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Optimal bidding strategy for price takers and customers in a competitive electricity market

Mathur, Somendra P.S.; Arya, Anoop; Dubey, Manisha

Cogent engineering. Volume 4:Number 1 (2017, January 1st) -- Cogent OA, an imprint of Taylor & Francis

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  • Title:
    Optimal bidding strategy for price takers and customers in a competitive electricity market
  • Author: Mathur, Somendra P.S.;
    Arya, Anoop;
    Dubey, Manisha;
    Xie, Gongnan
  • Found In: Cogent engineering. Volume 4:Number 1 (2017, January 1st)
  • Journal Title: Cogent engineering
  • Subjects: Engineering--Periodicals; Technology--Periodicals; Engineering; Periodicals; Technology; bidding strategy--competitive electricity market--rival's behavior--genetic algorithm; Dewey: 620
  • Rights: Licensed
  • Publication Details: Cogent OA, an imprint of Taylor & Francis
  • Abstract: Abstract:

    Bidding strategies are highly associated with the profit maximization and decreasing the risks for power utilities in a competitive market. For finding the optimal bidding strategies price takers need appropriate bidding structure. Thus, it is required to consider the model as a bi-level optimization problem. In the lower level price takers submit bid strategically to the ISO and in the upper level maximization of social welfare performed by solving the ISO Market clearing price (MCP). This paper aim to summarize the price taker's bidding strategy modeling methods for competitive market models on the state-of-the art. A new genetic algorithm approach in a day-ahead electricity market in sealed auction with a pay-as-bid MCP has been employed to solve the problem from two different viewpoints i.e. with symmetrical and unsymmetrical information. The efficiency of the proposed method has been tested on the IEEE-30 bus system.


  • Identifier: System Number: ETOCvdc_100081385561.0x000001; Journal ISSN: 2331-1916; 10.1080/23311916.2017.1358545
  • Publication Date: 2017
  • Physical Description: Electronic
  • UIN: ETOCvdc_100081385561.0x000001

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