International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) ...
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Artificial bee colony algorithm based approach for capacitor allocation in un

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Artificial bee colony algorithm based approach for capacitor allocation in un

  1. 1. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 67 ARTIFICIAL BEE COLONY ALGORITHM BASED APPROACH FOR CAPACITOR ALLOCATION IN UNBALANCED RADIAL DISTRIBUTION SYSTEMS Dr.K.Ravichandrudu1 , G.Jyothi 2 , Mr.P.Yohan Babu3 , Mr.G.V.P.Anjaneyulu4 1,2,3 Krishnaveni Engineering College For Women, Narasaraopet, Guntur, AP, India. 4 Reaserch scholar SVU College of engineering, S.V.U., Tirupathi. ABSTRACT This paper presents an artificial bee colony method for optimal sizing of capacitors at optimal locations in unbalanced radial distribution systems. The objective function formulated includes the energy cost, capacitor installation cost and purchase cost. So that the fitness function is to maximize the net saving. Most conventional optimization techniques are in capable to solve this hard combinatorial problem with set of operating conditions where as artificial bee colony (ABC) algorithm is very suitable. This method is executed on a typical 25-bus and 37-bus unbalanced radial distribution systems (URDS) and yields efficiency in reduction of power losses and improvement of net saving. Keywords: Power Loss Indices, Capacitor banks, Loss Minimization, Unbalanced Radial Distribution Systems, Artificial Bee Colony method, Net saving. 1. INTRODUCTION As the cost of new power plant construction has increased, the electric power industry is making every effort to reduce the growth of electricity demand. Since a substantial amount of generated power is being wasted as losses, reduction in losses has been recognized as a viable option to eliminate to some degree the need for unnecessary additional generating capacity. It is acknowledged that much of this power loss occurs in the distribution system. In past, a lot of work has been carried out in the area of reactive power compensation for distribution networks [1-3]. Voltage improvement and power loss reduction by capacitor placement is analyzed in [4]. Sundhararajan and Pahwa et al. used genetic algorithm for obtaining the optimum values of shunt capacitors in [5]. They have treated the capacitors as constant reactive power load at that particular bus. T.S. Abdul salma et al. proposed a heuristic technique, which brings about the identification of INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY (IJEET) ISSN 0976 – 6545(Print) ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), pp. 67-73 © IAEME: www.iaeme.com/ijeet.asp Journal Impact Factor (2013): 5.5028 (Calculated by GISI) www.jifactor.com IJEET © I A E M E
  2. 2. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 68 the sensitive buses that have a very large impact on reducing the losses in the distribution systems [6]. C.S. Chen et al. developed a systematic method of optimally locating and sizing of the shunt capacitors compensation on distribution feeders by taking into account the mutual coupling effect among phase conductors [7]. The capacitor placement and sizing problem is a nonlinear integer optimization problem, with locations and ratings of shunt capacitors being discrete values. Particle swarm optimization based approach for capacitor placement for loss reduction is analyzed in [8]. In this paper the artificial bee colony method is proposed for finding optimal size of capacitor in unbalanced radial distribution system for improving the net saving which is formulated as the difference between the energy saving obtained by loss reduction and the cost of capacitor installation, purchase and operation. 2. PROBLEM FORMULATION The objective function formulated includes the energy cost, capacitor installation cost and purchase cost, so that the fitness function is to be maximized for the net savings function (F) by placing the optimal size of the capacitor. The objective function can be expressed as: ' 1 1 1 n n nc abc abc loss j loss j j j j F Max EC P P T a IC nc CC CB = = =       = × − × − × × + ×           ∑ ∑ ∑ (1) Where, EC is energy Cost in Rs/kWh; T is time Period in hours; n is number of buses abc loss jP is the total active power loss before capacitor placement ' abc loss jP is the total active power loss after capacitor placement a is the depreciation factor ; IC is the installation cost; nc is the number of capacitor locations ; CC is the cost of the three phase capacitor CB is the capacitor bank rating in kVAr. Subjected to inequality constraints are i) max0 CB CB≤ ≤ Where max 20% loadCB of Q= ii) The bus voltage magnitudes are to be kept within acceptable operating limits throughout the optimization process. That is ± 5% of the nominal voltage value. ≥ ≥ sys sys sys V V Vmax i min 3. ILLUSTRATION OF LOCATION OF CAPACITORS The candidate bus identification method for capacitor placement is explained with 37 bus URDS .The line and the load data of this system is given in [9]. After performing the base case load flows, total active power loss of system is 85.6746 kW. After compensating the reactive power injection at each bus in all the phases equal to local reactive load of the system at that particular bus, perform the load flows as explained in [7] and record the total active power loss and loss reduction of the system. This procedure is repeated for all remaining buses except source bus. The power loss indices (PLI) are calculated as [ ] [ ]( ) ( ) . . . Loss reduction i Min reduction PLI i Max reduction Min reduction − = − (2)
  3. 3. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 69 Fig. 1: Power loss indices of 37 bus unbalanced radial distribution system The most suitable buses for the capacitor placement are chosen based on the condition that PLI must be greater than PLI tolerance value, it should be lies in between ‘0’ and ‘1’. The tolerance value for a chosen system is selected by experimenting with different values in descending order of the PLI limits. The best value of the tolerance value gives the highest profit and satisfies the system constraints. Fig.1 shows power loss index vs bus number for 37 bus URDS. From experimentation the best value of PLI tolerance is set as 0.6. It is concluded that buses 2, 10, 11, 33, 37 are the best candidate buses for the capacitor placement. Assume capacitor at candidate buses with size varying the integer steps of the standard size capacitors (50 kVAr per phase). 4. ARTIFICIAL BEE COLONY METHOD Artificial Bee Colony (ABC) is one of the most recently defined method by Dervis Karaboga in 2005, motivated by the intelligent behavior of honeybees. ABC as an optimization tool provides a population based search procedure in which individuals called food positions are modified by the artificial bees with time and the bee’s aim is to discover the places of food sources with high nectar amount and finally the one with the highest nectar. In this method [10], [11], the colony of artificial bees consists of three groups of bees: employed bees, onlookers and scouts. First half of the colony consists of the employed artificial bees and the second half includes the onlookers. For every food source, there is only one employed bee. In other words, the number of employed bees is equal to the number of food sources around the hive. The employed bee whose food source has been abandoned becomes a scout [12]. Thus, ABC system combines local search carried out by employed and onlooker bees, and global search managed by onlookers and scouts, attempting to balance exploration and exploitation process [13]. This ABC method is used for finding optimal size of capacitors at optimal locations. 5. RESULTS AND ANALYSIS To check the validity of the proposed ABC method, 25 bus and 37 bus unbalanced radial distribution systems have been considered. In addition, the results of these systems were compared with those obtained via existing PSO method [8]. The proposed ABC method results were obtained after carrying out 100 independent runs. Energy saving cost has been calculated as the difference of energy loss cost without capacitor and with capacitor. The net saving has been calculated as the difference of energy saving cost and the capacitor installation and purchase cost. The rate of energy loss cost has been considered as Rs. 3 per 0 0.2 0.4 0.6 0.8 1 1.2 0 10 20 30 40 Bus number Power Loss Indices (PLI)
  4. 4. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 70 kWh, depreciation factor is 0.2, installation cost Rs. 50,000 and the cost of the three phase capacitor is Rs. 200 for the cost benefit analysis [14]. The Control parameters of existing and proposed methods of both test systems are given in Table 1. Table 1: Control parameters of existing and proposed methods for both test systems Existing method [8] Proposed method Number of generations=100; Population size=20 Wmax=0.9; Wmin=0.2 ; c1 = 2; c2 = 2 MaxCycle=100 Colony size=40 1) Example: 1 The 37 bus unbalanced radial distribution system is considered as first example for testing the efficacy of proposed method. In order to study the effect of capacitor placement at multiple locations, an attempt was made to place capacitor at more than one location. The locations of capacitor placement is obtained as discussed in section 3 i.e., candidate buses for the placement of capacitors. The optimal sizes of capacitors are obtained by proposed and existing optimization methods. Summary of test results of 37 bus unbalanced radial distribution system is given in Table 2. The net saving obtained by existing and proposed methods are Rs. 3,09,007 and Rs. 3,15,304 for the total size of capacitor of 300 kVAr and 250 kVAr respectively. From Table 2, it is observed that the minimum voltages in phases A, B and C are improved from 0.9497, 0.9578 and 0.9445 p.u to 0.9622, 0.9712 and 0.9598 p.u by existing method, 0.9625, 0.9718 and 0.9601 p.u by proposed method respectively. Also observed that the active power loss in phases of A, B and C is reduced from 31.56, 23.67 and 30.44 kW to 25.47, 20.41 and 24.99 kW by existing method and 25.23, 20.36 and 24.81 kW by proposed method respectively.The reactive power loss in phases A, B and C is reduced from 24.01, 22.32 and 29.19 kVAr to 20.41, 18.83 and 24.65 kVAr by existing method and 20.21, 18.78 and 24.49 kVAr by proposed method respectively. From table 2 it is also observed that the total active and reactive power demand of test system is reduced by placing capacitors at optimal locations by proposed method than existing method. 2) Example: 2 The 25 bus unbalanced radial distribution system is considered as second example for testing the efficacy of proposed method. The line and load data of this test is taken from [14]. The selection of locations for capacitors is same as second example. For this test system 0.4 is taken as PLI tolerance which is selected by experimentation. The PLI values for 25 bus unbalanced radial distribution system is shown in Fig. 2. From this Fig. 2, the buses 9, 12, 14 and 15 are selected as optimal locations. Fig. 2: Power loss indices of 25 bus unbalanced radial distribution system 0 0.2 0.4 0.6 0.8 1 1.2 0 5 10 15 20 25 30 Bus number Power loss indices (PLI)
  5. 5. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 71 Summary of test results of 25 bus unbalanced radial distribution system is given in Table 3. The net saving obtained by existing and proposed methods are Rs. 10,87,405 and Rs. 11,00,689 for the total size of capacitor of 450 kVAr and 500 kVAr respectively. From Table 3, it is observed that the minimum voltages in phases A, B and C are improved from 0.9284, 0.9284 and 0.9366 p.u to 0.9545, 0.9522 and 0.9611 p.u by existing method, 0.9567, 0.9542 and 0.9631 p.u by proposed method respectively. Also observed that the active power loss in phases of A, B and C is reduced from 52.82, 55.44 and 41.86 kW to 37.58, 39.22 and 29.51 kW by existing method and 37.34, 38.92 and 29.32 kW by proposed method respectively. The reactive power loss in phases A, B and C is reduced from 58.32, 53.29 and 55.69 kVAr to 41.56, 38.05 and 39.77 kVAr by existing method and 41.36, 37.58 and 39.23 kVAr by proposed method respectively. Table 2: Summary of test results of 37 bus unbalanced radial distribution system Description Before capacitor placement Existing method [8] Proposed method Phase A Phase B Phase C Phase A Phase B Phase C Phase A Phase B Phase C Size of the Capacitor(Qc in kVAr) with node number 2 --- --- --- 0 0 0 50 50 50 10 0 0 0 50 50 50 11 100 100 100 50 50 50 33 100 100 100 100 100 100 37 50 50 50 50 50 50 Minimum voltage 0.9497 0.9578 0.9445 0.9622 0.9712 0.9598 0.9625 0.9718 0.9601 Max. Volt. regulation 0.0503 0.0422 0.0555 0.0378 0.0288 0.0402 0.0375 0.0282 0.0399 Improvement of max. Voltage regulation (%) --- --- --- 24.8509 31.7535 27.5676 25.4473 33.1754 28.1081 Net saving(Rs.) Best --- 309007 315304 Worst 222161 248654 Average 307764 309321 Total active power loss (kW) 31.56 23.67 30.44 25.47 20.41 24.99 25.23 20.36 24.81 Total active power loss reduction (%) --- --- --- 19.32 13.77 17.89 20.05 13.99 18.49 Total reactive power loss (kVAr) 24.01 22.31 29.20 20.41 18.83 24.65 20.21 18.78 24.49 Total reactive power loss reduction (%) --- --- --- 15.02 15.62 15.56 15.86 15.84 16.10 Total active Power demand(kW) 885.56 789.67 1163.44 879.47 786.41 1157.99 879.23 786.36 1157.81 Total reactive Power demand(kVAr) 442.01 397.31 580.19 438.40 393.83 575.65 438.21 393.78 575.49 Total Feeder Demand (kVA) 989.75 883.99 1300.09 982.68 879.51 1293.19 982.38 879.44 1292.95 Released feeder capacity (kVA) --- --- --- 7.07 4.48 6.90 7.36 4.55 7.13
  6. 6. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 72 Table 3: Summary of test results of 25 bus unbalanced radial distribution system Description Before capacitor placement Existing method [8] Proposed method Phase A Phase B Phase C Phase A Phase B Phase C Phase A Phase B Phase C Size of the Capacitor (Qc in kVAr) with node number 9 --- --- --- 150 150 150 150 150 150 12 100 100 100 100 100 100 14 0 0 0 150 150 150 15 200 200 200 100 100 100 Minimum voltage 0.9284 0.9284 0.9366 0.9545 0.9522 0.9611 0.9567 0.9542 0.9631 Max. Volt. Regulation (%) 7.16 7.16 6.34 4.55 4.78 3.89 4.33 4.58 3.69 Improvement of max. Voltage regulation (%) --- --- --- 36.4525 33.2402 38.6435 39.5251 36.0335 41.7981 Net saving(Rs.) Best --- 1087405.2260 1100689.5266 Worst 1059162.1232 1093939.6864 Average 1086473.9888 1099873.1927 Total active power loss (kW) 52.82 55.44 41.86 37.58 39.22 29.51 37.34 38.92 29.32 Total active power loss reduction (%) --- --- --- 28.85 29.26 29.50 29.31 29.80 29.96 Total reactive power loss (kVAr) 58.32 53.29 55.69 41.86 38.05 39.77 41.36 37.58 39.23 Total reactive power loss reduction (%) --- --- --- 28.22 28.60 28.59 29.08 29.48 29.56 Total active Power demand(kW) 1126.12 1138.74 1125.16 1110.88 1122.52 1112.81 1110.64 1122.22 1112.62 Total reactive Power demand(kVAr) 850.32 854.29 855.69 833.86 839.05 839.77 833.36 838.58 839.23 Total Feeder Demand (kVA) 1411.09 1423.57 1413.57 1389.02 1401.45 1394.12 1388.53 1400.93 1393.64 Released feeder capacity (kVA) --- --- --- 22.07 22.12 19.45 22.56 22.64 19.93 6. CONCLUSION The proposed ABC method successfully achieved the optimal solutions. The results of the proposed method were compared with existing method for capacitor placement at multiple locations. The proposed method shows that the sizes of capacitors at optimal locations improve the net saving significantly than the sizes of capacitor obtained by existing method. The real and reactive power demand effect is reduced on total system due to capacitors placement. The minimum voltage is also improved by proposed method than existing method. REFERENCES [1] J.J. Grainger and S.H Lee, “Optimum size and location of shunt capacitors for reduction of losses on distribution feeders,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS- 100, No. 3, PP. 1105-1118, 1981. [2] M.E. Baran and F.F. Wu, “Optimal capacitor placement on radial distribution systems,” IEEE Transactions on Power Delivery, Vol. 4, No. 1, PP. 725-734, 1989. [3] H.D.Chiang, , J.C. Wang, O. Cockings and H.D. Shin, “Optimal capacitor placements in distribution systems,” IEEE Transactions on Power Delivery, Vol. 5, No. 2, PP. 643-649, 1990. [4] C.J. Bridenbaugh, D.A. Di Mascio and R. D’ Aquila, “Voltage control improvement through capacitor and transformer tap optimization,” IEEE Trans. Power Syst., Vol. 7, No. 1, PP. 222– 226, 1992.
  7. 7. International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 4, July-August (2013), © IAEME 73 [5] S. Sundharrajan and A. Pahwa, “Optimal selection of capacitors for radial distribution systems using a genetic algorithm,” IEEE Trans. on Power Systems. Vol.9, PP.1499-1507, 1994. [6] T.S. Abdul-Salam, A.Y. Chikhani and R. Hacka, “A new technique for loss reduction using compensating capacitors applied to distribution systems with varying load condition,” IEEE Trans. on Power Delivery, Vol.9, No.2, PP.819-827, 1994. [7] C.S. Chen, C.T. Hsu and Y.H. Yan, “Optimal distribution feeder capacitor placement considering mutual coupling effect of conductors,” IEEE Trans. on Power Delivery, Vol.10, No.2, PP.987-994, 1995. [8] P. Umapathi Reddy, S. Sivanagaraju and P. Sangameswara Raju, “Particle swarm optimization based approach for loss reduction in unbalanced radial distribution system,” International Journal of Engineering Science and Technology (IJEST), Vol. 3, No.11, PP. 8030-8038, November 2011. [9] Radial Distribution test feeders - www.ewh.ieee.org/soc/pes/dsacom/testfeeders.html. [10] D. Karaboga and B. Basturk, “Artificial bee colony optimization algorithm for solving constrained optimization problems,” Springer-Verlag, IFSA, LNAI 4529, PP. 789–798, 2007. [11] D. Karaboga and B. Basturk, “On the performance of artificial bee colony algorithm,” Elsevier Applied Soft Computing, Vol. 8, PP.687–697, 2007. [12] S. Hemamalini and Sishaj P. Simon, “Economic load dispatch with valve-point effect using artificial bee colony algorithm,” xxxii national systems conference, nsc 2008, december 17- 19, 2008. [13] Chin Soon. Chong, Hean Low. Malcolm Yoke, Appa Iyer. Sivakumar and Khen. Leng Gay, “A Bee Colony Optimization Algorithm to Job Shop Scheduling,” Proc. of the 2006 Winter Simulation Conference, PP.1954- 1961, 2006. [14] J.B.V. Subramnyam, “Optimal capacitor placement in unbalanced radial distribution networks,” Journal of Theoretical and Applied Information Technology, Vol. 6, N0. 1, PP.106-115, 2009. [15] Suresh Kamble and Dr. Chandrashekhar Thorat, “Characterization of Voltage Sag Due to Balanced and Unbalanced Faults in Distribution Systems”, International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 1, 2012, pp. 197 - 209, ISSN Print: 0976-6545, ISSN Online: 0976-6553. [16] S.Neelima and Dr. P.S.Subramanyam, “Effect of Load Levels on Sizing and Location of Capacitors in Distribution Systems”, International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 3, 2012, pp. 31 - 42, ISSN Print: 0976-6545, ISSN Online: 0976-6553. [17] G.Vasu, J. Nancy Namratha and V.Rambabu, “Large Scale Linear Dynamic System Reduction Using Artificial Bee Colony Optimization Algorithm”, International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 1, 2012, pp. 145 - 155, ISSN Print: 0976-6545, ISSN Online: 0976-6553.

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