Load Forecasting using Fuzzy Logic Tool Box

Journal Title: GRD Journal for Engineering - Year 2018, Vol 3, Issue 8

Abstract

The main element for load forecasting is power system energy management system. Load forecasting helps to reduce the generation cost, spinning reserve capacity and increase the reliability of power system. The unit commitment, economic allotment of generation preservation schedule is crucial for short term load forecasting. In present many techniques have been used for load forecasting, but Artificial Intelligence Technique (Fuzzy Logic and ANN) gives better efficiency as contrast to conventional technique (Regression and Time Series). In this paper, the author main purpose is to reduce the error in the middle of the forecasted load and actual load value. The paper represents a technique of short term load forecasting using fuzzy logic. Using mamdani implication the fuzzy rule base are prepared. The software used for this is Matlab simulink and fuzzy tool box. By using triangular membership function the forecasted load results are obtained.

Authors and Affiliations

Manish Kumar Singla, Sikander Hans

Keywords

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  • EP ID EP375089
  • DOI -
  • Views 115
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How To Cite

Manish Kumar Singla, Sikander Hans (2018). Load Forecasting using Fuzzy Logic Tool Box. GRD Journal for Engineering, 3(8), 12-19. https://europub.co.uk./articles/-A-375089