Short-term Wind Power Forecasting using Wavelet based Recurrent Wavelet Neural Network for Small-Scale Wind Turbine

To estimate wind energy availability for stable economic scheduling in the electricity market, it is necessary to forecast wind power. However, the uncertain nature of wind, makes the estimation difficult. So, to achieve good wind power estimation, a wind speed forecast is necessary. An hourly-based wind speed data is used to predict wind power up to 24 hours ahead for a small wind power plant $(\gt 5 kW)$. The proposed method consists of two steps as wavelet-based recurrent neural network (RWNN) is used for wind speed estimation and the second step uses these estimated speed samples to predict the wind turbine power. The results are compared to those obtained using the traditional RNN technique. The effectiveness of the result is shown by mean absolute error.