A Geospatial Heuristic-Based Service for Resilient Electricity Infrastructures in Varying Environments

High-impact events such as those related to climate change can cause significant damage to critical infrastructure assets. Given the complexity of these systems and their interconnections, considerable time is required for their full restoration. This paper presents a geospatial-based tool that can be incorporated into a decision support system devoted to planning resilient electricity infrastructures. The tool addresses the optimization problem of the service restoration within the operational resilience function, especially when human intervention is required. Environmental and human factors are considered, as well as resource availability, that influence the intervention procedures. The tool computes multi-modal transportation plans and travel times for maintenance crews to reach the asset locations. Then, geospatial heuristic search algorithms are used to estimate the time needed to traverse untracked paths for which no information is directly provided by currently available navigation services. This tool can be useful for exploring new areas for network expansion and/or re-planning emergency procedures in environments altered by disasters.