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《Transactions of China Electrotechnical Society》 2006-09
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Fuzzy Neural Network Load Modeling Based on Subtractive Clustering

Li Peiqiang1 Li Xinran1 Chen Huihua2 Tang Waiwen2 (1. Hunan University Changsha 410082 China 2. Hunan Province Dispatching Center Changsha 410077 China)  
Load model is a key factor to effect electric power stimulation. To obtain accurate load modeling, a new load modeling method is proposed in the paper, which is fuzzy neural network load modeling based-on Subtractive clustering. By analyzing input and output data, the paper sets up the mount function to classify its clustering number and adjust class center. In this way, the method confirms membership function parameters of the initial fuzzy load model. The method can obtain fuzzy rules through the neural network study to modeling data , optimize membership function parameter by amending the linkage proportion in the back prevalence algorithm。So it can identify the load model construct and attain optimal membership function parameter. The proposed method is proved valid by the engineering instance and it has high precision and fast convergence.
【Fund】: 高等学校骨干教师资助计划项目(教计司[2002]65号);; 湖南省教育厅重点项目(湘教通[2001]197号)
【CateGory Index】: TM743
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