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《Power System Technology》 2002-03
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A SHORT-TERM LOAD FORECASTING METHOD BASED ON CASCADE NEURAL NETWORK

JIN Hai feng, XIONG Xin gen, WU Yao wu (Huazhong University of science and technology, Wuhan 430074, Hubei Province, China)  
To improve the defects in usually used BP algorithms, such as slow forecasting speed and easy to fall into local minimum, a Cascade Neural Network (CNN) load forecasting method is put forward in this paper. In this method the influences of weather factor and past load on load forecasting are separately considered, the RBF sub network is used to describe the relation between the past load and the forecasted load, the BP sub network is used to process the mapping relation between the weather factor and the forecasted load, and a cascade neural network is composed of the two above mentioned sub networks. The results of a series of experimental research show that this method is accurate and fast..
【CateGory Index】: TM714
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