Layout Optimization of 500kV Substation Main Wiring Diagrams Based on Enhanced Genetic Algorithm

This paper proposes a structure-aware layout optimization method for 500kV substation main wiring diagrams based on an enhanced genetic algorithm. Substation Configuration Description (SCD) files, which encode the logical topology and equipment relationships in XML format, are parsed to extract voltage levels, bay units, and device connections. A geometric modeling framework is then constructed to abstract the layout into structured regional blocks. A two-segment chromosome encoding is designed to represent both region assignment and intra-region ordering. The optimization process incorporates a bi-objective fitness function, considering load imbalance and logical connection distance, to guide the search toward spatially balanced and topologically compact layouts. Graph-guided repair and region-aware perturbation strategies are introduced to improve convergence stability and layout feasibility. Experimental validation on a 500kV substation demonstrates that the proposed method achieves better space distribution and faster convergence compared to standard genetic algorithms, offering practical value for automated layout generation in intelligent substation design.