%0 Journal Article
%T Application of Hopfield neural network in unit commitment problem<br>Hopfield神经网络在机组组合问题中的应用
%A GAO Wei-xin
%A MU Xiang-yang
%A TANG Nan
%A YAN Hong-liang
%A <br>高炜欣
%A 穆向阳
%A 汤楠
%A 闫宏亮
%J 计算机应用
%D 2009
%I 
%X This paper presented an algorithm, based on multi-layer Hopfield neural network, for determining unit commitment. By constructing an appropriate energy function, a single layer Hopfield neural network can solve the problem of assigning output power of generators at any given time. Based on this single layer Hopfield neural network, a multi-layer Hopfield neural network was presented. The multi-layer Hopfield neural network can solve the problem of power system unit commitment. The energy functions of single layer and multi-layer Hopfield neural network and the corresponding algorithm were given. The restricted conditions of the balance between power supply and demand, maximum and minimum outputs of power plants were considered in the energy function. An example shows that the result got by Hopfield neural network is like to that got by genetic algorithm, but the calculation time is much less.
%K Hopfield neural network
%K unit commitment
%K optimization<br>Hopfield神经网络
%K 机组组合
%K 优化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=CDC71B5D04D3B63987DCF23F7E9D81AD&yid=DE12191FBD62783C&vid=771469D9D58C34FF&iid=E158A972A605785F&sid=5CC11A326E54A79A&eid=D7513DBF373F2B6C&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=17