Optimal scheduling of electricity-carbon joint multilateral trading in regional power grid based on Nash negotiation
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    Abstract:

    Based on the background of the current electricity market and carbon trading market, aiming at the problems of insufficient consumption capacity and difficult peak shaving of regional power grids with new energy access, an optimal scheduling strategy of regional power grid electricity-carbon joint multilateral trading based on Nash negotiation is proposed. Firstly, considering improving the flexibility of multilateral trading in regional power grids, combined with carbon trading and power generation rights trading mechanisms, an electricity-carbon joint trading model is constructed. Secondly, considering the volatility of wind power, the demand method of wind power flexibility adjustment is adopted. According to the wind power curtailment and time period of day-ahead dispatching, a multi-agent peer-to-peer trading model of electricity-carbon joint is constructed. And then the model is decoupled into two sub-problems: maximizing the benefits of regional power grid alliance and reasonably allocating the benefits of electricity-carbon joint multilateral trading. The alternating direction method of multipliers is used for interactive decoupling to ensure the privacy security of each subject. In addition, in the fair distribution of benefits, the asymmetric bargaining method is selected to quantify the contribution of each subject in peer-to-peer transactions as a bargaining factor to achieve the purpose of fair distribution of benefits within the alliance. Finally, several different scenarios are set up to verify the low carbon and economy of the proposed method and model. The results show that the proposed method can promote the consumption of new energy and the improvement of flexible resource collaborative scheduling ability, and achieves the goal of energy saving and emission reduction.

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History
  • Received:September 26,2024
  • Revised:December 13,2024
  • Adopted:
  • Online: June 04,2025
  • Published: May 28,2025
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