POWER CONSTRAINT RESOLUTION METHODOLOGY FOR MULTI-REGIONAL FLEET ELECTRIFICATION INFRASTRUCTURE

Authors

Subhash Chandra
EV Fleet Technical Program Manager, Amazon.com

Keywords:

Fleet Electrification, Power Constraints, Grid Capacity, Decision Framework, Trade-Down Logic, Alternative Energy, Utility Coordination, Sensitivity Analysis

Synopsis

Commercial fleet electrification at scale confronts a persistent infrastructure challenge: utility power constraints that block or delay site energization. As fleet operators transition medium and heavy-duty vehicles to battery electric alternatives, the electrical demand at depot locations increases by five to ten times the baseline facility load, frequently exceeding available grid capacity. This paper presents a systematic, six-step trade-down resolution methodology for identifying, classifying, and resolving power constraints at fleet charging depot sites across multiple utility territories. The methodology incorporates a weighted multi-criteria decision framework for evaluating grid power against alternative energy solutions, validated through sensitivity analysis across 375 unique weighting scenarios. The framework provides fleet operators, utilities, and policymakers with a replicable, data-driven approach to unblocking electrification infrastructure at national scale.

References

[1] Alam, M.J.E., Muttaqi, K.M., and Sutanto, D. (2019). “A Novel Approach for Rescheduling Charging of Electric Vehicles in a Commercial Building with Solar PV and Battery Storage.” IEEE Transactions on Industrial Informatics, 15(7), pp. 3932–3942.

[2] Boardman, A.E., Greenberg, D.H., Vining, A.R., and Weimer, D.L. (2018). Cost-Benefit Analysis: Concepts and Practice. 5th ed. Cambridge University Press.

[3] ComEd. (2025). Beneficial Electrification Plan 2 (2026–2028): Commercial Fleet Charging Programs. Chicago, IL. ICC Docket No. 2025.

[4] Dufek, E.J., et al. (2023). “Developing Extreme Fast Charging Battery Technology: A Review of the Challenges and Opportunities.” Journal of the Electrochemical Society, 170(3), 030533.

[5] Edison Electric Institute (EEI). (2024). Electric Transportation: Utility Fleets and Infrastructure Investment.

Washington, DC.

[6] Electric Power Research Institute (EPRI). (2023). EVs2Scale2030: Scaling Electric Transportation Infrastructure. Palo

Alto, CA.

[7] Gamarra, C. and Guerrero, J.M. (2015). “Computational optimization techniques applied to microgrids planning: A review.” Renewable and Sustainable Energy Reviews, 48, pp. 413–424.

[8] Joint Office of Energy and Transportation. (2025). EV Charging Infrastructure: Permitting and Interconnection Timelines. Washington, DC.

[9] Muratori, M., et al. (2021). “The rise of electric vehicles: 2020 status and future expectations.” Progress in Energy, 3(2), 022002.

[10] National Renewable Energy Laboratory (NREL). (2024). Medium- and Heavy-Duty Vehicle Electrification: Infrastructure Requirements and Grid Impacts. Golden, CO. NREL/TP-5400-82081.

[11] Pohekar, S.D. and Ramachandran, M. (2004). “Application of multi-criteria decision making to sustainable energy planning: A review.” Renewable and Sustainable Energy Reviews, 8(4), pp. 365–381.

[12] U.S. Department of Energy (DOE). (2023). Transportation Energy Data Book. 41st ed. Oak Ridge National Laboratory. ORNL/TM-2023/1.

[13] U.S. Environmental Protection Agency (EPA). (2024). Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990–2022. EPA 430-R-24-004.

[14] Zhang, X., et al. (2022). “Fleet electrification infrastructure planning under uncertainty: A stochastic optimization approach.” Applied Energy, 324, 119748.

Published

August 29, 2026