作　　者： ; ; (徐海波）;

机构地区： 广东工业大学自动化学院

出　　处： 《电力系统保护与控制》 2011年第1期23-28,共6页

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

领　　域： [电气工程]