An analytical approach for optimal placement of combined dg and capacitor in distribution feeder 2

INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING &
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014
TECHNOLOGY (IJEET)
17 – 19, July 2014, Mysore, Karnataka, India
ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online)
Volume 5, Issue 8, August (2014), pp. 76-85
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IJEET
© I A E M E
AN ANALYTICAL APPROACH FOR OPTIMAL PLACEMENT OF
COMBINED DG AND CAPACITOR IN DISTRIBUTION FEEDER
Maruthi Prasanna. H. A.1,*, Veeresha. A. G.1, T. Ananthapadmanabha2, & A. D. Kulkarni2
1Research Scholar, Department of EEE, The National Institute of Engineering, Mysore, India
2Professor, Department of EEE, The National Institute of Engineering, Mysore, India
76
ABSTRACT
In the present deregulated environment, optimal placement of Distributed Generation (DG)
and shunt capacitor in the distribution network plays a vital role in distribution system planning. In
this paper, an analytical approach for optimal placement of combined DG and Capacitor units are
determined with the objective of power loss reduction and voltage profile improvement. Firstly, the
DG unit is placed for loss minimization objective and then the capacitor unit is placed for voltage
deviation minimization. Three scenarios of DG and capacitor combinations are tried out. To validate
the proposed analytical approach, it has been applied to IEEE 33-bus radial distribution systems in
MATLAB R2009b.
Keywords: Distributed Generation, Shunt Capacitors, Distribution System, Power loss reduction,
voltage deviation reduction, Load flow, optimal placement.
1. INTRODUCTION
Distributed generation is an electric power source connected directly to the distribution
network or on the customer site of the meter [1].
Most of the benefits of employing DG units in existing distribution networks have both
economic and technical implications and they are interrelated. The major technical benefits are
reduction of line losses, voltage profile improvement, increased overall energy efficiency, enhanced
system reliability and security, relieved T&D congestion. The major economical benefits are
deferred investments for upgrades of facilities, reduced O&M costs of some DG technologies,
reduced fuel costs due to increased overall efficiency, lower operating costs due to peak shaving and
increased security for critical loads [2]. For the known size of DG, in order to achieve the
aforementioned benefits, DG location has to be optimized.
If DG units are integrated at non-optimal locations, the power losses increase, resulting in
increased cost of energy, voltage increase at the end of a feeder, demand supply unbalance in

a fault condition, power quality decline and reduction of reliability levels [3]. Hence identifying
location for connecting DG units is a crucial part of DG planning.
In literature, there are a number of approaches developed for placement and sizing of DG
units in distribution system. Chiradeja and Ramkumar [2] presented a general approach and set of
indices to assess and quantify the technical benefits of DG in terms of voltage profile improvement,
line loss reduction and environmental impact reduction.
Khan and Choudry [4] developed an algorithm based on analytical approach to improve the
voltage profile and to reduce the power loss under randomly distributed load conditions with low
power factor for single DG as well as multi DG systems.
Hung et al. [5] used an improved analytical method for identification of the best location and
optimal power factor for placing multiple DGs to achieve loss reduction in large scale primary
distribution networks.
Kamel and Karmanshahi [6] proposed an algorithm for optimal sizing and siting of DGs at
any bus in the distribution system to minimize losses and found that the total losses in the
distribution network would reduce by nearly 85%, if DGs were located at the optimal locations with
optimal sizes.
Dr. T. Ananthapadmanabha et. al [7] proposed an analytical approach for optimal allocation
of a DG unit in radial distribution system, in which the optimal location of DG is found out by using
TENVD index concerned with the improvement of tail end node voltages and optimal size of DG is
found out for loss minimization.
The genetic algorithm (GA) is an optimization and search technique based on the principles
of genetics and natural selection. Application of GA to determine optimal allocation of DG proved
to be an efficient technique and many authors has succeeded in applying it [8]-[12]. Mithulananthan
et. al [8] have tried it taking power loss minimization alone as objective. Maruthi Prasanna. H. A.
et. Al [12] have attempted in combining the tail end node voltage improvement along with the power
loss minimization objective in optimally allocating a DG unit in a radial distribution feeder using
GA.
Many authors also tried particle swarm optimization (PSO) for DG optimization problem
[13]-[15]. Some authors have tried DG allocation problem as multi objective optimization in which
they have considered voltage profile improvement as additional objective along with power loss
minimization [14] & [15].
Installation of shunt capacitors on distribution networks is essential for power flow control,
improving system stability, power factor correction, voltage profile management and losses
minimization. Therefore it is important to find optimal location and sizes of capacitors required to
minimize feeder losses. The solution techniques for loss minimization can be classified into four
categories: Analytical, numerical programming, heuristics and artificial intelligence based. Capacitor
allocation problem is a well researched topic and all earlier approached differ from each other either
in their problem formulation or problem solution methods employed [16].
In large distribution networks it is very difficult to predict the optimum size and location of
capacitor which finally results not only in reducing losses but also improves the overall voltage
profile [17]. Though many conventional models and techniques are used for this purpose but it
becomes a cumbersome task as the complexity of the system increases. [18-20] Linear and nonlinear
programming methods have been proposed earlier to solve the placement problem.
Capacitors are commonly used to provide reactive power support in distribution systems. The
amount of reactive compensation provided is very much related to the placement of capacitors in
distribution feeders. The determination of the location, size, number and type of capacitors to be
placed is of great significance, as it reduces power and energy losses, increases the available capacity
of the feeders and improves the feeder voltage profile. Numerous methods for solving this problem
in view of minimizing losses have been suggested in the literature [21–27].
77

In literature, very few attempts were seen [28-30] about the optimal placement of combined
DG and capacitor. The present paper considers the optimal placement of DG and capacitor with the
key objective of minimizing the power loss and voltage deviation. In this paper, an analytical
approach for optimal placement of combined DG and Capacitor units are determined with the
objective of power loss reduction and voltage profile improvement. Firstly, the DG unit is placed for
loss minimization objective and then the capacitor unit is placed for voltage deviation minimization.
Three scenarios of DG and capacitor combinations are tried out. To validate the proposed analytical
approach, it has been applied to IEEE 33-bus radial distribution systems in MATLAB R2009b.
The organization of this paper is as follows; section 2 defines the problem, section 3 defines
the proposed methodology, Section 4 discusses the results obtained by the proposed method and
finally section 5 concludes the paper.
ij i j i j ij i j i j PL P P Q Q Q P PQ
b = d −d
PLRI i = (2)
spec
i VDI V V
spec is the Voltage specified in pu. In this paper, it is taken as 1 pu; Vi is the Voltage at the
78
2. PROBLEM FORMULATION
In order to determine benefits from combined DG and Capacitor integration, two sets of indices
are proposed in this paper Viz PLRI and VDRI. They are explained below.
2.1 Power Loss Reduction Index (PLRI)
The total real power loss in a distribution system with ‘N’ buses as a function of active and reactive
power injection at all buses can be calculated using the following equation (1) [31]
N
[ ]
= =
= + + −
i
N
1 j
1
a ( ) b ( )
(1)
Where,
a = d −d
cos( ) i j
r
ij
ij V V
i j
;
sin( ) i j
r
ij
ij V V
i j
;
PL is the exact loss of the distribution system; rijis the resistance between bus i and bus j; Vi and
Vj is the voltage magnitude of buses i and j respectively; i is the voltage angle at bus i; j is the
voltage angle at bus j; Pi and Qi active and reactive power injection at bus i ; Pj and Qj is the active
and reactive power injection at bus j.
The Power Loss Reduction Index of ith bus when DG is connected to that bus is given by,
( )
PL i
( )
( )
PL base
Where, PL(i) is the distribution system real power loss when DG is connected to the ith bus; PL(base)
is the distribution system real power loss without DG connection;
2.2 Voltage Deviation Reduction Index (VDRI)
The voltage deviation index (VDI) of the distribution system is given by,
b N

=
= −
i
i
1
2 ( ) (3)
Where, Vi
ith bus in pu.
The VDI is a measure of the voltage profile of the distribution system and it indicates how
the voltage values of the distribution nodes are nearer to the specified voltage. It is expected that this
value should be nearer to zero, so that all the nodes of the distribution system will be having voltage
nearer to the specified voltage (1 pu).

The Voltage Deviation Reduction Index (VDRI) of ith bus when capacitor is connected to that bus
VDI i
79
is given by,
( )
( )
( )
VDI base
VDRI i =
(4)
Where, VDI (i) is the voltage deviation index of distribution system when capacitor is
connected to ith bus; VDI (base) is the voltage deviation index of the distribution system without
capacitor connection.
The objective of the optimal DG placement is to achieve minimum power loss in the
distribution system with DG and the objective of the optimal capacitor placement is to achieve
minimum voltage deviation in the distribution system subject to the following constraints:
• Line load ability limit:
line(i, j ) line(i, j )max P P
(5)
Where, Pline(i,j) is the line flow between nodes i and j; Pline(i,j)max is the maximum line flow capacity of
line between nodes i and j;
• Bus Voltage limit:
min max V V V i (6)
Where, Vmin is the minimum acceptable voltage at any bus; Vmax is the maximum allowable voltage
at any bus; Vi is the voltage of any bus i.
3. PROBLEM FORMULATION
In this paper, it is proposed to determine optimal location for both DG and capacitor units.
The optimal location for DG unit is located such that it offers maximum power loss reduction and the
optimal location for capacitor unit is decided such that it offers maximum voltage deviation
reduction. Firstly, the DG unit is placed at the optimal location decided for loss reduction and then
the capacitor is placed for voltage deviation reduction. The purpose of such a procedure is to use DG
as a way for power loss reduction by injecting real power in the distribution system and to use
capacitor as a way for voltage deviation reduction by injecting reactive power in the distribution
system. The overall procedure of determining optimal locations for combined DG and capacitor is
shown in Fig 1.
4. SIMULATION RESULTS
The proposed methodology using FEM is tested on IEEE-33bus Radial Distribution System
(RDS) [32] (Fig 2) having following characteristics: Number of buses=33; Number of lines=32;
Slack Bus no=1; Base Voltage=12.66KV; Base MVA=100 MVA;
The forward backward method of load flow (FBLF) is employed in this paper, whose details are
given in [33]. Initially, the base case FBLF is run for the IEEE 33bus RDS and the base case voltage
profile is shown in Figure 3. The base case real power loss is 210.97 kw and base case VDI is 0.1338
pu.
The test system is simulated in MATLAB R2009b the proposed methodology has been
tested, whose results are as shown below. In this paper, 3 scenarios of optimal DG placement are
carried out:
Scenario-1 in which a 1DG of unity pf 1 Capacitor is to be placed.
Scenario-2 in which 2 DG units of unity pf 2 Capacitors are to be placed.
Scenario-3 in which 3 DG units of unity pf 3 Capacitors are to be placed.

The procedure of determining optimal location for combined DG and capacitor units is explained in
Figure 1. In each scenario, the DG sizes of available sizes and the practically available capacitor
sizes are considered. The details of available capacitors can be found in [34]. The results of each
scenario are tabulated in Table 1, Table 2 and Table 3 respectively.
Figure 1: Flowchart for Optimal Placement of Combined DG and Capacitor
80

Figure 2. Single line diagram of IEEE-33 bus RDS
Figure 3. Base Case Voltage Profile of IEEE-33 bus RDS
In each scenario, the power loss after placement is compared with the base case power loss
and loss reduction in Kw is tabulated. Similarly the VDI after placement is compared with base case
VDI and VDI reduction in pu is tabulated.
From each scenario, it is very clear that the proposed methodology yields maximum power
loss reduction and maximum voltage deviation reduction.
81

Table 1: Optimal Placement Results of IEEE 33 bus RDS for Scenario-1
82
DG Capacitor
Base Case
Parameters
After Placement of Combined DG and
Capacitor
Capacity
in KW
Optimal
Location
Capacity
in KVAr
Optimal
Location
Power
Loss in
KW
VDI in
pu
Power
Loss in
KW
Loss
Reducti
on in
Kw
VDI in
pu
VDI
Reduction
in Pu
150 18 150 18 210.97 0.1338 177.31 33.66 0.1008 0.0330
300 17 300 18 210.97 0.1338 153.38 57.59 0.0754 0.0584
450 15 450 18 210.97 0.1338 137.05 73.92 0.0569 0.0769
600 14 600 17 210.97 0.1338 125.66 85.31 0.0430 0.0908
900 13 900 15 210.97 0.1338 112.53 98.44 0.0264 0.1074
1200 10 1200 33 210.97 0.1338 82.69 128.28 0.0169 0.1169
DG Capacitor
Base Case
Parameters
Capacitor
Capacity
in KW
Optimal
Location
Capacity
in KVAr
Optimal
Location
Power
Loss in
KW
VDI in
pu
Power
Loss in
KW
Loss
Reductio
n in Kw
VDI in
pu
VDI
Reduction
in Pu
150
18
15
150
18
18
210.97 0.1338 153.10 57.87 0.0758 0.058
300
17
32
300
18
17
210.97 0.1338 121.67 89.3 0.0447 0.0891
450
15
32
450
18
15
210.97 0.1338 103.163 107.84 0.0236 0.1102
600
14
31
600
17
33
210.97 0.1338 57.05 153.92 0.0108 0.123
900
13
30
900
15
33
210.97 0.1338 50.34 160.63 0.0034 0.1304
DG Capacitor
Base Case
Parameters
Capacitor
Capacity
in KW
Optimal
Location
Capacity
in KVAr
Optimal
Location
Power
Loss in
KW
VDI in
pu
Power
Loss in
KW
Loss
Reducti
on in
Kw
VDI in
pu
VDI
Reduction
in Pu
150
18
15
32
150
18
18
17
210.97 0.1338 134.24 76.73 0.0590 0.0748
300
17
32
13
300
18
17
33
210.97 0.1338 81.82 129.15 0.0231 0.1107
450
15
32
9
450
18
15
33
210.97 0.1338 62.50 148.47 0.0080 0.1258
600
14
31
7
600
17
33
30
210.97 0.1338 37.06 173.91 0.0017 0.1321

83
5. CONCLUSION
An analytical approach for determining the optimal locations for combined DG and capacitor
units is presented in this paper. The optimal location of DG is decided such that it provides
maximum real power loss reduction and the optimal location of capacitor is decided such that it
provides maximum voltage deviation reduction. The proposed methodology is validated by applying
it to IEEE 33 bus Radial Distribution system with three different scenarios. In each scenario, it is
found that the proposed methodology has the capability of simultaneously reducing the real power
losses in the distribution system with voltage profile improvement. The proposed method can be
used as a tool by utilities in distribution system planning in deregulated environment.
ACKNOWLEDGEMENT
The authors Maruthi Prasanna. H. A. and Veeresha. A. G. acknowledge the Technical
Education Quality Improvement Programme (TEQIP)-II of All India Council for Technical
Education (AICTE), New Delhi, India and Dr. G. L. Shekar, Principal, NIE, Mysore for providing
financial assistance for carrying out this research work.
The author Maruthi Prasanna. H. A. also acknowledge the Karntaka Power Transmission
Corporation Limited (KPTCL), Karnataka for providing leave to pursue Integrated M.Tech + PhD
programme.
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