不确定环境下的随机模糊规划最优报价策略模型  

Random-fuzzy Programming Model for Developing Optimal Bidding Strategies in the Uncertain Environment

作　　者：马新顺[1] 刘建新[1] 文福拴[2] 

机构地区：[1]华北电力大学电气与电子工程学院,河北省保定市071003 [2]华南理工大学电力学院,广东省广州市510640

出　　处：《中国电机工程学报》2009年第34期77-83,共7页Proceedings of the CSEE

基　　金：国家自然科学基金项目(70673023);华北电力大学博士学位教师科研基金项目(200612005)~~

摘　　要：在电力市场环境下,发电公司在构造其最优报价策略时需考虑多种不确定信息,如竞争对手的策略性行为、系统预测负荷及需求弹性等。由于受到数学理论的限制,在构造发电公司的最优报价策略方面,以往的研究工作仅能够将这些不确定参数分别按随机变量或模糊变量进行处理,而不能将实际中存在的随机和模糊两类不确定性进行统一处理。从不确定理论出发,将竞争对手的报价行为和需求弹性作为模糊变量处理,同时将预测负荷视为随机变量的情况下,构造了计及风险的发电公司最优报价的机会约束随机模糊规划模型,设计了将随机模糊模拟、神经网络和遗传算法结合在一起的混合智能算法进行求解。用有6个发电公司参与的电力市场进行计算和分析,说明了该文模型及求解算法的可行性及有效性。In a competitive electricity market, the optimal bidding strategies of generation companies could be developed based on estimation of the hybrid random and fuzzy parameters such as rivals＇ bidding strategies, the forecasted load and price- demand elasticity. The probability theory and the possibility theory were employed to handle the uncertain information in existing literature, but the randomness and the fuzziness were dealt with separately. A new methodological framework with chance constrained random-fuzzy programming, which evaluated the randomness of the forecasted load, the fuzziness of rivals＇ biddings strategies and price-demand elasticity, was developed for building optimal bidding strategies of generation companies with the uncertainty theory based risk management taken into account. A hybrid intelligent algorithm with combined random-fuzzy simulation, artificial neural network and genetic algorithm was proposed to solve the random-fuzzy programming problem. A numerical example of a simulated electricity market with six participating generation companies was served for demonstrating the feasibility and efficiency of the developed model and solution algorithm.

关 键 词：电力市场 报价策略 不确定理论 随机模糊规划 混合智能算法 

分 类 号：TM73[电气工程—电力系统及自动化]