Optimal bidding of market players in competitive electricity markets based on a novel hybrid PSO-IGWO method

  • Authors

    • Ramachandra Agrawala
    • Prakash kumar Hota
    • Ranjan Kumar Mallick
    2018-04-03
    https://doi.org/10.14419/ijet.v7i2.12.11359
  • Competitive Electricity Market, Bidding, Optimal Bidding Issues, PSO, GWO, IGWO and HYBRID PSO-IGWO Method.

  • Abstract

    Strategic bidding is an important issue in the restructured electric marketplace. In an hour ahead actual power market having sealed bid auc-tion policy involving incomplete information of symmetrical and unsymmetrical nature have been addressed separately in the present work. Various constraints either equality type or inequality type have been properly analysed to model a market very close to a real one. Social welfare, where all the players individually benefitted is the prime objective. Hence, the bidding coefficients are to be selected very carefully. At present, the digital advancement supports each participant to optimize its desired objective through the optimization methods available so far. But, the proposed Particle Swarm Optimization-Improved Grey Wolf Optimization (PSO-IGWO) is a very novel hybrid method. Its supremacy compared to the other methods has been clearly evidenced by implementing in the present work. The standard IEEE-30 bus sys-tem and a practical 75 Bus Indian system have been considered to validate the effectiveness of the novel technique suggested and the excel-lent outputs evidence this fact on comparison with the results, of a very recently published article, found adopting GA optimization tech-nique [28].

     

     

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  • How to Cite

    Agrawala, R., kumar Hota, P., & Kumar Mallick, R. (2018). Optimal bidding of market players in competitive electricity markets based on a novel hybrid PSO-IGWO method. International Journal of Engineering & Technology, 7(2.12), 399-405. https://doi.org/10.14419/ijet.v7i2.12.11359

    Received date: 2018-04-10

    Accepted date: 2018-04-10

    Published date: 2018-04-03