14th IEEE PowerTech Conference, Madrid (Spain) Online. 27 June 2021
Given the rise of electric vehicle (EV) adoption, supported by government policies and dropping technology prices, new challenges arise in the modeling and operation of electric transportation. In this paper, we present a model for solving the EV routing problem while accounting for real-life stochastic demand behavior. We present a mathematical formulation that minimizes travel time and energy costs of a EV fleet.
The EV is represented by a battery energy consumption model. To adapt our formulation to real-life scenarios, customer pick-ups and drop-offs were modeled as stochastic parameters. A chance-constrained optimization model is proposed for addressing pick-ups and drop-offs uncertainties. Computational validation of the model is provided based on representative transportation scenarios. Results obtained showed a quick convergence of our model with verifiable solutions. Finally, the impact of electric vehicles charging is validated in Downtown Manhattan, New York by assessing the effect on the distribution grid.
Spanish layman's summary:
En este artículo, estudiamos el efecto de la adopción a gran escala de vehículos eléctricos en el funcionamiento de la red de distribución y en la reducción de las emisiones de carbono. Las incertidumbres en la demanda de servicios de transporte también se modelan para reflejar escenarios de la vida real.
English layman's summary:
In this paper, we study the effect of large-scale adoption of electric vehicles on the operation of the distribution grid and on curbing carbon emissions. Uncertainties in the demand for transport services are also modeled to mirror real life scenarios.
Keywords: Electric vehicle, Chance-constrained optimization, Vehicle routing problem
Publication date: June 2021.
O. Oladimeji, A. Gonzalez-Castellanos, D. Pozo, Y. Dvorkin, S. Acharya, Impact of electric vehicle routing with stochastic demand on grid operation, 14th IEEE PowerTech Conference - PowerTech 2021, Madrid (Spain) Online. 27 June - 02 July 2021. In: 2021 IEEE Madrid PowerTech: Conference proceedings, ISBN: 978-1-6654-1173-8