Application of a fuzzy model for short-term load forecast with group method of data handling enhancement

In this paper, a fuzzy model with the enhancement of group method of data handling is applied for short-term load forecast of a power system. In the approach, the group method of data handling is applied to formulate a fitting function that finds the relationship between linguistic values of input and output. Suitable inputs can be thus determined such that the number of redundant inputs is reduced. Moreover, as the properties of input variables are embedded with the weighting values of output, additional efforts of adjusting parameters of fuzzy membership functions can also be saved. The salient feature of this method lies in that an unknown system can be modeled at ease with a fewer number of rules, thereby reducing the computation time. By performing the simulations through the utility data, test results demonstrate the effectiveness of the proposed method, hence solidifying the feasibility of the method for the application considered.

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