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一种求解环境经济负荷调度问题的人工神经网络新方法 被引量:15

A NEW ARTIFICIAL NEURAL NETWORK APPROACH TO ECONOMIC EMISSION LOAD DISPATCH
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摘要 提出了一种求解火力发电系统的环境经济负荷调度 (EELD)问题的新的人工神经网络方法。该方法可以克服传统神经网络方法引起的参数问题 ,而且不论其初始点是否位于可行域内 ,神经网络模型所表示的动态系统的状态都会快速收敛于对应的 EELD问题的全局最优解。文中还利用一个 In this paper, a new effective artificial neural network method is developed for the solution of economic emission load dispatch (EELD) problems of thermal generations. The proposed neural network can overcome numerical difficulty caused by traditional neural networks with network parameters and converges globally to the solutions of the EELD problem whether its initial points locate inside or outside the feasible region of the problem. The application and validity of the proposed algorithm are demonstrated for a sample system having three generators.
出处 《电力系统自动化》 EI CSCD 北大核心 2002年第21期45-48,共4页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目 (5 0 10 70 0 6 )
关键词 环境经济负荷调度 人工神经网络 全局收敛 电力系统 economic emission load dispatch (EELD) artificial neural network global convergence
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