A Two-Stage Location-Allocation Optimization Method for Fixed UAV Nests in Power Inspection Considering Node Failure Scenarios
This paper explores the configuration and deployment of UAV nests for power inspection operations, focusing on potential nest failures. It proposes a two-stage location-allocation method. The problem is divided into two subproblems, each modeled as an integer linear programming (ILP) problem. The fi...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/4/1089 |
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| Summary: | This paper explores the configuration and deployment of UAV nests for power inspection operations, focusing on potential nest failures. It proposes a two-stage location-allocation method. The problem is divided into two subproblems, each modeled as an integer linear programming (ILP) problem. The first subproblem identifies the minimal set of nodes for nest construction using the commercial solver Gurobi. The second subproblem involves UAV nest type selection and task allocation, solved with an ILS-SA heuristic algorithm. A case study in China shows that our method reduces total costs by 33.9% and decreases the number of UAV nests by 32% compared to the current greedy deployment method used by the power grid company. These results demonstrate the effectiveness and practicality of our approach in improving the reliability and cost-efficiency of UAV-based power inspection systems. |
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| ISSN: | 1424-8220 |