fuzzy logic controllers used i...
Energy, economic and environmental analysis of fuzzy logic controllers used i...Energy, economic and environmental analysis of fuzzy logic controllers used i...
Energy, economic and environmental analysis of fuzzy logic controllers used i...
International Journal of Power Electronics and Drive Systems
 
Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...
Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...
Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...
paperpublications3
 

Mais procurados (18)

Energy, economic and environmental analysis of fuzzy logic controllers used i...
Energy, economic and environmental analysis of fuzzy logic controllers used i...Energy, economic and environmental analysis of fuzzy logic controllers used i...
Energy, economic and environmental analysis of fuzzy logic controllers used i...
 
Fuzzy Logic Method in SCADA to Optimize Network Electric Power Smart Grid
Fuzzy Logic Method in SCADA to Optimize Network Electric Power Smart GridFuzzy Logic Method in SCADA to Optimize Network Electric Power Smart Grid
Fuzzy Logic Method in SCADA to Optimize Network Electric Power Smart Grid
 
Voltage Sag Compensation in Fourteen Bus System Using IDVR
Voltage Sag Compensation in Fourteen Bus System Using IDVRVoltage Sag Compensation in Fourteen Bus System Using IDVR
Voltage Sag Compensation in Fourteen Bus System Using IDVR
 
DISTRIBUTED TRANSFORMER ENERGY METER USING GSM TECHNOLOGY
DISTRIBUTED TRANSFORMER ENERGY METER USING GSM TECHNOLOGYDISTRIBUTED TRANSFORMER ENERGY METER USING GSM TECHNOLOGY
DISTRIBUTED TRANSFORMER ENERGY METER USING GSM TECHNOLOGY
 
Harmonic enhancement in microgrid with applications on sensitive loads
Harmonic enhancement in microgrid with applications on sensitive loadsHarmonic enhancement in microgrid with applications on sensitive loads
Harmonic enhancement in microgrid with applications on sensitive loads
 
GSM Based Wireless Load-Shedding Management System for Non Emergency Condition
GSM Based Wireless Load-Shedding Management System for Non Emergency ConditionGSM Based Wireless Load-Shedding Management System for Non Emergency Condition
GSM Based Wireless Load-Shedding Management System for Non Emergency Condition
 
Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...
Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...
Design and Implementation of Wireless Sensor Node for WSN for Automatic Meter...
 
Design of management dashboard (smart electric grids)
Design of management dashboard (smart electric grids)Design of management dashboard (smart electric grids)
Design of management dashboard (smart electric grids)
 
IRJET - Design of EV with Fault Detection and Monitoring in Low Voltage S...
IRJET -  	  Design of EV with Fault Detection and Monitoring in Low Voltage S...IRJET -  	  Design of EV with Fault Detection and Monitoring in Low Voltage S...
IRJET - Design of EV with Fault Detection and Monitoring in Low Voltage S...
 
IRJET- Feature Ranking for Energy Disaggregation
IRJET-  	  Feature Ranking for Energy Disaggregation IRJET-  	  Feature Ranking for Energy Disaggregation
IRJET- Feature Ranking for Energy Disaggregation
 
Performance Analysis Of PV Interfaced Neural Network Based Hybrid Active Powe...
Performance Analysis Of PV Interfaced Neural Network Based Hybrid Active Powe...Performance Analysis Of PV Interfaced Neural Network Based Hybrid Active Powe...
Performance Analysis Of PV Interfaced Neural Network Based Hybrid Active Powe...
 
Development of Power Signal Distributor for Electronic Power Meters
Development of Power Signal Distributor for Electronic Power MetersDevelopment of Power Signal Distributor for Electronic Power Meters
Development of Power Signal Distributor for Electronic Power Meters
 
S2-R2
S2-R2S2-R2
S2-R2
 
GRID INTERCONNECTION OF RENEWABLE ENERGY SOURCES AT DISTRIBUTION LEVEL WITH P...
GRID INTERCONNECTION OF RENEWABLE ENERGY SOURCES AT DISTRIBUTION LEVEL WITH P...GRID INTERCONNECTION OF RENEWABLE ENERGY SOURCES AT DISTRIBUTION LEVEL WITH P...
GRID INTERCONNECTION OF RENEWABLE ENERGY SOURCES AT DISTRIBUTION LEVEL WITH P...
 
IRJET- Feed-Forward Neural Network Based Transient Stability Assessment o...
IRJET-  	  Feed-Forward Neural Network Based Transient Stability Assessment o...IRJET-  	  Feed-Forward Neural Network Based Transient Stability Assessment o...
IRJET- Feed-Forward Neural Network Based Transient Stability Assessment o...
 
Final Year Project Report. (Management of Smart Electricity Grids)
Final Year Project Report. (Management of Smart Electricity Grids)Final Year Project Report. (Management of Smart Electricity Grids)
Final Year Project Report. (Management of Smart Electricity Grids)
 
A hybrid algorithm for voltage stability enhancement of distribution systems
A hybrid algorithm for voltage stability enhancement of distribution systems A hybrid algorithm for voltage stability enhancement of distribution systems
A hybrid algorithm for voltage stability enhancement of distribution systems
 
Detection and Instantaneous Prevention of Power Theft
Detection and Instantaneous Prevention of Power TheftDetection and Instantaneous Prevention of Power Theft
Detection and Instantaneous Prevention of Power Theft
 

Semelhante a Volume 2-issue-6-2085-2090

11.optimization of loss minimization using facts in deregulated power systems
11.optimization of loss minimization using facts in deregulated power systems11.optimization of loss minimization using facts in deregulated power systems
11.optimization of loss minimization using facts in deregulated power systems
Alexander Decker
 
Optimization of loss minimization using facts in deregulated power systems
Optimization of loss minimization using facts in deregulated power systemsOptimization of loss minimization using facts in deregulated power systems
Optimization of loss minimization using facts in deregulated power systems
Alexander Decker
 
Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...
Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...
Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...
IJMTST Journal
 
Three phase parameter data logging and fault detection
Three phase parameter data logging and fault detectionThree phase parameter data logging and fault detection
Three phase parameter data logging and fault detection
iaemedu
 
Three phase parameter data logging and fault detection using gsm technology
Three phase parameter data logging and fault detection using gsm technologyThree phase parameter data logging and fault detection using gsm technology
Three phase parameter data logging and fault detection using gsm technology
iaemedu
 
Optimal dg placement using multiobjective index and its effect on stability 2
Optimal dg placement using multiobjective index and its effect on stability 2Optimal dg placement using multiobjective index and its effect on stability 2
Optimal dg placement using multiobjective index and its effect on stability 2
IAEME Publication
 

Semelhante a Volume 2-issue-6-2085-2090 (20)

Technical Power Losses Determination: Abeokuta, Ogun State, Nigeria Distribut...
Technical Power Losses Determination: Abeokuta, Ogun State, Nigeria Distribut...Technical Power Losses Determination: Abeokuta, Ogun State, Nigeria Distribut...
Technical Power Losses Determination: Abeokuta, Ogun State, Nigeria Distribut...
 
A010610110
A010610110A010610110
A010610110
 
Influencing Factors on Power Losses in Electric Distribution Network
Influencing Factors on Power Losses in Electric Distribution NetworkInfluencing Factors on Power Losses in Electric Distribution Network
Influencing Factors on Power Losses in Electric Distribution Network
 
IRJET- An Optimal and Capacitor Placement for Loss Reduction in Electrica...
IRJET-  	  An Optimal and Capacitor Placement for Loss Reduction in Electrica...IRJET-  	  An Optimal and Capacitor Placement for Loss Reduction in Electrica...
IRJET- An Optimal and Capacitor Placement for Loss Reduction in Electrica...
 
L0102189100
L0102189100L0102189100
L0102189100
 
IRJET- Voltage Stability, Loadability and Contingency Analysis with Optimal I...
IRJET- Voltage Stability, Loadability and Contingency Analysis with Optimal I...IRJET- Voltage Stability, Loadability and Contingency Analysis with Optimal I...
IRJET- Voltage Stability, Loadability and Contingency Analysis with Optimal I...
 
IRJET- Automation in Substation using Programmable Logic Controller (PLC)
IRJET- Automation in Substation using Programmable Logic Controller (PLC)IRJET- Automation in Substation using Programmable Logic Controller (PLC)
IRJET- Automation in Substation using Programmable Logic Controller (PLC)
 
11.optimization of loss minimization using facts in deregulated power systems
11.optimization of loss minimization using facts in deregulated power systems11.optimization of loss minimization using facts in deregulated power systems
11.optimization of loss minimization using facts in deregulated power systems
 
Optimization of loss minimization using facts in deregulated power systems
Optimization of loss minimization using facts in deregulated power systemsOptimization of loss minimization using facts in deregulated power systems
Optimization of loss minimization using facts in deregulated power systems
 
Optimum allocation of distributed generation by load flow analysis method a c...
Optimum allocation of distributed generation by load flow analysis method a c...Optimum allocation of distributed generation by load flow analysis method a c...
Optimum allocation of distributed generation by load flow analysis method a c...
 
IRJET- Overloading Detection in Residentional Area
IRJET- Overloading Detection in Residentional AreaIRJET- Overloading Detection in Residentional Area
IRJET- Overloading Detection in Residentional Area
 
Electricity Theft: Reason and Solution
Electricity Theft: Reason and SolutionElectricity Theft: Reason and Solution
Electricity Theft: Reason and Solution
 
Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...
Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...
Improving Stability of Utility-Tied Wind Generators using Dynamic Voltage Res...
 
Three phase parameter data logging and fault detection
Three phase parameter data logging and fault detectionThree phase parameter data logging and fault detection
Three phase parameter data logging and fault detection
 
Three phase parameter data logging and fault detection using gsm technology
Three phase parameter data logging and fault detection using gsm technologyThree phase parameter data logging and fault detection using gsm technology
Three phase parameter data logging and fault detection using gsm technology
 
Control Methodology for Peak Demand through Multi-Source Environment at Deman...
Control Methodology for Peak Demand through Multi-Source Environment at Deman...Control Methodology for Peak Demand through Multi-Source Environment at Deman...
Control Methodology for Peak Demand through Multi-Source Environment at Deman...
 
Power Factor Control at ABA Control 33/11kV Injection Substation Using Auto T...
Power Factor Control at ABA Control 33/11kV Injection Substation Using Auto T...Power Factor Control at ABA Control 33/11kV Injection Substation Using Auto T...
Power Factor Control at ABA Control 33/11kV Injection Substation Using Auto T...
 
Smart grid cost optimization using genetic algorithm
Smart grid cost optimization using genetic algorithmSmart grid cost optimization using genetic algorithm
Smart grid cost optimization using genetic algorithm
 
IRJET- Microcontroller based Automatic Power Change Over Mechanism
IRJET- Microcontroller based Automatic Power Change Over MechanismIRJET- Microcontroller based Automatic Power Change Over Mechanism
IRJET- Microcontroller based Automatic Power Change Over Mechanism
 
Optimal dg placement using multiobjective index and its effect on stability 2
Optimal dg placement using multiobjective index and its effect on stability 2Optimal dg placement using multiobjective index and its effect on stability 2
Optimal dg placement using multiobjective index and its effect on stability 2
 

Mais de Editor IJARCET

Volume 2-issue-6-2205-2207
Volume 2-issue-6-2205-2207Volume 2-issue-6-2205-2207
Volume 2-issue-6-2205-2207
Editor IJARCET
 
Volume 2-issue-6-2195-2199
Volume 2-issue-6-2195-2199Volume 2-issue-6-2195-2199
Volume 2-issue-6-2195-2199
Editor IJARCET
 
Volume 2-issue-6-2200-2204
Volume 2-issue-6-2200-2204Volume 2-issue-6-2200-2204
Volume 2-issue-6-2200-2204
Editor IJARCET
 
Volume 2-issue-6-2190-2194
Volume 2-issue-6-2190-2194Volume 2-issue-6-2190-2194
Volume 2-issue-6-2190-2194
Editor IJARCET
 
Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189
Editor IJARCET
 
Volume 2-issue-6-2177-2185
Volume 2-issue-6-2177-2185Volume 2-issue-6-2177-2185
Volume 2-issue-6-2177-2185
Editor IJARCET
 
Volume 2-issue-6-2173-2176
Volume 2-issue-6-2173-2176Volume 2-issue-6-2173-2176
Volume 2-issue-6-2173-2176
Editor IJARCET
 
Volume 2-issue-6-2165-2172
Volume 2-issue-6-2165-2172Volume 2-issue-6-2165-2172
Volume 2-issue-6-2165-2172
Editor IJARCET
 
Volume 2-issue-6-2159-2164
Volume 2-issue-6-2159-2164Volume 2-issue-6-2159-2164
Volume 2-issue-6-2159-2164
Editor IJARCET
 
Volume 2-issue-6-2155-2158
Volume 2-issue-6-2155-2158Volume 2-issue-6-2155-2158
Volume 2-issue-6-2155-2158
Editor IJARCET
 
Volume 2-issue-6-2148-2154
Volume 2-issue-6-2148-2154Volume 2-issue-6-2148-2154
Volume 2-issue-6-2148-2154
Editor IJARCET
 
Volume 2-issue-6-2143-2147
Volume 2-issue-6-2143-2147Volume 2-issue-6-2143-2147
Volume 2-issue-6-2143-2147
Editor IJARCET
 
Volume 2-issue-6-2119-2124
Volume 2-issue-6-2119-2124Volume 2-issue-6-2119-2124
Volume 2-issue-6-2119-2124
Editor IJARCET
 
Volume 2-issue-6-2139-2142
Volume 2-issue-6-2139-2142Volume 2-issue-6-2139-2142
Volume 2-issue-6-2139-2142
Editor IJARCET
 
Volume 2-issue-6-2130-2138
Volume 2-issue-6-2130-2138Volume 2-issue-6-2130-2138
Volume 2-issue-6-2130-2138
Editor IJARCET
 
Volume 2-issue-6-2125-2129
Volume 2-issue-6-2125-2129Volume 2-issue-6-2125-2129
Volume 2-issue-6-2125-2129
Editor IJARCET
 
Volume 2-issue-6-2114-2118
Volume 2-issue-6-2114-2118Volume 2-issue-6-2114-2118
Volume 2-issue-6-2114-2118
Editor IJARCET
 
Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113
Editor IJARCET
 
Volume 2-issue-6-2102-2107
Volume 2-issue-6-2102-2107Volume 2-issue-6-2102-2107
Volume 2-issue-6-2102-2107
Editor IJARCET
 

Mais de Editor IJARCET (20)

Electrically small antennas: The art of miniaturization
Electrically small antennas: The art of miniaturizationElectrically small antennas: The art of miniaturization
Electrically small antennas: The art of miniaturization
 
Volume 2-issue-6-2205-2207
Volume 2-issue-6-2205-2207Volume 2-issue-6-2205-2207
Volume 2-issue-6-2205-2207
 
Volume 2-issue-6-2195-2199
Volume 2-issue-6-2195-2199Volume 2-issue-6-2195-2199
Volume 2-issue-6-2195-2199
 
Volume 2-issue-6-2200-2204
Volume 2-issue-6-2200-2204Volume 2-issue-6-2200-2204
Volume 2-issue-6-2200-2204
 
Volume 2-issue-6-2190-2194
Volume 2-issue-6-2190-2194Volume 2-issue-6-2190-2194
Volume 2-issue-6-2190-2194
 
Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189Volume 2-issue-6-2186-2189
Volume 2-issue-6-2186-2189
 
Volume 2-issue-6-2177-2185
Volume 2-issue-6-2177-2185Volume 2-issue-6-2177-2185
Volume 2-issue-6-2177-2185
 
Volume 2-issue-6-2173-2176
Volume 2-issue-6-2173-2176Volume 2-issue-6-2173-2176
Volume 2-issue-6-2173-2176
 
Volume 2-issue-6-2165-2172
Volume 2-issue-6-2165-2172Volume 2-issue-6-2165-2172
Volume 2-issue-6-2165-2172
 
Volume 2-issue-6-2159-2164
Volume 2-issue-6-2159-2164Volume 2-issue-6-2159-2164
Volume 2-issue-6-2159-2164
 
Volume 2-issue-6-2155-2158
Volume 2-issue-6-2155-2158Volume 2-issue-6-2155-2158
Volume 2-issue-6-2155-2158
 
Volume 2-issue-6-2148-2154
Volume 2-issue-6-2148-2154Volume 2-issue-6-2148-2154
Volume 2-issue-6-2148-2154
 
Volume 2-issue-6-2143-2147
Volume 2-issue-6-2143-2147Volume 2-issue-6-2143-2147
Volume 2-issue-6-2143-2147
 
Volume 2-issue-6-2119-2124
Volume 2-issue-6-2119-2124Volume 2-issue-6-2119-2124
Volume 2-issue-6-2119-2124
 
Volume 2-issue-6-2139-2142
Volume 2-issue-6-2139-2142Volume 2-issue-6-2139-2142
Volume 2-issue-6-2139-2142
 
Volume 2-issue-6-2130-2138
Volume 2-issue-6-2130-2138Volume 2-issue-6-2130-2138
Volume 2-issue-6-2130-2138
 
Volume 2-issue-6-2125-2129
Volume 2-issue-6-2125-2129Volume 2-issue-6-2125-2129
Volume 2-issue-6-2125-2129
 
Volume 2-issue-6-2114-2118
Volume 2-issue-6-2114-2118Volume 2-issue-6-2114-2118
Volume 2-issue-6-2114-2118
 
Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113Volume 2-issue-6-2108-2113
Volume 2-issue-6-2108-2113
 
Volume 2-issue-6-2102-2107
Volume 2-issue-6-2102-2107Volume 2-issue-6-2102-2107
Volume 2-issue-6-2102-2107
 

Último

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
Earley Information Science
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
giselly40
 

Último (20)

Factors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptxFactors to Consider When Choosing Accounts Payable Services Providers.pptx
Factors to Consider When Choosing Accounts Payable Services Providers.pptx
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024Tata AIG General Insurance Company - Insurer Innovation Award 2024
Tata AIG General Insurance Company - Insurer Innovation Award 2024
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)Powerful Google developer tools for immediate impact! (2023-24 C)
Powerful Google developer tools for immediate impact! (2023-24 C)
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 

Volume 2-issue-6-2085-2090

  • 1. ISSN: 2278 - 1323 International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2, Issue 6, June 2013 www.ijarcet.org 2085 Determination of Nontechnical Losses via Matlab Environment Sonika Agrawal1 , Vijay Bhuria2 Department of Electrical Engineering, Madhav Institute of Technology and Science, Gwalior (M.P.) 474005, India Abstract---Total energy supplied by the distribution utility does not reach to the consumer end. An extensive amount of energy is lost in the transmission and distribution system because of Technical and Non Technical losses. In power system the losses which cannot be predicted or calculated in advance known as non-technical losses. These losses are due to poor revenue cash flow, huge over-heads, unmanaged peak Load / Demand, large commercial losses due to poor billing. The purpose of this paper is to investigate Nontechnical Losses and its economic consequences in power sector with the help of a case study and MATLAB Simulation in power system. Keywords---Electricity Act-2007, Non Technical Losses (NTL), Prepaid Energy Meter. I. INTRODUCTION India faces endemic electrical energy and peak shortages. These shortages had a very injurious effect on the overall financial growth of the country. In 1966- 67 the transmission and distribution losses in our country, were around 15% which after increasing gradually to 28.36 % by 2012-13. In Indian scenario transmission and distribution losses percentage has been high to a certain extent. The term “distribution losses” refers to the difference between the amount of energy delivered to the distribution system and the amount of energy customer is to be paid. However, as per sample studies carried out by autonomous agencies including TERI, these losses have been estimated to be as high as 50% in some states. In a recent study carried by SBI capital markets, The Transmission and Distribution losses have been estimated as 58%[1].The Transmission and Distribution losses in the advanced Countries of the world ranging from 4-12%. Though, the Transmission and Distribution losses in India are not comparable with advanced countries because the system operating conditions are different in different countries. To study non-technical losses, which comprise a fraction of the total losses in electrical power systems, the first step is to understand the entire image of power system losses. Power system losses can be divided into two categories: technical losses and non-technical losses. Technical losses are 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. 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 calculation failed to take into account. NTL are more difficult to measure because these losses are often unaccounted for by the system operators and thus have no recorded information. The project region chosen for this study was the Kalpi Bridge, Morar, Gwalior district, Madhya Pradesh because it is not only rural but also an urban area. II. ANALYSIS OF NON TECHNICAL LOSSES As NTL (nontechnical losses) cannot be computed easily, while it can be estimated from preliminary results, i.e. the result of technical losses are first computed and subtracted from the total losses to obtain the balance as NTL. The technical losses are computed using suitable load-flow studies simulated under MATLAB environment. Even though some electrical power loss is unavoidable, steps can be taken to ensure that it is minimized. Some measures have been applied to this end, including those based on technology and those that rely on human effort and ingenuity. The technical losses would be computed with the help of case studies of Gwalior and then impact of non technical losses on them is shown. Consider the transmission line length to be 3 km. The following are the specifications of a simple two bus system which is needed to complete a load-flow calculation for power loss in the transmission line are given below: Base Values: 11000 Volts, 100 Ampere, 1.1 MVA, 110 Ohms Transmission Line Resistance = 3 km × 0.266432 Ohms/conductor/km ×3 conductors = 2.3978 ohms ( ) = 0.021799 per unit ( p.u.)
  • 2. ISSN: 2278 - 1323 International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2, Issue 6, June 2013 www.ijarcet.org 2086 Transmission Line Reactance = 3 km × 0.348692 Ohms/cond./km × 3 conductors = 3.1382 = 0.028529 p.u. Table I .Load Profiles for Industrial & Residential load Time (Hrs) Industrial Load(KVA) Power Factor of Load 1 Residential Load(KVA) Power Factor of Load 2 1 60 0.91 33 0.81 2 65 0.91 31 0.81 3 85 0.91 50 0.81 4 87 0.87 35 0.87 5 93 0.89 25 0.86 6 101 0.90 40 0.76 7 125 0.87 85 0.73 8 150 0.81 75 0.74 9 231 0.76 100 0.80 10 235 0.76 60 0.83 11 255 0.76 50 0.85 12 265 0.76 55 0.82 13 275 0.76 30 0.81 14 310 0.76 60 0.86 15 310 0.76 45 0.89 16 310 0.81 55 0.82 17 260 0.81 90 0.76 18 180 0.81 100 0.72 19 140 0.87 125 0.69 20 100 0.89 150 0.66 21 85 0.90 170 0.82 22 70 0.91 80 0.80 23 60 0.90 75 0.85 24 55 0.90 65 0.92 A load profile of 24 hours has been shown for ease and the further calculations have been done with the help of Newton-Raphson method. Figure2.1 shows the variation of industrial and residential loads during 24hours. Fig.2.1 Load variations over 24 hours Fig.2.2 Variation of power factor over 24 hours As shown in table I, the industrial load has its peak demand during day times and the residential load demand is more during morning and evening hours. The load peaks are at 310 KVA for load1 and 170 KVA for load 2. The average load demands (sum of peak values / no. of hours in a day) are 162.79 KVA and 70.16 KVA for load 1 and load 2, respectively. Load power factors are shown in Figure 2.2. Resistance and reactance values of transmission line are taken from the datasheet of 11kv transmission line. To avoid overloading in the transmission line the conductor size and line length were chosen arbitrarily from the datasheet with the maximum conductor size of 120mm2 . Figure2.3 and 2.4 shows the graph of active and reactive power losses respectively. Fig.2.3 Active power losses Fig.2.4 Reactive power losses
  • 3. ISSN: 2278 - 1323 International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2, Issue 6, June 2013 www.ijarcet.org 2087 III. NONTECHNICAL LOSSES ADDITION As shown in the case study, non technical losses are complex to calculate because it contains a major portion of transmission & distribution losses. Non technical losses can also be viewed as undetected load of customers that the utilities don’t know. 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. From the various studies, it has been concluded that NTL constitutes 2-3% of the total system losses. Thus calculations have been shown by adding 3% of the original KVA demand to one of the bus and the modified results have been shown using MATLAB simulation. Hence the total increase in losses has been calculated. The extra load profile with negative power factor addition is shown in the table II. Table II. Extra Load Profile with Negative Power Factor Addition Time(Hrs) NTL Load(KVA) added at Bus 2 NTL Load Power Factor 1 2.92 -0.0247 2 3.01 -0.0247 3 4.15 -0.0247 4 3.80 -0.0265 5 3.55 -0.0259 6 4.40 -0.0235 7 6.12 -0.0218 8 6.90 -0.0231 9 10.00 -0.0241 10 9.01 -0.0251 11 9.25 -0.0259 12 9.75 -0.0245 13 9.20 -0.0242 14 11.01 -0.0259 15 10.45 -0.0267 16 10.80 -0.0239 17 10.25 -0.0226 18 8.26 -0.0215 19 7.96 -0.0222 20 7.25 -0.0218 21 7.90 -0.0235 22 4.65 -0.0240 23 4.41 -0.0250 24 3.80 -0.0275 Here the power factor contributions chosen are negative because the NTL load is assumed to be Inductive, i.e., motors or light fixtures. The extra load and negative power factor addition to second bus are shown in figure 3.1 and 3.2respectively. Fig.3.1 NTL addition Fig.3.2 Power factor additions The simulation is run with bus 1 as the slack bus. The NTL power factor is negative all times because of inductive NTL load assumption. After the simulation was done and evaluated, some remarkable results were evident. The active & reactive power losses along with NTL in transmission lines are shown in figure 3.3 and 3.4 respectively. The maximum active power losses occurred as shown in graph are 633.9512 watts maximum reactive power losses are while 829.6708 Watts. Fig.3.3 Active losses with NTL
  • 4. ISSN: 2278 - 1323 International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2, Issue 6, June 2013 www.ijarcet.org 2088 Fig.3.4 Reactive losses with NTL IV. COMPARISON OF LOSSES With the addition of NTL to one of the load, the overall system losses will increase. This large increase is due to only small addition i.e. only 3% load. Mainly reactive power losses have higher range than active power losses. The two losses are compared with the help of waveform shown in Figure 4.1 energy consumption divided by the length of the time period, in seconds. This information is always available for metered loads, because it is what the utilities’ revenues is based on.20 Fig.4 .1 Comparison of active power losses Fig.4.2 Comparison of reactive power losses Due to power factor contribution of the NTL load the increase in load demand and the increase in transmission losses are not at the same levels. In fact, the losses increased at a larger rate than the loads. The average load here is computed by averaging the overall loss increase for each hour. The Figure 4.3 shows the net per unit increase in losses at bus 2 where as percentage increase of load and losses due to NTL are also shown in Figures 4.4 and 4.5 respectively. Fig.4.3 Per unit increase in losses Fig.4.4 Percentage increase in load Fig.4.5 Percentage increase in losses Fig.4.6 Total increase in losses However the increase in transmission loss places a greater burden on the transmission equipment, the greater cause for concern would be the NTL load itself.
  • 5. ISSN: 2278 - 1323 International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2, Issue 6, June 2013 www.ijarcet.org 2089 The total power losses in the transmission line are shown in the Figure 4.6 which is sum of NTL active power and losses increase due to NTL. 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. At this point, it is getting clear that making calculations for expected losses accurately is nearly impossible in practice. 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 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 net summary of the simulations result will be shown in table III. Table III. Net Result Summary SUMMARY OF LOSSES CALCULATION ON AVERAGE BASIS (units) Losses without NTL(watts) 97.9751 Losses with NTL(watts) 118.6527 Increase in losses(watts) 20.6776 %Increase in losses(watts) 21.1049 P.U. load power at Bus 2 without NTL(watts) 0.06378 P.U. load power at Bus 2 with NTL(watts) 0.006391 Increase in load(watts) 3774.8 %Increase in load(watts) 6.6941 Total increased losses(watts)[NTL Real power+ Increased transmission lines) 3795.4 From the above results it has been cleared that reducing non technical losses will make sure that the cost of electricity to the supplier will be reduced. The cost of the electricity to the customer will therefore also reduce, as the customers will not have to pay for the non technical losses in the electricity distribution network. V. CONCLUSIONS The measurement of technical and non technical losses and its effects on electrical power systems as a whole using existing analytical tools would be possible only if information about the technical and NTL loads themselves is available to the forecaster. Precisely estimating losses in distribution systems is becoming ever more important, as regulatory thinking shifts from input-based to output-based methods. Also private companies become more involved in the distribution segment of the electricity industry. Replacement of the faulty energy meters would further reduce the non technical loss (i.e. the energy expenditure tendency is higher if the meter is faulty). The average energy expenditure of a consumer with a faulty energy meter is 23 per cent more than their tariff level. This fact indicates a serious loss of revenue to the board. In this work, it was decided to take a two bus system with one bus as slack bus and load is on another bus. The load profiles of simple industrial area and residential area has been taken. Then a small percentage (3 %) of NTL has been added to one of the load and the increased load and losses have been shown with the help of Newton-Raphson load flow method and MATLAB. Here negative power factor contributions are chosen because the NTL load is assumed to be inductive. All the simulation results have been shown in the form of line diagrams clearly. The readings of one full day have been taken. Then a case study of one small area has been carried out to determine the extent of non technical losses in that area. For one full month The total units supplied and total units billed have been thoroughly measured. Then their difference is used to determine the extent of non technical losses in that area. The loss calculation after addition of 3% load without NTL on average basis is 97.9751 watts and the losses with NTL become 118.6527 watts. There is 20.6776 watts increase in losses which is around 21.1049 % of total losses. At the end, it has been concluded that utilities will have to concentrate on reducing technical and non technical loss. Reducing these losses ensure that the cost of electricity to customers will be reduced and in turn the efficiency of the distribution network will be enhanced. Local bodies can play a main role in the effective utilization of electrical power. Hence, it is clear that it is tremendously important to bring the awareness of authorities to the up till now neglected area of rural power distribution system. It is also clear that such measures are essential for finding a least cost and time bound solution to the problem of energy shortage in MP.
  • 6. ISSN: 2278 - 1323 International Journal of Advanced Research in Computer Engineering and Technology (IJARCET) Volume 2, Issue 6, June 2013 www.ijarcet.org 2090 REFERENCES [1] Navani, J.P., Sharma, N.K., SapraS. (2004). “Technical and non-technical losses in power system and its economic consequence in Indian economy”, International Journal of Electronics and Computer Science Engineering, 1(2), 757-761. [2] Isha Awasthi, Ritu Agarwal, “Implementation of Simulink in Protection of Transmission Lines”, International Journal of Advances in Electrical and Electronics Engineering, (IJAEEE), ISSN: 2319-1112), Vol. 01, No. 02, pp.195-202, (2012). [3] Fourie, J.W. and Calmeyer, J.E., "A statistical method to minimize electrical energy losses in a local electricity distribution network," AFRICON, 2004, 7th AFRICON Conference in Africa, vol.2, no., pp. 667-673, 15-17 Sept. 2004. [4] R. Alves, Member, IEEE, P. Casanova, E.Quirogas, 0. Ravelo, and W. Gimenez Reduction of Non-Technical Losses by Modernization and Updating of Measurement Systems 1-4244-0288-3/06/$20.00 ©2006 IEEE. [5] Charles A. Gross, Power System Analysis (Second Edition). John Wiley & Sons, New York, 1986; pp. 255 – 298, and pp. 304 – 322. [6] Annual report of power and energy division of planning commission, government of India, New Delhi, 2011-12. [7] “All India Electricity Statistics”, Central Electricity Authority, Ministry of Power, Government of India, New Delhi, 2011-12. [8] Electricity Sector in India, “Key world energy statistics”, 2012. [9] A report on Madhya Pradesh Madhya Kshetra Vidyut Vitaran Company Limited (A wholly owned Govt. of MP Undertaking) RfP (Revised) for Appointment of Distribution Franchisee for Distribution and supply of electricity in Gwalior Town. [10]Dan Suriyamongkol, “Non technical losses in electrical power systems”, A Report presented to OhioUniversity ,November 2002. [11]Tejinder Singh “Analysis of non technical losses and its economic consequences on power system – A case study of Punjab state”, A report presented to Thapar University, June 2009. . 7 19 21 23