An overview of Artificial Intelligence applications to electrical power systems and DC microgrids

Abstract

Microgrids are composed of distributed energy resources such as energy storage devices, photovoltaic (PV) systems, backup generators, and wind energy conversion systems. Because renewable energy sources are intermittent, modern power networks must overcome the stochastic problem of increasing the penetration of renewable energy, which necessitates precise demand forecasting to deliver the best possible power supply. Technologies based on artificial intelligence (AI) have become a viable means of implementing and optimizing microgrid energy management. Owing to the sporadic nature of renewable energy sources, artificial intelligence offers a range of solutions based on the growth in sensor data and compute capacity to create sustainable and dependable power. Artificial intelligence (AI) techniques continue to evolve in DC Microgrids with the aim of perfect voltage profile, minimum distribution losses, optimal schedule of power, planning and controlling of grid parameters and lowering unit price. AI methods can improve DC Micro grid performance by monitoring and controlling the grid parameters by reducing the computational and processing time. This paper offers a comprehensive summary of some of the most recent research on artificial intelligence techniques used to DC Micro grids and electrical power system networks.