Rapid Fault Restoration Strategy of Power System Based on Mobile Operation and Maintenance Base
Year: 2026
Type: article
Abstract: In recent years, power grids have grown increasingly complicated, and the rising penetration of new energy sources poses prominent risks to the secure and stable operation of power systems. As a critical technology for improving grid resilience and power supply reliability, mobile operation and maintenance bases are investigated in this paper, which proposes an optimal configuration method tailored to multi-scenario emergency power guarantee requirements of power systems. Monte Carlo sampling is adopted to simulate various fault scenarios, and a multi-index resilience evaluation system consisting of load loss rate, power shortage ratio and recovery indicators is established. On this basis, a pre-positioning optimization model is formulated to minimize the space–time scheduling cost of mobile operation and maintenance bases. To tackle the model complexity, nonlinear convergence factors and dynamic adaptive weight strategies are embedded into the conventional whale optimization algorithm, which improves the global search capability and convergence stability of the algorithm. Simulation results show that the proposed method outperforms the baseline case without mobile operation maintenance bases: system load curtailment drops from 1.27 MWh to 0.65 MWh, and the overall resilience index reaches 0.831, greatly boosting distribution network power recovery performance. In addition, the improved algorithm converges within 126 iterations. Compared with standard algorithms, it improves solving efficiency by 29.2% and cuts total scheduling cost by 15.8%, achieving a good trade-off between calculation precision and convergence speed.
Source: Processes
DOI: 10.3390/pr14172840
Institution: Shandong University of Science and Technology
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: China Southern Power Grid
Award: G8764251834
OpenAlex ID: W7208719219
