TY - JOUR
T1 - Cost-Optimized Rural Electrification Networks Using Hybrid Genetic PathFinding Methods
AU - Fatima Zahra
AU - Youssef Idrissi
JF - Journal of Smart Grids, Energy Analytics and Optimization
JO - J Smart Grids Energy Anal Optim
Y1 - 2025
VL - 4
IS - 2
SP - 113
N2 - Networked rural electrification offers an alternative strategy to speed up electricity access in rural regions. By leveraging satellite imagery and GIS tools, an electrical distribution network links villages to suitably positioned generation facilities, thereby reducing overall electrification costs. The network design process begins by determining optimal paths between all node pairs, after which a cost-minimizing network topology is selected. Previous studies have shown that the A* (A-star) optimal pathfinding algorithm performs poorly in this context due to the intricate topography of rural settings. Although the multiplier-accelerated A (MAA) algorithm addresses major performance limitations, it still produces only a single path for each node pair, as with standard A. Depending on a single path, project risk increases, as various complications—such as inaccurate GIS data, unforeseen soil conditions, land rights conflicts, political obstacles, and others—may arise during actual implementation. This paper introduces a hybrid pathfinding technique that integrates a genetic algorithm with the A/MAA algorithm. The new method generates a set of near-optimal paths rather than a single optimal route for each connection. Having multiple path options enables project teams to respond rapidly to unforeseen challenges as new data emerges and to modify the network topology before or during construction with only minor effects on total project cost.
UR - https://isespub.com/b709958176
ER -