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Forecasting of wind speed and wind power generation is indispensable for the effective operation of a wind farm and the optimal management of revenue and risks. Hybrid forecasting of time series data is considered to be a potentially effective alternative compared with the conventional single forecasting modeling approaches such as autoregressive integrated moving average (ARIMA) and artificial neural...
In this paper, wind speed and the power generated are predicted using phase space reconstruction and artificial neural network (ANN) method. First of all, data of wind speed is preprocessed with theory of phase space reconstruction to obtain the optimal length of time series for forecasting. And then, RBF artificial neural network is used to forecast the wind speed. Finally, the output power of a...
The development of wind generation has rapidly progressed over the last decade, the most important application for wind power prediction is to reduce the need for balancing energy and reserve power, which are needed to integrate wind power into the balancing of supply and demand in the electricity supply system. This paper presents a new method of wind power prediction in short-term with Artificial...
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