Open Access

ARTICLE

An Upgrade Strategy for Active Distribution Networks Considering Probabilistic Power Flow

Xiaotong Li^1,2, Mingquan Qiu², Wenjun Zhang², Pengfei Li², Chong Liu², Chong Yang², Han Xiao², Feng Hu², Binghui Liu^1,*, He Wang¹

1 Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education (Northeast Electric Power University), Jilin, China
2 State Grid Beijing Electric Power Company, Beijing, China

* Corresponding Author: Binghui Liu. Email:

Energy Engineering 2026, 123(8), 7 https://doi.org/10.32604/ee.2026.071598

Received 08 August 2025; Accepted 29 September 2025; Issue published 12 July 2026

Abstract

To address the operational uncertainties and power quality challenges brought by high-penetration distributed energy integration into distribution networks, this paper proposes a precision renovation optimization method for active distribution networks (ADNs) that considers probabilistic power flow. First, based on probabilistic power flow analysis, a comprehensive power quality evaluation index system is constructed to accurately quantify the impact of uncertainties caused by photovoltaic fluctuations on distribution network power quality under high-penetration distributed photovoltaic (PV) scenarios. On this basis, a precision renovation optimization model is established with the goals of minimizing renovation cost, maximizing renewable energy hosting capacity, and optimizing the comprehensive power quality index, thereby achieving coordinated optimization of economic and operational performance. To address the challenges of solving this high-dimensional, mixed-variable, and strongly constrained model, an Adaptive and Feedback-enhanced Multi-strategy Particle Swarm Optimization (AFM-PSO) algorithm is proposed. This algorithm incorporates structured particle encoding, a dynamic information entropy feedback mechanism, and a local perturbation strategy, significantly improving search efficiency and convergence accuracy, making it suitable for rapidly solving complex distribution system renovation problems. Finally, the effectiveness of the proposed model and algorithm is verified using an IEEE 33-node distribution system with high-penetration PV integration as a simulation platform. The results demonstrate that the proposed method significantly enhances system voltage stability and renewable energy hosting capacity while controlling renovation costs, validating its superiority in achieving refined renovation and efficient operation of distribution networks.

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Keywords

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