Open Access

ARTICLE

Optimization Configuration Method for Grid-Side Grid-Forming Energy Storage System Based on Genetic Algorithm

Yuqian Qi^*, Yanbo Che, Liangliang Liu, Jiayu Ni, Shangyuan Zhang

School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China

* Corresponding Author: Yuqian Qi. Email:

Energy Engineering 2025, 122(10), 3999-4017. https://doi.org/10.32604/ee.2025.068054

Received 20 May 2025; Accepted 21 July 2025; Issue published 30 September 2025

Abstract

The process of including renewable energy sources in power networks is moving quickly, so the need for innovative configuration solutions for grid-side ESS has grown. Among the new methods presented in this paper is GA-OCESE, which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks. This is one of the methods suggested in this study, which aims to enhance the sizing, positioning, and operational characteristics of structured ESS under dynamic grid conditions. Particularly, the aim is to maximize efficiency. A multiobjective genetic algorithm, the GA-OCESE framework, considers all these factors simultaneously. Besides considering cost-efficiency, response time, and energy use, the system also considers all these elements simultaneously. This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources. Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6% and reducing peak-load effects by 22.3%, GA-OCESE outperforms previous heuristic-based methods. This was found by contrasting the outcomes of the assessment with those of the evaluation. The results of the assessment helped to reveal this. The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable. This technology is particularly well-suited for smart grids, microgrid systems, and power infrastructures that heavily rely on renewable energy. Every technical component has been carefully recorded to ensure accuracy, reproducibility, and relevance across all power systems engineering software uses. This was done to ensure the program’s relevance.

---

Keywords

---