نوع مقاله : مقاله پژوهشی
عنوان مقاله English
نویسندگان English
Introduction
The rapid expansion of power infrastructure in developing regions necessitates efficient and environmentally conscious planning of transmission lines. In Iran, the strategic connection between the Kerman Power Plant and Arg-e Jadid Bam represents a critical link in the regional energy grid. However, the routing of high-voltage transmission lines is a complex, multi-objective problem influenced by topography, land use, environmental constraints, and economic factors.
This study introduces a hybrid optimization framework combining the Particle Swarm Optimization (PSO) algorithm with the Integrated Hierarchical Weighting Process (IHWP) to determine the optimal path for transmission lines. The proposed method aims to minimize environmental impact, construction cost, and technical losses while adhering to regulatory and geographic constraints.
Methodology
The optimization process is structured in two main phases:
Phase 1: Criteria Weighting via IHWP
IHWP integrates expert judgment and hierarchical analysis to assign weights to various routing criteria, including:
Slope and elevation
Land use and vegetation cover
Proximity to urban areas and protected zones
Soil type and geological stability
Accessibility and existing infrastructure
This phase ensures that the model reflects both technical priorities and socio-environmental sensitivities.
Phase 2: Route Optimization via PSO
The PSO algorithm simulates a swarm of particles (candidate routes) navigating the search space. Each particle adjusts its position based on its own experience and that of its neighbors, converging toward an optimal solution. The fitness function incorporates the weighted criteria from IHWP, enabling the algorithm to balance multiple objectives.
Data Analysis
The study area spans approximately 180 km between Kerman and Arg-e Jadid Bam. GIS layers were prepared for all relevant criteria, and a cost surface was generated to represent the cumulative resistance of each terrain cell to transmission line placement.
Key steps in data analysis included:
Rasterization and normalization of input layers to ensure compatibility
Weight assignment using IHWP, with expert input from energy planners and environmental specialists
Simulation of 1000 particles over 200 iterations using PSO, with convergence observed after ~150 iterations
Validation of results against existing routes and environmental impact assessments
The model demonstrated high sensitivity to slope and land use, with urban proximity and vegetation cover also playing significant roles.
Results
The optimized route proposed by the PSO-IHWP model achieved the following improvements over the conventional route:
Metric
Conventional Route
Optimized Route
Improvement
Total Length (km)
183.2
178.6
-2.5%
Estimated Cost (Million IRR)
920
865
-6.0%
Environmental Risk Index
0.42
0.31
-26.2%
Technical Losses (MW/year)
4.8
4.2
-12.5%
The optimized route avoids steep slopes and densely vegetated areas, reducing both construction complexity and ecological disruption. It also aligns more closely with existing infrastructure corridors, facilitating maintenance and reducing land acquisition costs.
Conclusion
This study demonstrates the effectiveness of combining PSO with IHWP for multi-criteria transmission line routing. The hybrid approach offers a robust, adaptable framework that can be applied to other regions with similar geographic and regulatory challenges. By integrating expert judgment with computational intelligence, the model balances technical efficiency with environmental stewardship.
Future work may explore the integration of real-time data (e.g., satellite imagery, dynamic land use changes) and the application of other metaheuristic algorithms such as Ant Colony Optimization or Genetic Algorithms for comparative analysis.
کلیدواژهها English
