Differential Evolution Based Optimal Choice and Location of Facts Devices in Restructured Power System
Authors: K. Balamurugan, V. Dharmalingam, R. Muralisachithanandam, R. Sankaran
Abstract:
This paper deals with the optimal choice and location of FACTS devices in deregulated power systems using Differential Evolution algorithm. The main objective of this paper is to achieve the power system economic generation allocation and dispatch in deregulated electricity market. Using the proposed method, the locations of the FACTS devices, their types and ratings are optimized simultaneously. Different kinds of FACTS devices such as TCSC and SVC are simulated in this study. Furthermore, their investment costs are also considered. Simulation results validate the capability of this new approach in minimizing the overall system cost function, which includes the investment costs of the FACTS devices and the bid offers of the market participants. The proposed algorithm is an effective and practical method for the choice and location of suitable FACTS devices in deregulated electricity market.
Keywords: FACTS Devices, Deregulated Electricity Market, Optimal Location, Differential Evolution, Mat Lab.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1088622
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1992References:
[1] L.J. Cai, I. Erlich and G. Stamtsis, “Optimal choice and allocation of FACTS devices in deregulated electricity markets using genetic algorithms”, IEEE Power Engineering Society Power System Conference and Exposition, vol. 1, pp 201-207, October 2004.
[2] S.C. Srivastava and R.K. Verma, “Impact of FACTS devices on transmission pricing in a deregulated electricity market”, International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, pp 642– 648, April 2000.
[3] E. Handschin and C. Lehmkoster, “Optimal Power Flow for Deregulated System with FACTS Devices”, Proc. 13th PSCC, Trondheim, Norway, pp.1270-1276, June1999.
[4] J.D. Finney, H.A. Othman, W.L. Rutz, “Evaluating transmission congestion constraints in system planning”, IEEE Trans. on PowerSystems, vol. 12, pp. 1143-1150, August 1997.
[5] G.C. Stamtsis, “Power Transmission Cost Calculation in Deregulated Electricity Market”, Logos Verlag Berlin, ISBN 3-8325-0452-4, Berlin 2004.
[6] S. Gerbex, R. Cherkaoui, and A. J. Germond, “Optimal location of multitype FACTS devices in a power system by means of genetic algorithms”, IEEE Trans. Power Systems, vol. 16, pp. 537-544, August. 2001.
[7] L.J. Cai, “Robust Coordinated Control of FACTS Devices in Large Power Systems“, Logos Verlag Berlin, ISBN 3-8325-0570-9, Berlin 2004.
[8] Lijun Cai and Istvan Erlich, “Optimal Choice and Allocation of FACTS Devices using Genetic Algorithms”, ISAP, Intelligent System Application to Power System, Lemnos, Greece, August 31 – September 3, 2003.
[9] T. S. Chung, and Y. Z. Li, “A hybrid GA approach for OPF with consideration of FACTS devices”, IEEE Power Engineering Review, pp.47-57, February. 2001. M. Young, the Technical Writers Handbook. Mill Valley, CA: University Science, 1989.
[10] R. Storn, “Differential Evolution, A Simple and Efficient Heuristic Strategy for Global Optimization over Continuous Spaces”, Journal of Global Optimization, Vol. 11, Dordrecht, pp. 341-359, 1997.
[11] Price, K.V. (1999), “An Introduction to Differential Evolution” in Corne, D., Dorigo, M. and Glover, F. (Eds), New Ideas in Optimization, McGraw- Hill, London.
[12] Storn, R. and Price, K., “Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces”, Journal of Global Optimization, vol. 11, pp. 341–359, 1997.
[13] Mrs. S. Latha, Mrs. Raja Mary Slochanal & Mr. K. Balamurugan, Optimum size and Location of UPFC Using the Method of Evolutionary Programming, IE-Journal (EL), Vol-83, Page No. 242 to 245, Dec- 2002.