基于模糊集理论的发电公司分段报价策略研究

FUZZY SET THEORY BASED BIDDING STRATEGIES FOR GENERATION COMPANIES IN ELECTRICITY MARKET ENVIRONMENT

在电力市场环境下,发电公司竞价上网的目标是最大化利润。显然,发电公司采用的报价策略对其获得的利润会有相当大的影响。文章针对运行不久、历史数据尚不充分、采用分段报价和统一市场清除价的电力市场,提出了一种为发电公司构造最优报价策略的方法。文中在历史报价数据尚不充分和获取其他相关信息的基础上,采用模糊集理论描述了发电市场中竞争对手的报价行为,并建立了报价策略的模糊优化模型, 然后采用遗传算法求解得到发电公司的最优报价策略。最后用算例说明了该方法的主要特征。

The power industry restructuring is undergoing in many countries around the world and as a result many electricity markets are established. Under the electricity market environment, profits of generation companies depend, to a large extent, on bidding strategies employed. Hence, how to develop optimal bidding strategies becomes a major concern of generation companies. A fuzzy set theory based method for building optimal bidding strategies is developed for generation companies participating in a recently established electricity market in which the well-known step-wise bidding protocol is utilized and the available historical data is insufficient. Taken into account of the insufficient history data especially bidding data, bidding behaviors of rival generation companies are modeled as fuzzy sets. The genetic algorithm is next employed to solve the bidding strategy optimization problem. Finally, a simple numerical example with five suppliers in an electricity market is served for illustrating the essential features of the presented method.