Due to its intermittent nature, the optimal production of electricity from wind energy represents a real challenge for nowadays power systems. Whether isolated or grid-connected systems are considered, wind power sources can be profitable, but their intermittent output may lead to problems in terms of power quality and increased costs related to the operation of the grid and to the production of energy. This chapter discusses the choice of the most appropriate solutions for planning the electricity production from wind energy based on different algorithms for obtaining models based on principles used in artificial intelligence techniques such as recurrent neural networks (RNNs) and long short-term memory (LSTM) neural networks. We discuss the situation of obtaining the optimal model for estimating energy production based on a criterion or on multiple criteria: energy production history or energy production history correlated with different parameters describing the weather conditions.
Part of the book: Design Optimization of Wind Energy Conversion Systems with Applications