Business models for charging electric vehicles considering grid limitations

Growing wind and solar power in the Nordic power system tighten balancing needs and strain distribution capacity; hydropower alone cannot absorb this variability. Increased adoption of electric vehicles (EVs) offers an additional balancing resource, since EVs provide a large, distributed battery resource. This research develops technical and market-based tools to efficiently use EV flexibility to balance the grid through controlled charging, ancillary services, and local congestion management. First, residential charging models with Monte Carlo simulations show that grid-aware coordination prevents overloads and substantially lowers EV-owner costs, deferring grid reinforcement. Second, a mixed integer linear programming-based aggregator-planning framework optimizes participation in ancillary-service markets under uncertainties, improving grid utilization and economics. Third, an extended review of over 100 studies synthesizes business-model innovations for EV charging and identifies gaps in degradation remuneration, revenue sharing, and stakeholder coordination. Fourth, an optimization model for an energy hub that consists of battery energy storage and heavy-duty EV charging shows profitable operations within grid constraints while providing ancillary services. Finally, an aggregator planning model combining controlled charging with simplified and detailed battery degradation models achieves profitable operation and significant owner cost reductions, highlighting the need for fair degradation compensation and tariff-aligned pricing. Future work will quantify the trade-off between grid reinforcement and EV flexibility for optimal grid planning and validate the models on Swedish feeders with more realistic data and test systems.