Loss Reduction in Distribution Networks a Case Study: Technical and Economic
Analysis
Shobo Adedamola Adewunmi 1, Igemokhai Julian Oshioreamhe2, Oluwaseun Edema3
Nigerian Electricity Regulatory Commission (NERC), Abuja, Nigeria
Shobodamola@gmail.com julianigemokhai@gmail.com, oluwaseun956@gmail.com
Abstract: This paper presents a process for
technical loss reduction in a practical
distribution network. The method proposed
aims to reduce real power losses present in the
network by reactive power compensation using
shunt capacitor placement. One of the objectives
of the study is to show the potential savings to be
realized in the network as a result of effecting
the proposed method. Furthermore an overview
of methods for non-technical loss reduction is
provided.
Keywords:
Network
Modelling,
simulation, Economic analysis.
Network
I.
INTRODUCTION
The distribution network is arguably the most
important cadre of the electric grid. Distribution
networks are tasked with supplying energy to
consumers through various distribution substations.
Due to the vast land area distribution networks are
required to service and the large number of
electrical equipment utilized in the network,
distribution networks incur heavy losses during the
process of conveying electrical energy from various
transmission substations to consumers.
A number of research works is being done on loss
reduction in distribution networks. [1] Proposed
loss reduction using optimum size and location of
distributed generation, an optimized algorithm
using sensitivity to permissible voltage limits at
buses was used. [2] Proposed loss reduction using
concurrent constraint programming, considering
both system operation constraints and load flow
constraints in loss reduction. [8] Proposed optimal
capacitor placement for loss reduction in
distribution networks using a number of
optimization techniques. [9] Performed loss
reduction by reducing feeder lengths in a network
by network restructuring.
This paper takes an introductory review into losses
in distribution networks of emerging economies. It
describes the various types of losses and points out
the impact of these losses on the economy of the
Distribution companies and the customer with this
key question in sight: How can losses in
distribution networks be reduced?
II.
LOSSES
NETWORKS
IN
DISTRIBUTION
Losses in distribution networks refer to the amount
of electricity injected into the distribution grid that
is not paid for by the user [1]. There are two major
classifications of losses in distribution networks,
namely;
 Technical Losses
 Non-Technical Losses [3].
Technical losses in power system are caused by the
physical properties of the components of the power
system. The most obvious example is the power
dissipated in transmission lines and transformers
due to internal electrical resistance [5].
Non-technical losses on the other hand are
losses caused by actions external to the power
supply/network and consist primarily of electricity
theft, non-payment by customers, errors in
accounting and record keeping [3].
These two categories of losses are merged to the
Aggregate Technical and Commercial (AT&C)
losses which is used by distribution companies as
an indicator of how much energy is being
distributed by the utility which is not billed for.
The distribution networks of emerging economies
are characterised by high energy losses caused by
 Poor network structure
 Ineffective billing & collection
systems
 Unbalanced load across Phases
 Over loaded lines
 Low Bus Voltages
Due to these factors high AT&C losses are
recorded. In 2014 the World Bank reported
ATC&C losses in the electrical network
(Transmission and Distribution inclusive) of
emerging economies like Brazil, India, Argentina,
Ghana, Botswana, and Mozambique as 16, 19, 15,
23, 11, and 15 respectively. These levels of losses
compared to losses from developed economies like
USA, United Kingdom, Germany (6, 9 and 8
respectively) [16] shows the gap in the efficiency in
the electrical sector that needs to be abridged
a.
IMPACT OF AT&C LOSSES ON
EMERGING ECONOMIES
A major consequence of high AT&C losses is high
cost of electricity. Utilities in the power sector in a
bid to compensate for the energy lost have high
tariff rates in comparison to quality of service.
Residential tariff rates in Nigeria average at 0.1077
$/kW compared to residential rates of 0.125$/kWh
in the US.
In emerging economies small and medium
enterprises with high demand for electricity
encounter barriers of high cost of and limited
access to electricity which poses an obstacle to
economic development. The problem of
minimizing distribution system losses has been a
major focus for researchers and utility companies
to the need for better quality of service and better
utilization of available energy.
b.
ATC&C LOSSES: NIGERIA AS A
CASE STUDY
The ATC&C loss of distribution companies in
Nigeria in 2018 is shown in the table below.
Table 1: ATC&C losses for Discos between
January & December 2018
During the period of Jan.-Dec. 2019, 72.7% of
Discos incurred ATC&C losses above 50% with an
average loss of 52.67% across Discos. Between the
period of Jan. 2018 & Dec. 2018 distribution
companies in Nigeria received a total of
52,635.52GWh of energy [17]. Considering the
ATC&C losses recorded during that period a total
of 28,712.68GWh of electricity was not billed for
during the period.
IV.
THEORETICAL
NETWORK
RESTRUCTURING
OF
DISTRIBUTION
NETWORKS
(TECHNICAL
LOSS
REDUCTION)
In our case study in loss reduction the distribution
network of Jos electricity distribution company is
taken into consideration with analysis done on the
distribution network fed by the Jos Transmission
S/S. The average length of various distribution
lines of the Jos distribution network is given in the
table below.
Table 2: average feeder length in Jos distribution
network
S/N FEEDER AVERAGE (km)
1
33KV
159.83
2
11KV
13.27
Feeders are modelled as below.
Figure 1
Where: R= Resistance of the feeder (Ω/km)
X= Reactance of the feeder (Ω/km)
B= Susceptance of the feeder (S/km)
In the above model capacitance can be ignored if
the lines are less than 80km long and Voltage
below 66kV [6]. Therefore the Short transmission
line model below is used for the feeders.
III.
LOSS REDUCTION TECHNIQUES
There are various methods of reducing losses in
distribution networks some of which are.
 Capacitor Placement
 Feeder Restructuring
a. CAPACITOR PLACEMENT
Shunt capacitor are placed in various locations to
maintain a desired voltage profile in buses&
feeders, correct power factor and reduce losses in
feeders and to the real power needed for
distribution [4].
b. FEEDER RESTRUCTURING
Feeder restructuring is targeted at realizing critical
areas of the network in consideration, Identify
feeders with excessive losses along their length,
and reconfigure the structure of the feeders by
length reduction [13].
Figure 2
Where: Vs= Voltage at Source
Vr= Voltage at Receiving end
Is= Source Current
Ir= Load Current
Table 3: Nominal and operational voltages on the
distribution system. [5]
S/N Nominal
Min.
Max
Max
Voltage
V
V
Loading(MW)
(kV)
(kV)
(kV)
1
33
31
34.98
20
2
3
11
0.4
10.45
0.376
11.55
0.424
5.9
-
The Nigerian Grid Code Specifications as above
was used to specify the voltage limits for buses in
the simulation software.
a.
NETWORK
MODELLING
AND
SIMULATION
The area of Jos distribution network supplied by
the Jos Transmission S/S network structure was
designed as below:
3.3
5
MIANGO
STATE LWC
0.0001
0.0238
0
0
5.3
5.7
5.3
36.7
27.3
5.3
RANTYA
RUKUBA RD
FOBUR
RUKUBA*
ANGLO JOS*
WEST OF
MINES_L
ARMY
BARACKS
FEEDER
TAFAWA
BALEWA
DOGON
DUTSE*
NASARAWA
CONGO
KATAKO
NARAGUTA
GADA BIU
JUTH*
UNIJOS(DED)
BAPTIST
BAUCHI RNG
RD
DILIMI
MURTALA
MOH
TORO*
NNPC FDR 8*
ZARIA RD*
ZARIA ROAD
TOWNSHIP
TOTAL =
0.0084
0.1087
0
2.503
1.659
0.0024
0
0.0002
0
0.0009
0.00006
0
0.0002
0
0.0298
0
2.464
0.0009
0.2602
0.007
0.0463
0.0317
0.0798
0.3356
0.0122
0.0016
0.0098
0.0004
0.0201
0.0228
0
0
10.5313
0.5487
0.058
0.0624
0.0159
18.8428
-0.2273
0.00009
3
6
28
Figure 3
The modelled systems load flow analysis was done
using Newton-Raphson Iterative method. Load
values in the simulation were determined by
analysis of the hourly load profiles of the various
feeders. The daily MYTO allocation for Jos Disco
was put into consideration in selecting the load
values for the load flow. The network loading was
determined based on feeder availability and power
drawn by the feeder closest to the MYTO
allocation for that period. Therefore the load values
used in the network corresponds to the feeder
loading on the 30th of August 2019 at 21:00.
Results are as below:
Figure 4
The losses in each feeder given in the table below
(33kV feeders are asterisked).
Table 4: loss profile of feeders in the network
LENGTH
FEEDER
P
Q
(km)
LOSS
LOSS
(MW)
(MVar)
4.9
LAMINGO_L
0
0
5.8
2.1
4.55
8.1
5.5
69
8.5
2
5
3.4
5.3
88.3
78
4.8
3.2
5.1
0.0001
0.0001
0.0001
0.0001
0
0
0
0.0001
0
-0.2243
Energy supplied to the network during simulation
was 93.077MW & 45.719MVar from the Network
Feeder. Given the simulation results Technical
losses account for 20.35% of real power input in
the network.
Loss reduction in the modelled network will be
done by installation of capacitor banks on specified
buses.
b. LOSS REDUCTION BY INSTALLATION
OF CAPACITOR BANKS
Determination of capacitor bank sizes and location
for the network is done using capacitor placement
tool in NEPLAN software. The tool minimizes the
MW loss in the system by reactive power
compensation using shunt capacitor placement at
buses. The capacitors are modelled to be turned off
if compensation isn’t required. The following
parameters were used in the calculation of the
capacitor bank size and placement.
Primary Bus: -X_JOS S/S
Subjective factors:
Maximum Number of Capacitor Installations: 16
Minimum Load Factor: 0.77
Maximum Load Factor: 1
Newton-Raphson Iterative method was used for the
iterative process. The tool is limited to radial
networks.
The result of the capacitor placement analysis using
NEPLAN capacitor placement tool is shown below.
Various capacitors were installed in the system; the
reactive power compensation is shown below.
Figure 5
The installation of the capacitors in the network
causes changes in the loss profile of the network.
This is shown in the result of the updated networks
Load flow as below.
c. FUZZY LOGIC TECHNIQUE FOR
CAPACITOR PLACEMENT
Siddiqui et al [8] introduced a Fuzzy logic based
technique for determination of suitable location
capacitor banks in a network. This method was
calculated by minimising the objective function
with the unit cost of capacitor banks included. The
objective function given as:
S=KP∆P+KE∆E-KCC
(1)
Where: KP= per unit cost of peak power cost
reduction
KE= per unit cost of energy loss reduction
KC= per unit cost of Capacitor
∆P= Peak power loss reduction
Analysis is pursuant to voltage constraints of the
system at the buses. The voltage p.u. constraints at
each voltage level between are the ranges below:
0.94Vnom ≤Vnom≤ 1.06Vnom
This method will be of interest to utilities as it
includes minimization of costs as well as losses.
d. ECONOMIC ANALYSIS OF CAPACITOR
INSTALLATION
To calculate the savings in the network caused by
loss reduction using capacitor bank installation, the
tariff of the network is estimated as a residential
user tariff R1 class. The amount of energy saved is
calculated according to Eq. (2) below
Esaved= T×Psaved-max×LSF ×1000
(2)
Where: Esaved= Energy savings (kWh)
T= Period of study (hourly)
LSF= Loss factor
Psaved-max= Maximum power
saved (MW)
Figure 6
Table 5: load flow results and savings
S/N
Power
input Technical
(MW)
Losses (MW)
Initial
Load 93.077
18.941
flow
Load
Flow 91.063
16.927
after
compensation
Savings
2.014
2.014
These results were obtained from the load flow
simulation before and after capacitor bank
placement. The power savings was calculated from
the differential between the power input and
technical losses of the simulation results before and
after capacitor placement. The power savings was
the sum of the power input savings and technical
losses savings calculated as
Power Savings2.01+ 2.014= 4.028 MW
LSF = 0.3 × LF + 0.7 × LF2
Where: LF= Load factor
(3)
The loss factor of the network was calculated as
0.646 [13]. Power savings was determined from
simulation results as 4.028MW. Given the loss
factor the energy savings was calculated as
2,602.088kWh.
Given a large amount of energy supplied was to
residential users, as such the tariff used to calculate
the savings was the residential tariff rate. The
residential class R1 tariff rate is set at N4 /kWh for
Jos Electricity Distribution Company [18].
Savings= Esaved × Tariff/kWh
(4)
The savings was calculated as N10, 408.35 for each
hour of operation. The cost of capacitor bank
installation is estimated between $10,000$15,000/MVar. Total installed capacitor bank
MVar is 30.40MVar
Max cost of installation= $456,000 at an exchange
rate of N361.50 to a dollar;
Cost of Investment= N198,884,400
Monthly savings= N10,408.35×24×30=N7,494,012
In calculating payback period which is an
approximate method for analysing economic
projects;
Payback period= Cost of investment / Savings
(4)
The maximum payback period is estimated at 27
months. Taking into consideration the analysis does
not consider future change in demand, equipment
maintenance, forced shutdown periods and other
variable circumstances. The reduction of network
losses will lead to an increase in the production
output of energy as a result the installed generating
capacity will produce more energy leading to a
greater savings in investment.
e.
NON
TECHNICAL
LOSS
REDUCTION
In Distribution networks the wide variety of factors
related to network equipment issues that contribute
to non-technical losses can be classified according
to the following main causes:
 Theft and fraud, due to illegal interference
with network assets;
 Measurement errors, due to inaccuracies
in measuring equipment. [9]
Theft is defined as any illegal abstraction of
electricity for use other than at premises where any
metering points or metering systems are registered
by a supplier. It can occur where an unauthorized
connection to the network is made or where illegal
re-connection takes place (e.g. after a formal
disconnection). It can also sometimes occur where
the connection process is incomplete [10].Fraud is
the illegal abstraction of electricity within the
boundary of a customer’s property [10]. All
metered customers purchase electricity from a
supplier and are associated to a registered meter
point. Fraud happens as a result of an illintentioned and illegal manipulation of the meter,
by tampering or bypassing the meter [11]. In both
cases, the purpose is to make the meter record a
lower amount of energy than is actually consumed
[12].Various papers have been written on the topic
of non technical loss reduction. Some suggested
methods to reduce these losses are listed below:



Development of optimum business models
for enhanced management [14].
Technology Management and deployment
[14].
Smart meters in identification of irregular
consumption [15].
VI.
CONCLUSION
This study investigated the viability of the chosen
method for a section of the Jos distribution
network. The technical losses were reduced using
capacitor banks placed at certain buses in the
network. The proposed method can be applied to
practical networks for feasibility analysis of loss
reduction projects in an electrical network. The
method implemented returned monthly energy
savings of N7, 494,012 with a payback period
below 27 months. The 415V voltage level was not
considered due to unavailability of network data.
Improper line joints (hotspots) along feeders which
contribute to technical losses were not considered.
In future works loss reduction will be done using
feeder length reduction, utilizing Geographic
Information System (GIS) data of the network and
optimal feeder lengths. The integration of mingrids into the network will also be considered
together with cost of investment & loss reduction
optimization.
ACKNOWLEDGMENTS
Special thanks to Engr. Jonathan Okoronkwo Engr.
Ovie Adjekpiyede and Engr. Mohammed Imam for
their essential contribution and guidance to the
completion of this study.
REFERENCES
[1] A. Anwar and H. R. Pota, “Loss reduction of
power distribution networks using optimum size
and
location
of
distributed
generation”,
Australasian Universities Power Engineering
Conference (AUPEC), Aug. 2013
[2] N.G. Caciedo, C.A. Lozano, J.F. Diaz, C.
Rueda, G. Gutierrez, C. Olarte, “ Loss reduction in
distribution networks using concurrent constraint
programming”, Probabilistic Methods Applied to
Power Systems (PMAPS),Vol. 4,
[3] L.M. Adesina, “Determination of Power
Systems losses in Nigerian Distribution Networks”,
International Journal of Engineering and
Technology (IJET), Vol.6, No.9, Sept. 2016.
[4] P. Varilone, G. Carpinelli, A. Abur, “Capacitor
placement in unbalanced power systems”, in
Power Systems Computation Conference, Sevilla,
Spain, 2002, pp. 1-6.
[5] J.P Navani, N.K Sharma, & Sonal Sapra
“Technical and Non-Technical Losses in Power
System and Its Economic Consequence in Indian
Economy” International Journal of Electronics and
Computer Science Engineering ISSN: 2277-1956
[6] D. Das, “Characteristics and Performance of
Transmission Lines”, in Electrical Power Systems,
New Age International (P) Ltd., Publishers, 2006,
pp. 124-125.
[16] The world bank: “Electric power transmission
and distribution losses (% of output)” viewed 24
October 2019 <https://data.worldbank.org ›
indicator ›> EG.ELC.LOSS.ZS
[7] “Distribution Code for the Nigerian Electricity
Distribution System, 2015”, Nigerian Electricity
Regulatory Commission (NERC), Abuja, Nigeria,
2015, p. 34.
[17] Nigerian electricity regulatory commission:
“Industry statistics for ATC&C losses” viewed 28
October 2019
<https://nerc.gov.ng/index.php/library/indust
[8] A.S. Siddiqui, M. F. Rahman, “Optimal
Capacitor Placement to Reduce Losses in
Distribution System”, World Scientific and
Engineering Academy and Society Transactions on
Power Systems (WSEAS), Jan. 2012.
[9] A. Beutel et al, “Reduction of Technical and
Non-Technical Losses in Distribution Networks”,
International
Conference
on
Electricity
Distribution (CIRED), Nov. 2017.
[10] Treatment of losses by network operators –
Conclusions Paper Ref: E08-ENM-04-03c
Available:https://www.ceer.eu/documents/104400//-/6f455336-d8c8-aa6f-36d3-fe5264caf57d
[11] W. Heckmann, et al., “Detailed analysis of
network losses in a million customer distribution
grid with high penetration of distributed
generation” 22nd International Conference on
Electricity Distribution (CIRED), 10-13 June 2013,
Stockholm, Netherlands, 2013.
Available:http://www.cired.net/publications/cired2
013/pdfs/CIRED2013_1478_final.pdf
[12] M. Clemence, R. Coccioni, A. Glatingy, “How
Utility Electrical Distribution Networks can Save
Energy in the Smart Grid Era”,
Available:http://download.schneiderelectric.com/fil
es?p_enDocType=White+Paper&p_File_Id=17248
47349&p_File_Name=998-2095-11- 2513AR0.pdf&p_Reference=998-2095-11-2513AR0_EN
[13] M.B. Sadati et al., "Decreasing Length of
Distribution Network for Loss Reduction:
Technical and Economical Analysis", Research
Journal of Applied Sciences Engineering and
Technology, vol. 4, April 2012.
[14] I.E. Davidson, “Non-technical losses in power
networks-analysis and impact measurement” Dept
Elect. Elect. Eng., Natal Univ., Durban, 2002.
[15] I. Bula, V. Hoxha, M. Shala, E. Hajrizi,
“Minimizing non-technical losses with point-topoint measurement of voltage drop between
“SMART” meters”, International Federation of
Automated Control (IFAC), 2016 pp.2405-896
ry-statistics/distribution/119-atc-c-losses>
[18] S.M Bagher, Y.A Mohammad & Takami, Mir.
“Decreasing Length of Distribution Network for
Loss Reduction: Technical and Economical
Analysis”. Research Journal of Applied Scientific,
Engineering and Technology. 4 2012