Automatic Region-Based Layout Optimization of Substation Wiring Diagrams Via Improved Genetic Algorithms

This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method addresses the problems of low space utilization and rigid region division caused by template-based layouts. A two-segment chromosome structure is designed to encode both region assignment and interval ordering. The algorithm includes repair mechanisms and enhanced crossover and mutation operations to improve search efficiency and solution stability. In the layout modeling phase, interval units are abstracted as rectangular blocks to enable unified spatial representation. A set of graph-structured constraints, including voltage isolation, region boundary rules, and transformer area merging logic, are incorporated into the objective function as penalty terms. A case study on a 220kV substation shows that the proposed method results in better-balanced occupancy across regions and a more compact and readable layout. Experimental results demonstrate improvements of 11.6 percent in optimal performance and 24.2 percent in average performance compared to the standard genetic algorithm. The method proves effective for handling constrained and dynamically changing layout tasks in intelligent substation design.

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Publication Details

Published
2025-05-09
DOI
https://doi.org/10.1109/aemcse65292.2025.11042402
Citations
1
Primary Topic
Power Systems and Technologies
Type
article
Field-Weighted Citation Impact
0.73

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article

Automatic Region-Based Layout Optimization of Substation Wiring Diagrams Via Improved Genetic Algorithms

Zeliang Shen, Xiaofeng Xu, Jun Qin, Junyi Liu et al.
1 citations
Power Systems and Technologies
0.73
article

Automatic Region-Based Layout Optimization of Substation Wiring Diagrams Via Improved Genetic Algorithms

Zeliang Shen, Xiaofeng Xu, Jun Qin, Junyi Liu, Hao Ren, Cong Peng, Qing Fan
article en
1 citations

Abstract

This paper proposes an automatic region-based layout optimization method for substation main wiring diagrams using a improved genetic algorithm. The method addresses the problems of low space utilization and rigid region division caused by template-based layouts. A two-segment chromosome structure is designed to encode both region assignment and interval ordering. The algorithm includes repair mechanisms and enhanced crossover and mutation operations to improve search efficiency and solution stability. In the layout modeling phase, interval units are abstracted as rectangular blocks to enable unified spatial representation. A set of graph-structured constraints, including voltage isolation, region boundary rules, and transformer area merging logic, are incorporated into the objective function as penalty terms. A case study on a 220kV substation shows that the proposed method results in better-balanced occupancy across regions and a more compact and readable layout. Experimental results demonstrate improvements of 11.6 percent in optimal performance and 24.2 percent in average performance compared to the standard genetic algorithm. The method proves effective for handling constrained and dynamically changing layout tasks in intelligent substation design.

Shanghai Electric (China) (CN), Nanjing University of Aeronautics and Astronautics (CN)
Science and Technology Project of State Grid
Openalex Percentile: Top 27%
Power Systems and Technologies
0.73
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