AN INTELLIGENT LOAD SHEDDING SCHEME USING NEURAL NETWORKS AND NEURO-FUZZY

被引:19
作者
Haidar, Ahmed M. A. [1 ]
Mohamed, Azah [2 ]
Al-Dabbagh, Majid [2 ]
Hussain, Aini [2 ]
Masoum, Mohammad [3 ]
机构
[1] UMP, Fac Elect & Elect Engn, Kuantan, Pahang, Malaysia
[2] Univ Kebangsaan Malaysia, Bangi, Malaysia
[3] Curtin Univ Technol Perth, Perth, WA, Australia
关键词
Neural networks; neuro-fuzzy; feature extraction; load shedding; EXPERT-SYSTEM; LOGIC; MODEL; BACKPROPAGATION; ALGORITHMS; DESIGN;
D O I
10.1142/S0129065709002178
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power supply. This was confirmed by the results obtained in this research of which sample results are given in this paper.
引用
收藏
页码:473 / 479
页数:7
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