Abstract
Short-term load forecasting (STLF) plays an important role in the operational planning security functions of an energy management system. The short term load forecasting is aimed at predicting electric loads for a period of minutes, hours, days or week for the purpose of providing fundamental load profiles to the system. The work presented in this paper makes use of PSO based local linear wavelet neural networks (LLWNN) to find the electric load for a given period, with a certain confidence level. The results of the new method show significant improvement in the load forecasting process.
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