Distribution System Planning Considering Non-Utility-Owned Electric Vehicle Charging Stations

• Autor(a) principal: Mejia, Mario A. [UNESP]
• Data de Publicação: 2022
• Outros Autores: MacEdo, Leonardo H. [UNESP], Munoz-Delgado, Gregorio, Contreras, Javier, Padilha-Feltrin, Antonio [UNESP]
• Tipo de documento: Artigo de conferência
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1109/SEST53650.2022.9898149; http://hdl.handle.net/11449/249312
• topic: Distribution system planning; electric vehicle charging stations; mixed-integer linear programming; multi-objective optimization; stochastic optimization

This article proposes a new mixed-integer linear programming formulation for the planning of active distribution networks and non-utility-owned electric vehicle charging stations (EVCSs). The approach uses multi-objective optimization to consider both the utility's and the EVCSs owner's economic interests. In this context, the utility decides on investments in network assets, such as replacing overloaded conductors and installing capacitor banks and voltage regulators, whereas the EVCSs owner decides on EVCSs infrastructure such as land size and location, as well as the number of chargers to be constructed. The model is designed to reduce the total expected cost for both owners. A travel simulation algorithm provides the EVCSs' load profiles. Scenario-based optimization is used to address uncertainties related to the energy price at the substation, wind speed, solar irradiation, electricity demand, EVCSs load profiles, and plug-in electric vehicle adoption rate. The effectiveness of the proposed model has been proved on a 69-node network. Results show that the objectives of both owners are in conflict, both depending on the location of the EVCSs.