A Fuzzy Neural Approach for Forecasting Peak Power Demands

Abstract

Accurate prediction of future electrical power demands greatly facilitates the task of power generation reliably and economically. In this paper, the new soft computing technologies, namely neuro-fuzzy techniques are adopted to improve precision of medium to long-term load forecasting. Performance of the proposed methodology is verified using simulations of some data pertaining to the Riyadh power system. This approach is compared with time series and neural networks design methods. It is demonstrated that the proposed methodology surpasses other methods by producing very accurate peak load forecasts. Keywords: Fuzzy logic, Neural networks, Neuro-fuzzy, Load forecasting