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.

  • Abstract

    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.

     

     

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  • 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

    Received date: 2019-02-21

    Accepted date: 2019-02-21

    Published date: 2018-12-13