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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 
© IAEME: www.iaeme.com/IJEET.asp 
Journal Impact Factor (2014): 6.8310 (Calculated by GISI) 
www.jifactor.com 
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
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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).
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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.
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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 
Table 2: Optimal Placement Results of IEEE 33 bus RDS for Scenario-2 
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 
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 
Table 3: Optimal Placement Results of IEEE 33 bus RDS for Scenario-3 
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 
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
Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 
17 – 19, July 2014, Mysore, Karnataka, India 
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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85

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

  • 1. 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 © IAEME: www.iaeme.com/IJEET.asp Journal Impact Factor (2014): 6.8310 (Calculated by GISI) www.jifactor.com 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
  • 2. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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
  • 3. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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).
  • 4. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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.
  • 5. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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
  • 6. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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
  • 7. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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 Table 2: Optimal Placement Results of IEEE 33 bus RDS for Scenario-2 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 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 Table 3: Optimal Placement Results of IEEE 33 bus RDS for Scenario-3 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 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
  • 8. Proceedings of the 2nd International Conference on Current Trends in Engineering and Management ICCTEM -2014 17 – 19, July 2014, Mysore, Karnataka, India 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. REFERENCES [1] T. Ackermann, G. Anderson and L. Soder, “Distributed generation: a definition”, Electrical Power System Research. 2001, 57 (3): 195-204. [2] P. Chiradeja and R. Ramkumar. “An approach to quantify the technical benefits of distributed generation”, IEEE Transaction on Energy Conversion. 2004, 19 (4): 764-773. [3] Augusto C Rueda-Medina, John F Franco, Marcos J Rider, Antonio Padilha-Feltrin and Rubén Romero, “A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems”, Electric Power Systems Research, Vol.97, pp.133-143, 2013. [4] H. Khan and M.A. Choudhry, “Implementation of distributed generation algorithm for performance enhancement of distribution feeder under extreme load growth”, International Journal of Electrical Power and Energy Systems. 2010, 32 (9): 985-997. [5] D.Q. Hung, N. Mithulanathan and R.C. Bansal, “Multiple distributed generators placement in primary distribution networks for loss reduction”, IEEE Transactions on Industrial Electronics, Vol 60 , Issue 4, 1700 – 1708, April 2013. [6] R.M. Kamel and B. Karmanshahi, “Optimal size and location of DGs for minimizing power losses in a primary distribution network”, Transaction on Computer Science and Electrical and Electronics Engineering. 2009, 16 (2): 137-144. [7] Dr. T. Ananthapadmanabha, Maruthi Prasanna. H. A., Veeresha. A. G. and Likith Kumar. M. V., “A new simplified approach for optimum allocation of a distributed generation unit in the distribution network for voltage improvement and loss minimization”, International Journal of Electrical Engineering Technology (IJEET), Volume 4, Issue 2 (2013), pages: 165-178. [8] Mithulananthan, T. Oo, L. Van Phu, “Distributed generator placement in power distribution system using genetic algorithm to reduce losses”, Thammasat International Journal of Science and Technology, Vol. 9, No. 3, July-September 2004. [9] M. Sedighizadeh, and A. Rezazadeh, “Using Genetic Algorithm for Distributed Generation Allocation to Reduce Losses and Improve Voltage Profile”, World Academy of Science, Engineering and Technology, 37, 2008, 251-256.
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