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Electrochemical energy storage (ES) units (e.g., batteries) have been field-validated as an efficient back-up resource that enhances resilience of distribution systems. However, using these units for resilience is insufficient to justify their installation economically and, therefore, these units are often installed in locations where they yield the greatest economic value during normal operations. Motivated by the recent progress in mobile ES technologies, i.e., ES units can be moved using public transportation routes, this paper proposes using this spatial flexibility to bridge the gap between the economically optimal locations during normal operations and the locations where extra back-up capacity is necessary during disasters. We propose a two-stage optimization model that optimizes investments in mobile ES units in the first stage and can re-route the installed mobile ES units in the second stage to form dynamic microgrids (MGs) and to avoid the expected load shedding caused by disasters. Since the proposed model cannot be solved efficiently with off-the-shelf solvers, even for relatively small instances, we apply the progressive hedging algorithm. The proposed model and algorithm are tested on a 15-bus radial distribution test system.
Kim et al. (2018) studied this question.