基于MEA算法结合委托代理模式的风火发电权交易研究

Research on Wind Power and Thermal Power Generation Rights Trading Based on Mind Evolutionary Algorithm Under the Principal-agent Mode

风电面临的弃风问题愈来愈严重,为了解决风电消纳难题,利用风电和常规机组之间的发电权交易来完成风电的再次消纳值得探索。结合风电出力的随机性、间断性特点,综合借鉴委托代理原理对风火发电权交易的市场结构、交易机理进行了探讨,并提出了在风火发电权交易中计及风电偏差电量成本的委托代理收益模型。结合思维进化算法(mind evolutionary algorithm,MEA)对IEEE-30节点网络的风火发电权交易模型进行算例仿真。通过仿真结果验证了委托代理模式下的风火发电权交易模型合理性,并试图为风电再次消纳提供一种合理的交易方法。

As wind power faces with more and more serious wind abandoning problem, in order to solve the problem of wind power absorption, it is worth to discuss generation rights trading between wind power and conventional power units so as to finish secondwind power absorption. Therefore, this paper discusses market structure and trading mechanism of wind power and thermal power generation rights by combining characteristics of random and intermittent of wind power output and com- prehensively considering principal-agent principles, it also presents a principal-agent benefit model considering wind power deviation electricity costs in generation rights trading. Combining mind evolutionary algorithm （MEA）, it conducts example simulation on the trading model of IEEE-30 node system and the results verify reasonability of the wind power and thermal power generation rights trading model under the principal-agent mode. By simulation, it also tries to provide a kind of rea- sonable trading method for second wind power absorption.