A New Method for Reducing Uncertainty of Wind Power Based on Fuzzy RLS-MLFE

Due to incremental use of renewable energies, some challenges have been arised in control of wind power systems. One of the important ones is the uncertainty of wind power that affects directly on the cost of utilization. In this paper some algorithms based on the fuzzy logic and neural networks have been implemented to analyze the uncertainty of the wind power using historical data collected from a sample wind field. The algoriths are BLS, RLS, MLFE and ANN. Simulation results show that all of the methods results in acceptable outputs but the accuracy of the cobined RLS-MLFE is much better than the others.