Short Term Load Forecasting of Chhattisgarh Grid Using Adaptive Neuro Fuzzy Inference System
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 11)Publication Date: 2015-11-05
Authors : Saurabh Ghore; Amit Goswami;
Page : 841-846
Keywords : Short Term Load Forecasting; State Load Dispatch Centre; Adaptive Neuro Fuzzy Inference System; Training; Testing; Simulation; Grid Partitioning; Subtractive Clustering; Mean Absolute Percentage Error;
Abstract
Electrical load forecasting is the process of predicting future electrical load demand on the basis of given historical load information. Load forecasting is an essential and integrated process in planning and operation of electric power utilities. The basic quantity of interest in load forecasting is typically the time period in relation to the load demand studied. Power sector is highly capital intensive and entire planning of generation, transmission and distribution follows an axiomatic approach based on load forecasting. Short-term load forecasting is used in power system for real-time control, security, optimal unit commitment, economic scheduling, maintenance, energy management and power-plant structure planning etc. In this research work Short-Term Load Forecasting of Chhattisgarh Grid is done by using the data obtained from State Load Dispatch Centre (SLDC) of Chhattisgarh State Power Transmission Company Limited (CSPTCL). Adaptive Neuro Fuzzy Inference System (ANFIS) is used in MATLAB to train, test and simulate the data obtained from SLDC Chhattisgarh.
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