Authors: Wei Min Zhang; Yan Xia Zhang
Addresses: Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin, 300072, China ' Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, No. 92, Weijin Road, Nankai District, Tianjin, 300072, China
Abstract: In this paper, a novel method is proposed for real-time adaptive reactive power optimisation of photovoltaic systems derived from the improved dynamic teaching and learning reactive power optimisation based on moth-flame optimisation algorithm. By constructing the mathematical model for the reactive power voltage control of a photovoltaic power station, learning is optimised continuously in the process of teaching and learning. According to real-time data, the optimal cooperation strategy between the RPVC/AVC control system and intelligent power grid command is formed, and real-time, adaptive and dynamic control of the system is realised. A simulation study is made in this paper, and the simulation results show that the proposed method is reasonable and effective for the 220 kV substation and its feeder system.
Keywords: moth-flame optimisation algorithm; dynamic teaching and learning reactive power optimisation; photovoltaic; reactive; power and voltage coordinated; automatic voltage control; AVC.
International Journal of Simulation and Process Modelling, 2020 Vol.15 No.1/2, pp.145 - 154
Received: 12 Nov 2018
Accepted: 02 Jun 2019
Published online: 21 Apr 2020 *