Optimal Bidding by IPP in a Restructured Dynamic Competitive Electricity Market Adopting IGWO Method

  • Authors

    • Ramachandra Agrawal
    • Smrutirekha Tripathy
    • Debashis Sitikantha
    • Krishna Gopal
    • Manoj Kumar Debnath
    2018-12-13
    https://doi.org/10.14419/ijet.v7i4.39.27724
  • Market Clearing Price, Grey Wolf Optimization, Optimal Bidding Strategy, Restructured and forward electricity markets.

  • In a restructured Electricity Marketplace the Independent Power Producer (IPP) has to bid adequately to optimize their profits for each self independently. So each IPP of the electric power market should bid to adopt a proper strategy enabling it to win the maximum share of the total power demanded at any specific trading period from its rivals participating in the competitive market. In this present work, a very latest and efficient bio-inspired method known as Improved Grey Wolf Optimization (IGWO) has been considered to find out the optimal values of the bidding coefficients. The implementation of IGWO evidenced much better output in terms of higher profits in comparison to the earlier methods reported recently by the eminent researchers. Additionally, a new case study involving an entire trading day with the ramp rate constraints for the IPPs along with the consumer demand variation, both on an hourly basis, is presented, which has not been proposed by anyone so far. The Market Clearing Price (MCP) variation is also kept within the specified extreme boundaries during each hour of the entire trading duration of the day depicting a dynamic market environment. The proposed technique along with the simple GWO method when tested on IEEE 30 Bus standard configuration incorporating 6 IPPs in the MATLAB environment resulted in much-improved outcomes compared to the latter case.

     

     

  • References

    1. [1] D. Zhang, Y. Wang, and P. B. Luh, “Optimization based bidding strategies in deregulated marketâ€, Proc. IEEE PES Power Industry Computer Applications Conf., 1999, pp. 63–68.

      [2] A. K. David, and F. Wen, “Strategic bidding for electricity supply in a day-ahead energy marketâ€, Electr. Power Syst. Res., 2001, 59, pp. 197–206.

      [3] K.Singh, N. P. Padhy, and J. Sharma, "Influence of price responsive demand shifting bidding on congestion and LMP in pool-based day-ahead electricity markets.†Power Systems, IEEE Transactions on 26, no. 2 (2011): 886-896.

      [4] David, A. Kumar, and Fushuan Wen. "Strategic bidding in competitive electricity markets: a literature survey." In Power Engineering Society Summer Meeting, 2000. IEEE, vol. 4, pp. 2168-2173. IEEE, 2000.

      [5] M. Prabavathi, R. Gnanadass, “Energy bidding strategies for restructured electricity market’’, International Journal of Electrical Power pp. 956–966.

      [6] Li CA, Svoboda AJ, Guan XH, Singh H., “Revenue adequate bidding strategies in competitive electricity marketsâ€, IEEE Transactions on Power Systems 1999;14(2):492–7.

      [7] Wu. Yuan-Kang, "Comparison of pricing schemes of several deregulated electricity markets in the world." Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES, pp. 1-6. IEEE, 2005.

      [8] Ni Yixin, Jin Zhong, and Haoming Liu, "Deregulation of power systems in Asia: special consideration in developing countriesâ€, Power Engineering Society General Meeting, 2005, pp. 2876-2881. IEEE, 2005.

      [9] P.HERINGS and R.PEETERS, “a globally convergent algorithm to compute all Nash equilibria for n person gamesâ€, July 2005, Volume 137, Issue 1, pp 349-368.

      [10] Yuan-Kang, Wu. "Comparison of pricing schemes of several deregulated electricity markets in the world." In Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES, pp. 1-6. IEEE, 2005.

      [11] Shukla, Umesh Kumar, and Ashok Thampy. "Analysis of competition and market power in the wholesale electricity market in India." Energy Policy 39, no. 5 (2011): 2699-2710.

      [12] Ni, Yixin, Jin Zhong, and Haoming Liu. "Deregulation of power systems in Asia: special consideration in developing countries." In Power Engineering Society General Meeting, 2005. IEEE, pp. 2876-2881. IEEE, 2005.

      [13] Lai, Mingyong, Xiaojiao Tong, Hongming Yang, and Pingping Bing. "Dynamic bidding analysis in power market based on the supply function." Computers & Mathematics with Applications 58, no. 1 (2009): 25-38.

      [14] Soleymani, S. "Bidding strategy of generation companies using PSO combined with SA method in the pay as bid markets." International Journal of Electrical Power & Energy Systems 33, no. 7 (2011): 1272-1278.

      [15] P.D. Klempere,M.A. Meyer, “Supply function equilibria in oligopoly under Uncertaintyâ€, Econometrica 1989;57(2):1243–77.

      [16] R. Green,D.M. Newbery, “Competition in the British electricity spot marketâ€, J Polit Econ 1992;100(5):929–53.

      [17] Ettore Bompard, Wene Lu, Roberto Napoli, Xiuchen Jiang, “A supply function model for representing the strategic bidding of the producers in constrained electricity marketsâ€, Electrical Power and Energy Systems 32 (2010) 678–687,ELSEVIER.

      [18] Kumar, J. Vinoth, Shaik Jameer Pasha, and D. M. V. Kumar. "Strategic bidding in deregulated market using particle swarm optimization." In India Conference (INDICON), 2010 Annual IEEE, pp. 1-6. IEEE, 2010.

      [19] J. Vijaya Kumar, D. M. Vinod Kumar, K. Edukondalu:†Bidding Strategy Considering Risk by Generating Companies in an Open Electricity Market Using Particle Swarm Optimization†International Journal of Energy Engineering (IJEE), Feb. 2013, Vol. 3 Iss. 1, PP. 7-11.

      [20] S. Mirjalili, S. M. Mirjalili, A. Lewis, Grey Wolf Optimizer, Advances in Engineering Software , vol. 69, pp. 46-61, 2014.

      [21] Muangkote, Nipotepat, Khamron Sunat, and Sirapat Chiewchanwattana. "An improved grey wolf optimizer for training q-Gaussian Radial Basis Functional-link nets." In Computer Science and Engineering Conference (ICSEC), 2014 International, pp. 209-214. IEEE, 2014.

      [22] J. Vijaya Kumar ∗, D.M. Vinod Kumar, “Generation bidding strategy in a pool based electricity market using Shuffled Frog Leaping Algorithmâ€,Applied Soft Computing 21 (2014) 407–414,ELSEVIER.

      [23] J.V. kumar, D.M.Vinod kumar, K. Edukondalu, “strategic bidding using fuzzy adaptive gsa in a pool based electricity marketâ€, Applied soft computing 13 (2013)2445-2455, Elsevier.

  • Downloads

  • How to Cite

    Agrawal, R., Tripathy, S., Sitikantha, D., Gopal, K., & Kumar Debnath, M. (2018). Optimal Bidding by IPP in a Restructured Dynamic Competitive Electricity Market Adopting IGWO Method. International Journal of Engineering & Technology, 7(4.39), 890-896. https://doi.org/10.14419/ijet.v7i4.39.27724