基于多Agent遗传算法的水电厂机组优化组合研究与实现  

Research and implementation of unit optimization combination of hydropower plant based on multi-Agent genetic algorithm

作　　者：孟安波[1] 刘永前[2] 徐海波 

机构地区：[1]广东工业大学自动化学院,广东广州510006 [2]华北电力大学,北京102206 [3]广东易事特现代电力电子工程技术研究研发中心,广东东莞523808

出　　处：《电力系统保护与控制》2011年第1期23-28,共6页Power System Protection and Control

基　　金：国家863计划资助项目(2007AA05Z428)~~

摘　　要：基于多Agent系统理论,构建了一个多Agent机组优化组合系统。对于问题优化模型,提出了一种新颖的多Agent遗传算法,解决了大规模遗传算法的效率问题。对于机组的非线性耗水量特性,提出了一种由Agent动态地管理与维护的神经网络。基于与FIPA兼容的多Agent中间件JADE平台,给出了一个详细的具体实施系统。仿真结果验证了所提出的优化模型与实施方案的合理性和可操作性。Based on multi-Agent system theory,a MAS based system for unit optimization combination is built.For the optimization problem mentioned above,a novel MAS based genetic algorithm is proposed,which solves the efficiency problem for genetic algorithm with large-scale computation.As far as the nonlinear water consumption characteristic of generating units is concerned,the BP neural network which can be managed and maintained by Agent is proposed.Based on multi-agent middle ware JADE platform which is fully compliant with FIPA,a detailed implementation system is presented.The simulation results exhibit the reasonability and feasibility of the model proposed in this paper.

关 键 词：水电厂 多代理系统 机组优化组合 遗传算法 中间件 

分 类 号：TV736[水利工程—水利水电工程]