Designing a reliable electric vehicle charging station expansion under uncertainty

• Published in: International journal of production economics Vol. 236; p. 108132
• Main Authors: Quddus, Md Abdul, Shahvari, Omid, Marufuzzaman, Mohammad, Ekşioğlu, Sandra D., Castillo-Villar, Krystel K.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2021
• Subjects: Charging stations; Disruption prevention; Electric vehicles; Sample average approximation; Stochastic optimization; Charging stations; Electric vehicles; Disruption prevention; Stochastic optimization; Sample average approximation
• ISSN: 0925-5273; 1873-7579
• DOI: 10.1016/j.ijpe.2021.108132

This study proposes a novel disruption prevention model that considers both long-term expansion decisions and short-term operational decisions to design and manage an electric vehicle charging station network under power demand uncertainty. A non-linear term is introduced into the model to prevent the evolution of excessive temperature on a power line under different exogenous factors (e.g., outside temperature, air velocity). We first linearize the model using extensions of McCormick relaxation technique and then solve using a combined Sample Average Approximation with a Scenario Decomposition algorithm. A real life case study is presented to draw a several key managerial insights. It is observed that the disruption prevention model is able to reduce 16% overall system cost upon a power outage. The results of the analysis help decision-makers achieving a more reliable and cost-effective electricity supply network. •A disruption prevention model is proposed for EV charging station.•A hybrid decomposition algorithm is developed to solve the mathematical model.•A case study is constructed to visualize and validate the modeling results.•Several managerial insights are made based on our computational results.