Toward Sustainable Electricity Markets: Capacity-Based Pricing for Electric Vehicle Smart Charging

As electric vehicles (EVs) become more widespread, cities face the growing challenge of managing charging demand without overloading the grid. This study presents a novel information systems (IS) solution that supports smart and sustainable EV integration. The authors develop a capacity-based pricing model that adjusts in real time based on charging rates and grid capacity. Unlike many existing approaches, it avoids “avalanche effects” where synchronized charging behavior creates new demand peaks. The presented solution is also computationally efficient, making it practical for real-world use. Evaluated through simulations based on realistic urban scenarios, the model reduces demand volatility, aligns EV charging with renewable energy availability, and maintains overall charging costs for users. This work offers policy makers and energy providers a concrete tool to balance environmental goals with energy system reliability. For urban mobility planners, it provides a scalable, adaptive method to support the transition to cleaner urban mobility.

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Publication Details

Journal
Information Systems Research
Published
2025-06-24
DOI
https://doi.org/10.1287/isre.2023.0078
Citations
3
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
2.19
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article

Toward Sustainable Electricity Markets: Capacity-Based Pricing for Electric Vehicle Smart Charging

John Collins, Wolfgang Ketter, Gediminas Adomavičius, Konstantina Valogianni
3 citations
Information Systems Research
Electric Vehicles and Infrastructure
2.19
article

Toward Sustainable Electricity Markets: Capacity-Based Pricing for Electric Vehicle Smart Charging

John Collins, Wolfgang Ketter, Gediminas Adomavičius, Konstantina Valogianni
article en
3 citations

Abstract

As electric vehicles (EVs) become more widespread, cities face the growing challenge of managing charging demand without overloading the grid. This study presents a novel information systems (IS) solution that supports smart and sustainable EV integration. The authors develop a capacity-based pricing model that adjusts in real time based on charging rates and grid capacity. Unlike many existing approaches, it avoids “avalanche effects” where synchronized charging behavior creates new demand peaks. The presented solution is also computationally efficient, making it practical for real-world use. Evaluated through simulations based on realistic urban scenarios, the model reduces demand volatility, aligns EV charging with renewable energy availability, and maintains overall charging costs for users. This work offers policy makers and energy providers a concrete tool to balance environmental goals with energy system reliability. For urban mobility planners, it provides a scalable, adaptive method to support the transition to cleaner urban mobility.

Information Systems Research
IE University (ES), University of Minnesota (US), University of Cologne (DE), Decision Sciences (United States) (US)
Openalex Percentile: Top 12%
Electric Vehicles and Infrastructure
2.19
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