Open Access

ARTICLE

Flexible Matching of Maximum Service Restoration Strategies in Active Distribution Networks

Yi An¹, Litao Hong², Chun Chen^3,*, Zihan Zhang³, Yijia Cao³
1 Electric Power Science Research Institute of State Grid Jiangxi Electric Power Co., Ltd., Nanchang, China
2 China Energy Engineering Group Hunan Electric Power Design Institute Co., Ltd., Changsha, China
3 National Key Laboratory of Power Grid Disaster Prevention and Mitigation, Changsha University of Science and Technology, Changsha, China
* Corresponding Author: Chun Chen. Email:

Energy Engineering https://doi.org/10.32604/ee.2026.073739

Received 24 September 2025; Accepted 18 November 2025; Published online 29 July 2026

Abstract

With the rapid development and widespread application of distributed energy resources (DERs), service restoration in the distribution network has become more complex and challenging. This paradigm shift, while offering unprecedented opportunities for a cleaner and more resilient energy grid, has fundamentally altered the traditional, centralized approach to managing power outages. This paper addresses the issue that intentional islanding partition and network reconfiguration are not effectively integrated during service restoration, proposing a flexible matching method for maximizing service restoration in the active distribution network. Firstly, a fault branch variable based on the basic ring matrix of the distribution network is proposed. The fault restoration strategy is then determined using the decision tree presented in this paper, and different objective functions are formulated for various fault strategies. Secondly, photovoltaic (PV) units and Wind Turbines (WTs), emergency electric vehicles (EEVs), energy storage systems (ESSs), and controllable loads are analyzed and modeled for their output characteristics in service restoration by considering the participation of DERs. Then, considering the non-convexity in controllable loads and power flow constraints, relaxation techniques are applied to transform the problem into a mixed-integer second-order cone programming (MISOCP) model for the solution. Finally, case studies are conducted on the IEEE 69-bus and IEEE 33-bus systems to verify the effectiveness of the proposed model and method.

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Keywords

Intentional islanding partition; network reconfiguration; faulted branch variable; MISOCP planning; distributed energy resources

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