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Short Term Load Forecasting Using Adaptive Neuro Fuzzy Interface

Journal: International Journal of Application or Innovation in Engineering & Management (IJAIEM) (Vol.7, No. 9)

Publication Date:

Authors : ;

Page : 030-035

Keywords : ;

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ABSTRACT Load forecasting has become one of the major areas of the research in the electrical engineering. Short-term load forecasting (STLF) is essential for effective power system planning, economic load dispatch, and unit commitment. A variety of mathematical methods has been developed for load forecasting. This paper discusses the influencing factors of STLF and an artificial intelligence (AI) based STLF model for MGVCL load. It includes Adaptive neuro-fuzzy interface approach applied for load forecasting. Our main objective is to develop the best suited STLF model for MGVCL, by critically evaluating the ways in which the AI techniques proposed are designed and tested Keywords: Short-term load forecasting, Power system Planning, Artificial Intelligence, Adaptive Neuro-Fuzzy Interface

Last modified: 2018-10-15 15:44:18