基于改进的PSO算法求解电力公司最优报价策略  

Improved PSO algorithm based optimal bidding strategy for generating company

作　　者：唐江桦[1] 罗可[1] 赵志学[1] 

机构地区：[1]长沙理工大学计算机与通信工程学院,长沙410076

出　　处：《计算机工程与应用》2008年第24期212-214,221,共4页Computer Engineering and Applications

基　　金：国家自然科学基金No.60474070; No.10471036;湖南省教育厅重点项目(No.07A001);湖南省科技厅项目(No.05FJ3074)~~

摘　　要：电力公司报价策略是一个双层优化问题,其中上层的ISO是保证社会公共效益最大化而制定的市场清除价模型,确定参与发电的电力公司,下层是基于发电公司利润最大的模型。采用启发式算法求解简单易行,最优解具有全局性,且与初始点选择无关。运用改进后的粒子群优化算法(PSO)求解电力公司利润最大的优化问题,并与确定性方法的计算结果进行了比较。在IEEE30节点6机系统验证了该方法的有效性。The optimal quoted price function model for a power producers is a bi-level mathematical programming problem in which the upper optimization is to maximize the benefit whilst the lower one is to maximize the benefit model.The heuristic approach can be an alternative to solve the model above with simplicity and immune to the local optima.Particle Swarm Optimization（PSO） integrating with the heuristic approach is then presented in this paper to obtain, the optimal quoted price functions for power producers.In addition,the result of the model proposed is compared with that of the deterministic approach,the IEEE 30- bus system has proved the feasibility of the proposed model.

关 键 词：两层优化模型 粒子群优化算法 报价策略 

分 类 号：TP39[自动化与计算机技术—计算机应用技术]