双轨制下电力现货市场政府授权合约分解优化模型与方法

A Decomposition and Optimization Method for Government-Authorized Contracts in a Dual-track Spot Electricity Market Based on Game Equilibrium

在现货市场中,政府授权合约的曲线分解方式对市场不平衡资金规模与市场主体利益具有重要影响,合理分解相关合约问题亟待解决。从电力现货试点实际需要出发,综合考虑不平衡资金规模、政府授权合约分解结果、发电主体报价策略及市场出清结果之间的关联性,构建了基于博弈均衡的双轨制电力现货市场政府授权合约曲线分解优化模型与方法。该方法基于博弈均衡的思想对应建立了以控制不平衡资金规模为目标的政府授权合约分解模型、考虑政府授权合约分解结果的发电商报价决策模型以及市场出清模型,利用3层粒子群算法实现各层模型间的迭代修正,得到均衡市场个体与整体利益的合约分解结果。通过算例仿真分析,验证了在各因素互相作用和博弈均衡下,所提方法对缩小市场不平衡资金规模的作用。

In the electricity spot market,the curve decomposition method of government authorization contracts has significant impacts on the funds scale of the market and the interests of participants.Hence it is becoming urgent to solve the decomposition of the government-authorized contracts in a reasonable way.According to the actual requirements of the electricity spot pilot project,this paper first takes into full consideration the correlation between the scale of unbalanced funds,the decomposition results of the government-authorized contracts,the quotation strategy of the power generation entities and the results of market clearing.Based on game equilibrium,a decomposition and optimization method for government-authorized contracts in a dual-track spot electricity market is constructed.Then,the government-authorized contract decomposition model to constraint the unbalanced funds scale,the quotation decision model of power generation companies considering the decomposition results of the government-authorized contracts,and the market clearing model are established respectively.A three-layer particle swarm optimization algorithm is proposed to achieve iterative corrections between different models,such that the contract decomposition results that balance the individual and the overall interests of the market are obtained.Finally,case studies are conducted and analyzed by means of numerical simulations.The effect of the proposed method on reducing the unbalanced funds scale in the market is verified under the interactions of various factors and game equilibrium.