Open Access

ARTICLE

Bi-Objective Optimization of Distribution Network Reliability Enhancement Using Quantitative Decomposition

Chenying Yi¹, Yangjun Zhou^1,2, Wei Zhang¹, Like Gao¹, Hongwen Wu³, Yuanchao Zhou^4,*, Ke Zhou¹, Weixiang Huang¹, Juntao Pan⁵, Shan Li¹, Bin Feng⁵

1 Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment, Electric Power Research Institute of Guangxi Power Grid Co., Ltd., Nanning, 530001, China
2 School of Electrical Engineering, Chongqing University, Chongqing, 400044, China
3 Wuzhou Power Supply Bureau of Guangxi Power Grid Co., Ltd., Wuzhou, 543099, China
4 Nanning Power Supply Bureau of Guangxi Power Grid Co., Ltd., Nanning, 530031, China
5 Guangxi Power Grid Co., Ltd., Nanning, 530015, China

* Corresponding Author: Yuanchao Zhou. Email:

(This article belongs to the Special Issue: Innovations and Challenges in Smart Grid Technologies)

Energy Engineering 2026, 123(8), 13 https://doi.org/10.32604/ee.2025.073805

Received 25 September 2025; Accepted 24 November 2025; Issue published 12 July 2026

Abstract

Ensuring reliability in distribution networks is essential under increasing operational and economic constraints. Traditional planning models rely on power flow calculations, leading to high computational costs and poor scalability. This study proposes a quantitative decomposition framework that establishes a direct linkage among reliability improvement measures, reliability parameters, and reliability indices, enabling fast and analytical reliability evaluation without power flow analysis. A bi-objective optimization model is developed to minimize both reliability indices (SAIDI) and investment costs, solved using Pareto-based multi-objective PSO combined with the TOPSIS method. Case studies on a 519-node distribution network demonstrate that the proposed approach achieves significant reliability improvement with superior computational efficiency, offering a practical and scalable tool for reliability-oriented distribution planning.

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Keywords

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