MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH USING DIFFERENTIAL EVOLUTION

  • Ram Kishan Mahate Department of Electrical Engineering, Madhav Institute of Technology and Science Gwalior, India
  • Himmat Singh Department of Electrical Engineering, Madhav Institute of Technology and Science Gwalior, India
Keywords: Reactive Power Management, Differential Evolution Algorithm, Power Loss Minimization, Voltage Deviation, Pareto-Optimal Solutions

Abstract

Reactive power optimization is a major concern in the operation and control of power systems. In this paper a new multi-objective differential evolution method is employed to optimize the reactive power dispatch problem. It is the mixed–integer non linear optimization problem with continuous and discrete control variables such as generator terminal voltages, tap position of transformers and reactive power sources. The optimal VAR dispatch problem is developed as a nonlinear constrained multi objective optimization problem where the real power loss and fuel cost are to be minimized at the same time. A conventional weighted sum method is inflicted to provide the decision maker with a example and accomplishable Pareto-optimal set. This method underlines non-dominated solutions and at the same time asserts diversity in the non-dominated solutions. Thus this technique treats the problem as a true multi-objective optimization problem. The performance of the suggested differential evolution approach has been tested on the standard test system IEEE 30-bus.

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References

Lee K Y, Paru Y M, “Oritz J L –A united approach to optimal real and reactive power dispatch”, IEEE Transactions on power Apparatus and systems 1985: PAS-104 : 1147-1153 DOI: https://doi.org/10.1109/TPAS.1985.323466

A.Monticelli , M .V.F “Pereira ,and S. Granville , “Security constrained optimal power flow with post contingency corrective rescheduling” , IEEE Transactions on Power Systems :PWRS-2, No. 1, pp.175 182.,1987. DOI: https://doi.org/10.1109/TPWRS.1987.4335095

Deeb N, Shahidehpur S.M, “Linear reactive power optimization in a large power network using the decomposition approach”. IEEE Transactions on power system 1990: 5(2) : 428-435 DOI: https://doi.org/10.1109/59.54549

D. Devaraj, and B. Yeganarayana, “Genetic algorithm based optimal power flow for security enhancement”, IEE proc Generation. Transmission and. Distribution; 152, 6 November 2005 DOI: https://doi.org/10.1049/ip-gtd:20045234

Kwang Y. Lee and Frank F.Yang, “Optimal Reactive Power Planning Using evolutionary Algorithms: A Comparative study for Evolutionary Strategy, Genetic Algorithm and Linear Programming”, IEEE Trans. on Power Systems, Vol. 13, No. 1, pp. 101- 108, February 1998. DOI: https://doi.org/10.1109/59.651620

R. Storn, K. Price, “Differential evolution—a simple and efficient adaptive scheme for global optimization over continuous spaces”, in: Technical Report TR-95-012, ICSI, 1995.

R. Storn, K. Price,” Differential evolution, a simple and efficient heuristic strategy for global optimization over continuous spaces”, Journal of Global Optimization 11 (1997) 341–359. DOI: https://doi.org/10.1023/A:1008202821328

Zhenyu Yang, Ke Tang, Xin Yao,” Differential evolution for high-dimensional function optimization”, in IEEE Congress on Evolutionary Computation (CEC2007), 2007, pp. 3523–3530. DOI: https://doi.org/10.1109/CEC.2007.4424929

R. Balamurugan, S, Subramanaian, “Self-adaptive differential evolution based power economic dispatch of generators with valve-point effects and multiple fuel options”, Comput. Sci. Eng 1 (1) (2007) 10-17.

N. Srinivas, K. Deb: “Multi-objective Optimization using Nondominated Sorting in Genetic Algorithm”, Evolutionary Computation, Vol. 2, No. 3, 1994, pp. 221-248. DOI: https://doi.org/10.1162/evco.1994.2.3.221

N. Grudinin, "Reactive Power Optimization Using Successive Quadratic Programming Method," IEEE Trans. on PWRS, Vol. 13, No. 4, 1998, pp. 1219-1225. DOI: https://doi.org/10.1109/59.736232

C. M. Fonseca and P. J. Fleming, “An Overview of Evolutionary Algorithms in Multiobjective Optimization,” Evolutionary Computation, Vol. 3, No. 1, 1995, pp. 1-16. DOI: https://doi.org/10.1162/evco.1995.3.1.1

E. Zitzler and L. Thiele, “An Evolutionary Algorithm for Multiobjective optimization: The Strength Pareto Approach,” Swiss Federal Institute of Technology, TIK-Report, No. 43, 1998.

M.A. Abido,” Optimal power flow using particle swarm optimization”, Electric Power Energy Syst. 24 (7) (2002) 563–571. DOI: https://doi.org/10.1016/S0142-0615(01)00067-9

Miroslav M. Begovic, Branislav Radibratovic, Frank C Lambert, “On Multi objective Volt-VAR Optimization in Power Systems”, the 37th Hawaii International Conference on System Sciences - 2004 DOI: https://doi.org/10.1109/HICSS.2004.1265192

Published
2019-02-28
How to Cite
Mahate, R. K., & Singh, H. (2019). MULTI-OBJECTIVE OPTIMAL REACTIVE POWER DISPATCH USING DIFFERENTIAL EVOLUTION . International Journal of Engineering Technologies and Management Research, 6(2), 27-38. https://doi.org/10.29121/ijetmr.v6.i2.2019.353