INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY (IJEET)

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1 INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY (IJEET) ISSN (Print) ISSN (Online) Volume 5, Issue 8, August (2014), pp IAEME: Journal Impact Factor (2014): (Calculated by GISI) 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. Ananthapadmanabha 2, & A. D. Kulkarni 2 1 Research Scholar, Department of EEE, The National Institute of Engineering, Mysore, India 2 Professor, Department of EEE, The National Institute of Engineering, Mysore, India 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 units are determined with the obective of power loss reduction and voltage profile improvement. Firstly, the DG unit is placed for loss minimization obective 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 s, 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 maor technical benefits are reduction of line losses, voltage profile improvement, increased overall energy efficiency, enhanced system reliability and security, relieved T&D congestion. The maor 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 76

2 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. Chiradea 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 obective. Maruthi Prasanna. H. A. et. Al [12] have attempted in combining the tail end node voltage improvement along with the power loss minimization obective 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]-[]. Some authors have tried DG allocation problem as multi obective optimization in which they have considered voltage profile improvement as additional obective along with power loss minimization [14] & []. 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. 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 []. Though many conventional models and techniques are used for this purpose but it becomes a cumbersome task as the complexity of the system increases. [-20] Linear and nonlinear programming methods have been proposed earlier to solve the placement problem. s 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 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 obective of minimizing the power loss and voltage deviation. In this paper, an analytical approach for optimal placement of combined DG and units are determined with the obective of power loss reduction and voltage profile improvement. Firstly, the DG unit is placed for loss minimization obective 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. 2. PROBLEM FORMULATION In order to determine benefits from combined DG and 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 inection at all buses can be calculated using the following equation (1) [31] Where, PL = N N [ α i ( Pi P + QiQ ) + β i ( Qi P Pi Q )] i= 1 = 1 ri α i = V V i cos( δ i δ ) ; ri β i = V V i sin( δ i δ ) ; PL is the exact loss of the distribution system; r i is the resistance between bus i and bus ; V i and V is the voltage magnitude of buses i and respectively; δ i is the voltage angle at bus i; δ is the voltage angle at bus ; P i and Q i active and reactive power inection at bus i ; P and Q is the active and reactive power inection at bus. The Power Loss Reduction Index of i th bus when DG is connected to that bus is given by, PL( i) PLRI ( i) = (2) PL( base) Where, PL(i) is the distribution system real power loss when DG is connected to the i th 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, VDI N = b i= 1 78 (1) spec 2 ( V i V ) (3) Where, V i spec is the Voltage specified in pu. In this paper, it is taken as 1 pu; V i is the Voltage at the i th 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). i

4 The Voltage Deviation Reduction Index (VDRI) of i th bus when capacitor is connected to that bus is given by, VDI ( i) VDRI ( i) = VDI( base) (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 obective of the optimal DG placement is to achieve minimum power loss in the distribution system with DG and the obective of the optimal capacitor placement is to achieve minimum voltage deviation in the distribution system subect to the following constraints: Line load ability limit: P line( i, ) < Pline ( i, ) max (5) Where, P line(i,) is the line flow between nodes i and ; P line(i,)max is the maximum line flow capacity of line between nodes i and ; Bus Voltage limit: V < Vi < (6) min V max Where, V min is the minimum acceptable voltage at any bus; V max is the maximum allowable voltage at any bus; V i 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 inecting real power in the distribution system and to use capacitor as a way for voltage deviation reduction by inecting reactive power in the distribution system. The overall procedure of determining optimal locations for combined DG and capacitor is shown in Fig 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 kw and base case VDI is 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 is to be placed. Scenario-2 in which 2 DG units of unity pf & 2 s are to be placed. Scenario-3 in which 3 DG units of unity pf & 3 s are to be placed. 79

5 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 80

6 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 Capacity in KW Table 1: Optimal Placement Results of IEEE 33 bus RDS for Scenario-1 Base Case After Placement of Combined DG and DG Parameters Loss Power Power Optimal Capacity Optimal VDI in Reducti VDI in Loss in Loss in Location in KVAr Location pu on in pu KW KW Kw VDI Reduction in Pu Capacity in KW Capacity in KW Table 2: Optimal Placement Results of IEEE 33 bus RDS for Scenario-2 Base Case After Placement of Combined DG and DG Parameters Power Power Loss Optimal Capacity Optimal VDI in VDI in Loss in Loss in Reductio Location in KVAr Location pu pu KW KW n in Kw VDI Reduction in Pu Table 3: Optimal Placement Results of IEEE 33 bus RDS for Scenario-3 Base Case After Placement of Combined DG and DG Parameters Loss Power Power Optimal Capacity Optimal VDI in Reducti VDI in Loss in Loss in Location in KVAr Location pu on in pu KW KW Kw VDI Reduction in Pu

8 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): [2] P. Chiradea and R. Ramkumar. An approach to quantify the technical benefits of distributed generation, IEEE Transaction on Energy Conversion. 2004, 19 (4): [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 , [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): [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, 00 08, April [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): [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: [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 [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,

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