Resilience-driven planning in smart distribution systems: A multi-stage stochastic robust optimization framework for solar farm and battery integration

Grid planning decisions for resilience-enhancing assets such as solar farms frequently overlook the intricate operational dynamics and cascading failures that occur during the very hazard events they aim to mitigate. This paper introduces a novel, integrated multi-stage, bi-level stochastic robust optimization (SRO) framework that effectively addresses this critical gap. The proposed framework spans the full hazard–response horizon by coupling ex-ante strategic placement of solar farms and Battery Energy Storage Systems (BESS) with ex-post control and restorative actions, including: worst-case damage realization under an information-theoretic uncertainty budget with immediate system response optimization; autonomous self-healing via dynamic network reconfiguration; and joint crew routing/scheduling with time-coupled power flow control. To enable tractable computation, the nested bi-level SRO is reformulated as a single-level MILP, and strategic placement decisions are obtained via a discrete Differential Evolution algorithm. Other key novel contributions include the explicit integration of probabilistic structural vulnerabilities for both grid components and renewable assets in addition to high-resolution, data-driven operations—including hurricane-induced irradiance disruptions and BESS state-of-charge dynamics. Validation using realistic IEEE 33- and 118-bus testbeds demonstrates large, quantitative benefits, where optimal placement enhances system resilience by up to 126.5 % and reduces total event costs by up to 94.7 % compared to no-solar baselines; dynamic reconfiguration increases resilience by 7 %–14 % and reduces costs by 59 %–84 % relative to no-reconfiguration cases; recovery time drops from 63 h to 30 h under optimal solar/BESS deployment. The study further highlights the importance of this holistic, multi-stage approach, which yields a concentrated, strategic placement of assets, in contrast to the more distributed placements derived from simplified ‘damage-only’ models that are shown to result in up to 17.5 % lower resilience and 737 % higher total costs. Additionally, a comprehensive 25-year life-cycle cost-benefit analysis confirms the robust economic feasibility of these resilience-focused investments. These investments typically achieve break-even points within 12–24 years, even without accounting for market revenues, though this timeline is subject to variations in key cost and operational parameters. Comprehensive sensitivity studies—spanning uncertainty-budget, randomized infrastructure realizations, and battery replacement timing and cost variations—confirm solution robustness (resilience ≥91 %) and identify storage energy-capacity cost as the dominant economic driver in larger systems. The developed SRO framework serves as a powerful decision-support tool for enhancing the resilience of smart distribution networks, ensuring that strategic asset placements are cost-effective and remain robust against physical disruptions while incorporating complex operational realities.