ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 13 - 2025 | doi: 10.3389/fenrg.2025.1640949
This article is part of the Research TopicGrid Stability and Optimized Operation in Renewable Energy Grid SystemsView all articles
Frequency Coordinated Control and Parameter Optimization for Photovoltaic-Energy Storage Systems Based on a GA-BP Hybrid Algorithm
Provisionally accepted
Runzhi MU1Hongchun SHU2Yuming ZHANG1Xiongbiao WAN1
Shunji LUO2*Zichao ZHOU1Guangxue WANG2Shunguang LEI2- 1Yunnan Electric Power Test and Research Institute (Group) Co., Ltd., kunming, China
- 2Kunming University of Science and Technology, Kunming, China
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To address the issue of frequency oscillations caused by stochastic disturbances in grid-connected photovoltaic systems, this paper proposes a GA-BP neural network-based adaptive optimization strategy for photovoltaic-energy storage systems (PV-ESS). First, the working principles and characteristics of virtual synchronous generator (VSG) technology are elaborated. Second, the power control point positioning under deloading operation of PV systems and the virtual inertia control of energy storage systems are analyzed. Subsequently, a GA-BP neural network is introduced and applied to the adaptive parameter design of the PV-ESS system, enabling real-time dynamic adjustment of the moment of inertia J, damping coefficient D, and virtual inertia coefficient K, thereby enhancing the dynamic response performance of active power. Finally, experimental results demonstrate that under active power command mutation scenarios, compared with fixed-parameter control strategies, the proposed strategy reduces the frequency nadir deviation by 14.81%, overshoot by 62.5%, and steadystate recovery time by 44.44%, effectively validating its superiority and effectiveness.
Keywords: Coordinated PV-ESS Control, Frequency regulation, GA-BP neural network, Deloading control, dynamic parameters
Received: 04 Jun 2025; Accepted: 30 Jun 2025.
Copyright: © 2025 MU, SHU, ZHANG, WAN, LUO, ZHOU, WANG and LEI. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Shunji LUO, Kunming University of Science and Technology, Kunming, China
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