新能源并网环境下发电侧微分演化博弈竞价策略

A Bidding Strategy Based on Differential Evolution Game for Generation Side in Power Grid Integrated With Renewable Energy Resources

智能电网中新能源的大量接入及其固有的不确定性,导致电力市场对常规电能需求裕度降低并存在大幅波动性,从而对发电侧竞价策略的可靠性提出了更高的要求。将演化博弈理论引入到发电商的竞价策略中,以便在不确定性环境中可通过动态演化获得稳定的最优竞价策略;鉴于可再生能源出力的不确定性导致演化博弈复制动态方程难以求解,提出通过将演化博弈思想与复合微分进化算法有机融合,构造复合微分演化博弈算法实现发电商竞价发电的动态演化博弈过程;最后通过与常规竞价策略进行对比分析,验证了所提出的微分演化博弈竞价策略的优越性。

Large number of renewable energy resources integrated in smart grid and its inherent uncertainty lead to decrease and high volatility of the demand margin of conventional energy resources in electricity market, raising higher requirements of reliability for the bidding strategy for generation side. In this paper, evolutionary game theory is applied to the bidding strategy of generators, so that a stable optimal bidding strategy can be obtained through dynamic evolution in uncertain environment. Because the uncertainty of renewable energy output can lead to the replicating dynamic equation of evolutionary game difficult to solve, a compound differential evolution game algorithm combining evolutionary game theory with composite differential evolution is proposed to achieve dynamic evolution game based generating and bidding of generators. Finally, by comparing with conventional bidding strategies, superiority of the proposed differential evolution game strategy is verified.