Hybrid Approaches for Wind Speed Forecasting in India. Long Term and Short Term Wind Speed Forecasting

      Аннотация: Economic development and energy consumption are directly proportional to each other. To meet the energy demands and to achieve sustainability, various countries are generating power using renewable energy. Among renewable energy, Wind energy is becoming the most critical source of electricity in various countries. One of the essential attributes of wind power generation is wind speed, and the wind speed is intermittent in nature. When wind energy is integrated into the power system, several issues are raised. The relevant issues are overcome by having accurate wind speed forecasting tools. This book outlines the bibliographical survey on various approaches to wind speed forecasting. Additionally, various metrics to assess the forecasting error are discussed. This book also helps wind farm owners to understand the current wind prediction models.Accurate prediction of wind speed is required as the wind power directly depends upon the wind speed. Due to the complex non-stationary and nonlinear characteristics of wind speed, it is not easy to get good prediction accuracy. Hybrid forecasting models always have higher accuracy in wind speed forecasting.

Ключевые слова: Hybrid decomposition technique (HDT), Selfish herd optimizer (SHO), Deep neural network (DNN), Multivariate empirical mode decomposition (MEMD), Enhanced empirical wavelet transform (EEWT), Intrinsic mode functions (IMFs), tabu search, General Regression Neural Network, Optimization technique, statistical measures