The Concept of Constructing an Artificial Dispatcher Intelligent System Based on Deep Reinforcement Learning for the Automatic Control System of Electric Networks

Abstract

The concept of the Artificial Dispatcher autonomous intelligent control system for integrating into modern automatic control systems of electric networks in order to improve the efficiency of managing the modes of electric power systems is proposed. This intelligent control system is implemented based on the deep machine learning technology and joint use of the Monte Carlo tree search method and deep artificial neural networks. It is shown that the efficient training of the Artificial Dispatcher intelligent control system is achievable through an innovative self-play algorithm, without using large databases of circuit-mode situations and expertise in managing the modes of electric power systems. Calculation examples of using agents created based on the concept of the Artificial Dispatcher intelligent control system in the problems of the automation of substation technological processes (managing voltage and reactive power controllers) and industrial enterprises (DC servomotor control) are presented.