This paper studies coordinated routing and charging/discharging scheduling of two mobile energy storage system (MESS) vehicles across three distribution networks (DNs) under load and renewable uncertainty. To avoid equal-weight limitations, a dual-dimension dynamic weighting strategy jointly uses network importance and real-time flexibility deficit. The optimization target is the total weighted system flexibility index (SFI) of the three-DN system, while DN-level SFIs are retained as component indicators for interpretation. SFI is defined by aggregating normalized upward and downward regulation capability of generation, demand response, stationary storage, and MESS over the scheduling horizon. The MESS spatiotemporal flexibility value is quantified by the difference between weighted SFI before and after MESS integration. A deterministic model and a stochastic extension with Monte Carlo scenario generation and forward scenario reduction are developed. In the revised case, 1000 raw uncertainty scenarios are reduced to 50 representative scenarios. Results show that MESS integration increases both expected and worst-case weighted SFI, and dynamic weights automatically shift toward high-deficit periods and critical DNs. Explicit route and state-of-charge trajectories provide implementable operating guidance.

Jiangtao Yin. Coordinated Scheduling of Two Mobile Energy Storage Vehicles for Maximizing Weighted SFI in Three Distribution Networks under Uncertainty. Academic Journal of Computing & Information Science (2026), Vol. 9, Issue 4: 21-29. https://doi.org/10.25236/AJCIS.2026.090403.

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