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標題Title: Artificial Neural Network Based Adaptive Load Shedding for an Industrial Cogeneration Facility
作者Authors: 許振廷,Hui-Jen Chuang..等
上傳單位Department: 電機工程系
上傳時間Date: 2009-11-16
上傳者Author: 許振廷
審核單位Department: 電機工程系
審核老師Teacher: 許振廷
檔案類型Categories: 論文Thesis
關鍵詞Keyword: Load shedding, Artificial neural networks, Cogeneration
摘要Abstract: Abstract—This paper presents the design of adaptive loadshedding strategy by executing the artificial neural network (ANN) and transient stability analysis for an Industrial cogeneration facility. To prepare the training data set for ANN, the transient stability analysis has been performed to solve the minimum load shedding for various operation scenarios without causing tripping problem of cogeneration units. Various training algorithms have been adopted and incorporated into the backpropagation learning algorithm for the feed-forward neural networks. By selecting the total power generation, total load demand and frequency decay rate as the input neurons of the ANN, the minimum amount of load shedding is determined to maintain the stability of power system. To demonstrate the effectiveness of the ANN minimum load-shedding scheme, the traditional method and the present load shedding schemes of the selected cogeneration system are also applied for comparison and verification of the proposed methodology.

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2009_11_8373c0ea.pdf 246Kb pdf 791 485
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