Abstract
AbstractAs a renewable energy source, wind power is considered to be a significant alternate source of energy in the times of energy crisis. As wind power penetration increases, power forecasting is crucially important for integrating wind power into a conventional power grid. A short-term wind farm power output prediction model is presented using a neural network optimized by a genetic algorithm (GA). Using wind data collected from a wind farm in Inner Mongolia of China, a power forecasting map is illustrated, and a comparative study between a Back-Propagation (BP) neural network model and a GA-BP neural network model is undertaken.KeywordsRenewable energywind farmpredictionArtificial Neural NetworkGenetic Algorithm
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