TIAN Yonglin. Optimal scheduling of electricity-carbon joint multilateral trading in regional power grid based on Nash negotiation[J]. 2025, 44(3): 108-119.
TIAN Yonglin. Optimal scheduling of electricity-carbon joint multilateral trading in regional power grid based on Nash negotiation[J]. 2025, 44(3): 108-119.DOI:
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.