An Integrated GIS-AHP-Multi-Objective Optimization Approach for Sustainable High-Voltage Substation Siting

Optimal siting of high-voltage (HV) substations is a critical multi-criteria decision-making (MCDM) problem in power system planning with significant economic, technical, environmental, and social implications. This paper proposes a novel integrated framework combining Geographic Information Systems (GIS), the Analytical Hierarchy Process (AHP), and Multi-Objective Evolutionary Algorithms (MOEA) to address this complex problem. The proposed framework introduces a clear, three-phase operational pipeline: (1) expert-driven criterion weighting using AHP, (2) spatial feasibility and suitability screening using GIS, and (3) optimal trade-off analysis using a tailored multi-objective optimization model solved with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The core optimization model is formulated to minimize five explicit, quantifiable objectives: total land cost, total cable length, total compensation cost, average distance to load centers, and estimated power losses. The framework is validated through a comprehensive synthetic case study, with sensitivity analysis demonstrating its robustness. Results show that the proposed approach effectively generates a diverse Pareto-optimal front, providing planners with clear trade-off visualizations between economic investment and technical performance. The key contribution is the seamless integration of qualitative expert judgment, spatial constraints, and quantitative multi-objective optimization into a single, transparent decision-support system. Its modular design ensures direct applicability to a wide range of infrastructure siting problems beyond power systems.