МОДЕЛЬ АДАПТИВНОЙ СИСТЕМЫ УПРАВЛЕНИЯ ПОТОКОМ РЕАКТИВНОЙ МОЩНОСТИ НА ГРАНИЦЕ БАЛАНСОВОЙ ПРИНАДЛЕЖНОСТИ ПРЕДПРИЯТИЯ И СЕТЕВОЙ ОРГАНИЗАЦИИ

Abstract

The paper proposes the structure of the reactive power flow control system at a balance affiliation boundary of an enterprise and a grid operator. It deals with the features of neural networks and presents a numerical mathematical model based on an artificial neural network for adaptive control of reactive power flow. Training of the neural network is automated and implemented in software. Levenberg-Marquardt method is used for neural network training. The structure of the control system of reactive power flow and voltage levels is designed. A Levenberg-Marquardt method-based algorithm for neural network training is developed and implemented in software. The authors have proposed an adaptive control system of reactive power flow at the balance affiliation boundary of an enterprise and a grid operator based on the synthesis of the artificial neural network and STATCOM own logic.