摘要
针对目前发电侧电力市场环境下发电商间日益激烈的竞争,介绍了一种发电商根据竞争对手竞价历史数据优化主电力市场和旋转备用市场联合竞价策略的方法。该方法首先对竞争对手的历史数据进行分析并确定其概率密度分布,然后用蒙特卡洛对竞争对手竞价策略进行抽样,最后对各抽样结果采用退火遗传算法优化竞价策略,优化结果的期望即可作为发电商的竞价策略。文中给出由六个发电商组成的市场模拟算例,计算结果表明该方法是可行的。
As the competition at generation side becomes more and more furious under deregulated environment, a new method, which can optimize the bidding strategies of generation company in day--ahead energy and spinning reserve according to its rivals＇ history data, is presented in this paper. Firstly, history data is analyzed to establish its probability distribution, and then Monte Carlo simulation is used to simulate the rivals＇ bidding strategies. On that basis, the bidding strategies are optimized using annealing genetic algorithm. Finally an example is given to show the feasibility of the method.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2006年第6期10-12,共3页
Proceedings of the CSU-EPSA
基金
国家自然科学基金资助项目(50539140)
关键词
电力市场
旋转备用市场
竞价策略
power market
spinning reserve market
bidding strategies
