Machine Learning And Optimization With Applications Of Power System Iii

This Special Issue focuses on machine learning and optimization techniques that can be applied to power system operation, such as energy data analytics, time series energy forecasting, renewable energy markets, energy storage systems, microgrids, and distribution networks. Deep learning techniques, such as recurrent neural networks, long short-term memory, and convolution neural networks, are being used to predict renewable generation and electric loads. Additionally, energy storage systems are being deployed to control the grid under volatile generation and loads. Finally, optimal power flow and peer-to-peer energy trading are of great interest for distribution networks and/or microgrids.