Online Solving Of Economic Dispatch Problem Using Neural Network Approach And Comparing It With Classical Method

A. Mohammadi, M. Varahram, I. Kheirizad
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引用次数: 28

Abstract

In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and lambda iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for convergence is considerably smaller compared to classical methods
用神经网络方法在线求解经济调度问题并与经典方法比较
本研究比较了求解经济调度问题的两种方法,即Hopfield神经网络和lambda迭代法。考虑了3台、6台和20台电力系统的三个样本。计算了解决这两个系统的经济调度所需的CPU时间。研究表明,对于在线经济调度,Hopfield神经网络比经典方法更有效,收敛时间也更短
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