日前和实时市场中发电商多目标二层规划竞价策略  

A Multi-Objective Bi-Level Programming Bidding Strategy Model for Generation Companies in Day-Ahead and Real-Time Electricity Market

作　　者：曾亮[1] 齐欢[1] 陈迎春[1] 

机构地区：[1]华中科技大学控制科学与工程系,湖北省武汉市430074

出　　处：《电网技术》2009年第1期65-70,共6页Power System Technology

基　　金：国家自然科学基金项目(60574025;60774036)~~

摘　　要：由日前和实时市场组成的2市场交易机制是目前普遍存在的电力市场交易机制,在2市场中发电商的电量分配和竞价决策以及风险评估等都是受到广泛关注的问题。指出了现有文献在借鉴经济学和金融学的理论模型来研究多交易市场中发电商竞价策略时存在的问题。首先在分析了发电商竞价结果的概率分布之后,提出了发电商竞价成功概率分布函数的概念。然后基于日前和实时市场中投标结构的特点,针对采用分段报价和按报价结算(pay as bid price,PAB)方式的电力市场,建立了日前和实时市场中发电商的多目标二层规划竞价策略模型,并设计了以蒙特卡罗方法和遗传算法为基础的求解算法。最后采用算例对所提出的模型和算法进行了仿真验证。The dual market transaction mechanism consisting of day-ahead market and real-time market is a ubiquitous transaction mechanism for electricity markets, and in the dual markets generation companies （GenCos） pay special attentions to those items such as electricity quantity allocation, bidding decision and risk evaluation. The authors point out the implicit problems that the theoretical models in economics and financial sciences in published literatures are used for reference in the research of bidding strategies of GenCos in multi-transaction markets. Firstly, after the analysis on probability distribution of GenCos＇ bidding results, a concept of bid acceptance probability distribution function of GenCos is proposed; then based on the features of bidding structure in day-ahead and real-time markets, a multi-objective bi-level programming bidding strategy model in day-ahead and real-time markets for GenCos is built for electricity markets in which the step-wise bidding function and pay-as-bid settlement protocols are utilized; and then in order to solve the proposed model an algorithm based on Monte Carlo method and genetic algorithm is designed; finally, the simulation of numerical examples are performed to verify the correctness of the proposed model and algorithm.

关 键 词：目前和实时市场 多目标二层规划 竞价策略 多市场中的协调 竞价成功概率分布函数 蒙特卡罗方法 

分 类 号：F123.9[经济管理—世界经济]