International Journal of Energy Engineering          
International Journal of Energy Engineering(IJEE)
ISSN:2225-6563(Print)
ISSN:2225-6571(Online)
Frequency: Yearly
Editor-in-Chief: Prof. Sri Bandyopadhyay(Australia)
Bidding Strategy Considering Risk by Generating Companies in an Open Electricity Market Using Particle Swarm Optimization
Full Paper(PDF, 280KB)
Abstract:
This paper presents a novel methodology based on Particle Swarm Optimization (PSO) for the preparation of optimal bidding strategies by power suppliers in a competitive electricity market. The gaming by participants in a competitive electricity market causes electricity market more an oligopoly than a competitive market. In general, Competition implies the opportunities for Generation Companies (Gencos) to get more profit and, in the mean time, the risk of not being dispatched. In this paper each participant can increase their own profit by optimally selecting the bidding parameters using PSO. The proposed method is numerically verified through computer simulations on IEEE 30-bus system consist of six suppliers and two large consumers. The results are compared with Genetic Algorithm (GA) and Monte Carlo method. The Test results indicate that the proposed algorithm maximize profit, converge much faster and more reliable than GA and Monte Carlo method.
Keywords:Market Clearing Price; Optimal Bidding Strategy; Fuzzy Inference; Risk Analysis; Particle Swarm Optimization
Author: J. Vijaya Kumar1, D. M. Vinod Kumar1, K. Edukondalu1
1.Department of Electrical Engineering, National Institute of Technology, Warangal Andhrapradesh, 506004, India
References:
  1. David, A.K., and Wen, F.: ‘Strategic bidding in competitive electricity markets: a literature survey’. IEEE PES Summer Meeting, 2000, vol. 4, pp. 2168–2173
  2. David, A.K.: ‘Competitive bidding in electricity supply’, IEE Proc., Gener. Trans. Dist., 1993, 140, (5), pp. 421–426
  3. Gross, G., and Finlay, D.J.: ‘Optimal bidding strategies in competitive electricity markets’. Proc. 12th Power System Computation Conf., August 1996, pp. 815–823
  4. Zhang, D., Wang, Y., and Luh, P.B.: ‘Optimization based bidding strategies in deregulated market’. Proc. IEEE PES Power Industry Computer Applications Conf., 1999, pp. 63–68.
  5. Ferrero, R.W., Ramesh, V.C., and Shahidehpour, S.M.: Transaction analysis in deregulated power system using game theory’, IEEE Trans. Power Syst., 1997, 12, (3), pp. 1340–1347
  6. Torre, S.D., Conejo, A.J., and Contreras, J.: ‘Finding multi-period Nash equilibrium in pool-based electricity markets’, IEEE Trans. Power Syst., 2004, 19, (1), pp. 643–651
  7. David, A.K., and Wen, F.: ‘Strategic bidding for electricity supply in a day-ahead energy market’, Electr. Power Syst. Res., 2001, 59, pp. 197–206
  8. David, A.K., and Wen, F.: ‘Optimally co-ordinated bidding strategies in energy and ancillary service markets’, IEE Proc., Gener. Tran. .Dis., 2002, 149, (3), pp. 331–338
  9. Ugedo, A., Lobato, E., Franco, A., Rouco, L., Ferna´ndez-Caro, J., and Chofr, J.: ‘Strategic bidding in sequential electricity markets’, IEE Proc. Gener. Tran. Dis., 2006, 153, (4), pp. 431–442.
  10. Fleten, S.-E., and Pettersen, E.: ‘Constructing bidding curves for a price-taking retailer in the Norwegian electricity market’, IEEE Trans. Power Syst., 2005, 20, (2), pp. 701–708
  11. Song, H.L., Liu, C.C., and Lawree, J.: ‘Decision making of an electricity suppliers bid in a spot market’. Proc. IEEE Power Engineering Society Summer Meeting, 1999, vol. 1, pp. 692–696
  12. David, A.K., and Wen, F.S.: ‘Optimal bidding strategies for competitive generators and large consumers’, Elect. .Power. Syst., 2001, 23, (1), pp. 37–43.
  13. Gan K.S., Anthony P. and Teo J. Mutation rate in the evolution of bidding strategies, The 3rd International Symposium on Information Technology 2008, 2008.
  14. A.k.Jain. and S.C.srivastava. Strategic Bidding and risk Assessment Using Genetic Algorithm in Electricity Markets. International Journal of Emerging Electric Power Systems, 2009, Vol.10.
  15. P.Bajpai, S.K.Punna and S.N.Singh. “Swarm intelligence-based strategic bidding in competitive electricity markets”. IET Gener. Trans. Distr. 2008, 2, (2), pp.175-184.
  16. K. Kanakasabhapathy, K. Shanti Swarup.” Evolutionary Tristate PSO for strategic Bidding of Pumped-Storage Hydroelectric plant”. IEEE Trans. on Syst. Man, and Cybernetics. Vol. 40, No. 4, July 2010.
  17. Guangquan Zhang, Guoli Zhang, Ya Gao, and Jie Lu.:”Competitive Strategic Bidding Optimization in Electricity Market using Bi-level Programming and Swarm Technique.”, IEEE Transactions on Industrial Electronics, Vol. 58, No. 6, June 2011
  18. Kennedy, J., and Eberhart, R.: ‘Particle swarm optimisation’. Proc. IEEE Int. Conf. Neural Networks, 1995, vol. 4, pp. 1942–1948.