DOE OSTI · 3005294
Recovery Simulator and Analysis Formulation: Mathematical Framework for Enhanced Resilience and Resource Allocation
Abstract
This report introduces recovery simulator and analysis (RSA), a framework aimed at enhancing the resilience of electrical grids post-disruption. The RSA model leverages an optimization problem formulation that focuses on maximizing the load served (or optionally customers served) through a coordinated and cooptimized recovery of non-black start generation, transmission lines, feeders and substations subject to labor budget constraints. By integrating advanced linear programming techniques, the simulator selects efficient reocovery pathways, optimizing both short-term and long-term grid recovery strategies. The mathematical framework guides decision-making through a comprehensive evaluation of potential recovery actions, factoring in the trade-offs between labor constraints and load (or optionally customer) restoration efficacy. This enables grid operators to simulate diverse outage scenarios and delineate optimal recovery pathways, thereby prioritizing critical repair tasks and ensuring resource allocation is both economical and effective. The intended use case of RSA is to allow planners to explore many recovery scenarios quickly and determine assets most critical across a wide range of scenarios, and therefore strong candidates for hardening or additional investment. RSA might also be used in an operational setting, following a single event, for exploring efficient recovery pathways.
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Maloney, Patrick R. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Zhao, Meng [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Ke, Xinda [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Mendez-Curbelo, Pablo R. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Sadnan, Rabayet [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Nassif, Alexandre B. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Guddanti, Kishan Prudhvi [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Mahapatra, Kaveri [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Vasios, Orestis [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Li, Xue (Michelle) [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Abdelmalak, Michael M. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Bereta dos Reis, Fernando [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Bedoya Ceballos, Juan C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)], Chalishazar, Vishvas H. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000248833509), Fan, Xiaoyuan [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)] (ORCID:0000000338688106), Elizondo, Marcelo A. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)]. 2025-10-31. Recovery Simulator and Analysis Formulation: Mathematical Framework for Enhanced Resilience and Resource Allocation. https://doi.org/10.2172/3005294
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