Techno-Economic Analysis of Shared Mobile Storage for Demand Charge Reduction

This paper investigates the techno-economic viability of shared electric vehicle (EV) fleets for demand charge reduction under practical logistical and operational constraints. Unlike idealized models that overlook transit overheads, we propose a high-fidelity fleet management framework that explicitly accounts for the spatio-temporal coupling of energy consumption, labor costs for EV drivers, and battery degradation. We formulate the dispatch problem as a mixed-integer linear program (MILP) that jointly minimizes demand charges and total cost of ownership. To address the computational complexity arising from path-dependent constraints, we develop a marginal-value-based heuristic algorithm that achieves near-optimal performance (gap < 4.8%) with high computational efficiency. Using real-world data from San Francisco, our analysis reveals that a modest number of EVs can achieve significant demand charge savings, sufficient to recover the ownership and operational expenses. Our results also show how tariff structures, fleet size, and cost components influence overall profitability.