Topology Design and Operation of Distribution Network Based on Multi-Objective Framework and Heuristic Strategies

Qingxia Li (), Shengjun Huang, Xueyang Zhang, Wenhua Li, Rui Wang and Tao Zhang
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Qingxia Li: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Shengjun Huang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Xueyang Zhang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Wenhua Li: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Rui Wang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
Tao Zhang: College of Systems Engineering, National University of Defense Technology, Changsha 410073, China

Mathematics, 2024, vol. 12, issue 13, 1-21

Abstract: This work elucidates a methodological approach employed in the process of planning the expansion of distribution network (DN) lines, wherein the amalgamation of system reconfiguration capabilities with operational equilibrium and reliability is paramount. The expansion proposals for the DN and the radial operation schemes post-expansion are encompassed. We formulate a bi-objective DN planning optimization model that concurrently addresses resource optimization configuration and operational optimization. Subsequently, the NSGA-II algorithm is employed to solve the optimization model, providing a coordinated presentation of multiple alternative solutions. However, this problem diverges from conventional bi-objective optimization problems due to its nature as a bi-objective optimization problem with embedded sub-optimization problem, consequently imposing a substantial computational burden. To address this issue, heuristic algorithms are designed to optimize system operational configuration, which is regarded as a sub-optimization problem. The proposed metric, model, and algorithms are validated on two case studies using the IEEE 33-bus and 70-bus test systems. Notably, the proposed method achieves solution efficiency by over 200 times compared to existing methods.

Keywords: topology optimization; distribution network; heuristic algorithms; evolutionary multi-objective optimization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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