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《Power System Technology》 2000-12
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A RESEACH OF AN INTEGRATED INTELLIGENT SYSTEM FOR SHORT-TERM ELECTRIC LOAD FORECASTING

ZHAO Hai dan, WU Jie, YANG Ping, YAN Hua (Electrical Institute, South China University of Technology, Guangzhou 510641, Guangdong Province, China)  
An integrated intelligent modularization system for short termpower loadforecasting is presented in this paper. The first module of the system is based on artificial neural network. The second module is based on fuzzy logic system. The third module is an accessory fuzzy expert system that can be used to update the result of load forecasting in allusion to the shortcoming of the above mentioned technique. When the weather is steady and there isn't any special event, it is appropriate to forecast the load from Tuesday to Saturday using the method of both fuzzy logic system and artificial neural network without updating by fuzzy expert system. As to the load of Sunday and Monday, and that of other particular days on which remarkable change of weather occurs or some special event happen, it is necessary to update the forecasting result by use of fuzzy expert system. As an example, this system has been used to calculate the daily load of a provincial power network, the result shows that satisfactory forecasting accuracy can be achieved by this system. A practical software package of this system is put into test run.
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