ANN and ANFIS for Short Term Load Forecasting

Journal Title: Engineering, Technology & Applied Science Research - Year 2018, Vol 8, Issue 2

Abstract

Load forecasting has become one of the major areas of research in electrical engineering. Short term load forecasting (STLF) is essential for power system planning and economic load dispatch. 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 also includes comparison of various AI models. Our main objective is to develop the best suited model for MGVCL, by critically evaluating the ways in which the AI techniques proposed are designed and tested.

Authors and Affiliations

J. Chakravorty, S. Shah, H. N. Nagraja

Keywords

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  • EP ID EP168452
  • DOI -
  • Views 241
  • Downloads 0

How To Cite

J. Chakravorty, S. Shah, H. N. Nagraja (2018). ANN and ANFIS for Short Term Load Forecasting. Engineering, Technology & Applied Science Research, 8(2), -. https://europub.co.uk/articles/-A-168452