Load Forecasting using Fuzzy Logic Tool Box
Manish Kumar Singla, Thapar Institute of Engineering and Technology,Patiala; Sikander Hans ,Thapar Institute of Engineering and Technology,Patiala
Component, Fuzzy Logic, Short Term Load Forecasting, Absolute Percentage Error, Fuzzy Interface System, Mamdani
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.
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Paper ID: GRDJEV03I080034
Published in: Volume : 3, Issue : 8
Publication Date: 2018-08-01
Page(s): 12 - 19
Published in: Volume : 3, Issue : 8
Publication Date: 2018-08-01
Page(s): 12 - 19