Fast Clearing Method for Inter-Provincial Medium- and Long-Term Power Transactions Considering Low Carbon Value and Uncertainty Characteristics of Green Power

[Objective] Building and improving the mid-long-term electricity market between provinces is one of the fundamental links in promoting the development of green electricity and implementing the “dual carbon” goals. However，the randomness of green power output affects the physical feasibility of medium- and long-term clearing schemes for inter-provincial electricity transactions，and the participation of large-scale green power increases the burden of solving the clearing model. This paper proposes a fast-clearing method for mid- to long-term inter-provincial electricity transactions that considers the low-carbon value and stochastic characteristics of green electricity to improve the feasibility of clearing schemes and the efficiency of clearing calculations. [Methods] This paper constructs an inter-provincial electricity mid- to long-term transaction-clearing model that considers the low-carbon value and stochastic characteristics of green electricity. The objective function includes the cost of carbon emissions from power generation and the non-executable electricity penalty established based on the distribution characteristics of green electricity output，enabling clean and low-carbon green electricity to gain an advantage in market competition and improve the enforceability of green electricity-winning bids. Subsequently，an acceleration strategy based on fixed transaction variables is proposed. Based on the calculation results of the period decoupling model，transaction variables with a high probability of not closing are fixed，thereby constructing a smaller-scale clearing model and improving the efficiency of the clearing calculation. [Conclusions] Simulation examples based on actual transaction data from China show that the proposed model can balance the feasibility of the green electricity winning bid quantity and winning bid electricity. In addition，the proposed acceleration strategy can improve the computational efficiency by an average of 1.91 times while ensuring feasibility and accuracy （with an average relative error of only 0.4% compared with the optimal solution in multiple examples）. [Conclusions] This translation accurately reflects the technical meaning and structure of the original Chinese sentence while being fluent and appropriate for an academic context.