Abstract: Post-disaster power system restoration is challenged by the dual uncertainties of unit start-up times and load recovery amounts, which poses substantial threats to restoration security. Therefore, a source-load coordinated restoration strategy based on Information Gap Decision Theory(IGDT) robust optimization is proposed. Firstly, the possible fluctuation ranges of uncertain parameters are mathematically characterized. Subsequently, a multi-objective uncertain optimization model is established with the goals of maximizing both units restoration output and load-weighted restoration amount. Relying on the IGDT theory, this uncertainty model is transformed into a deterministic optimization problem that meets minimum restoration performance requirements, which is then efficiently solved using the Non-dominated Sorting Genetic Algorithm Ⅱ (NSGA-Ⅱ). The proposed approach achieves coordinated cross-time-step restoration of sources and loads, providing effective support for operators to develop restoration plans that balance security and efficiency. Case studies on the New England 10-machine 39-bus system validate the robustness and effectiveness of the strategy.

Key words: source-load coordinated restoration, robust optimization, information gap decision theory (IGDT), uncertainty multi-objective optimization model