Intelligent phase symmetry algorithms in low-voltage networks with integrating PV panels

Abstract

Relevance: The development of distributed generation based on photovoltaic systems (PV) is causing new technical challenges in low-voltage electric networks. One of the key problems is the phase asymmetry caused by the uneven connection of single-phase PV. The asymmetry of voltages and currents leads to a deterioration in the quality of electricity, increased losses, overload of the neutral wire and a decrease in the reliability of the power supply. In these conditions, the task of developing effective phase symmetry methods that ensure the stable operation of the network and the integration of renewable energy becomes particularly relevant. One of the promising approaches is the use of intelligent control systems, in particular, fuzzy logic (FLC), for adaptive phase control and control of FES operating modes.

Aim: Development of an intelligent method for controlling phase symmetry in low-voltage networks with distributed solar integratsion based on the use of fuzzy logic (FLC) in order to minimize neutral current, increase phase symmetry and reduce losses in the system.

Methods: In the course of the research, MATLAB/Simulink modeling methods, the theory of indefinite sets, as well as phase symmetry algorithms were applied. A fuzzy logic (FLC) based controller has been developed. Results: The existing models and methods of complex optimization of short-term modes of electric power systems based on decomposition are improved. The results of the study of its effectiveness are presented using the example of an 8-node test scheme of the EPS.