Short-term Load Forecasting Using the Adaptive Network-based Fuzzy Inference System

Abstract

The short-term load forecasting method plays an important role for electric utility that can help the electric utility to improve reliability and security of electricity supply. This paper proposed an adaptive network-based fuzzy inference system (ANFIS) based method for the short-term load forecasting. To evaluate the accuracy of the proposed ANFIS based forecasting method, the load data of a practical electrical power system was used. The accuracy of the proposed method was evaluated using two indices, namely the maximum absolute percentage error, and the mean absolute percentage error. The forecasting data are found to be in close agreement with the realistic data. The numerical simulation results show that the proposed approach may achieve quite satisfactory forecasting of load.

Authors and Affiliations

Wen-Yeau Chang .

Keywords

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  • EP ID EP240280
  • DOI -
  • Views 138
  • Downloads 0

How To Cite

Wen-Yeau Chang . (2017). Short-term Load Forecasting Using the Adaptive Network-based Fuzzy Inference System. International Journal of Electrical and Electronics Engineering Research (IJEEER), 7(4), 21-28. https://europub.co.uk/articles/-A-240280