MILP-Based Allocation of Remote-Controlled Switches for Reliability Enhancement of Distribution Networks

Yu Mu, Dong Liang () and Yiding Song
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Yu Mu: State Key Laboratory of Intelligent Power Distribution Equipment and System, Hebei University of Technology, Tianjin 300401, China
Dong Liang: State Key Laboratory of Intelligent Power Distribution Equipment and System, Hebei University of Technology, Tianjin 300401, China
Yiding Song: State Key Laboratory of Intelligent Power Distribution Equipment and System, Hebei University of Technology, Tianjin 300401, China

Sustainability, 2025, vol. 17, issue 13, 1-22

Abstract: As the final stage of electrical energy delivery, distribution networks play a vital role in ensuring reliable power supply to end users. In regions with limited distribution automation, reliance on operator experience for fault handling often prolongs outage durations, undermining energy sustainability through increased economic losses and carbon-intensive backup generation. Remote-controlled switches (RCSs), as fundamental components of distribution automation, enable remote operation, rapid fault isolation, and load transfer, thereby significantly enhancing system reliability. In the process of intelligent distribution network upgrading, this study targets scenarios with sufficient line capacity and constructs a reliability-oriented analytical model for optimal RCS allocation by traversing all possible faulted lines. The resulting model is essentially a mixed-integer linear programming formulation. To address bilinearities, the McCormick envelope method is applied. Multi-binary products are decomposed into bilinear terms using intermediate variables, which are then linearized in a stepwise manner. Consequently, the model is transformed into a computationally efficient mixed-integer linear programming problem. Finally, the proposed method is validated on a 53-node and a 33-bus test system, with an approximately 30 to 40 times speedup compared to an existing mixed-integer nonlinear programming formulation. By minimizing outage durations, this approach strengthens energy sustainability through reduced socioeconomic disruption, lower emissions from backup generation, and enhanced support for renewable energy integration.

Keywords: distribution network reliability; remote-controlled switch; mixed-integer linear programming; McCormick relaxation; energy sustainability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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