Optimal Planning of Autonomous Electric Vehicles Charging Stations with Photovoltaic Generations and Energy Storage Systems in Electric Distribution Systems
| dc.contributor.author | de Lima, Tayenne Dias [UNESP] | |
| dc.contributor.author | Ali, Haider | |
| dc.contributor.author | Soares, João | |
| dc.contributor.author | Franco, John F. [UNESP] | |
| dc.contributor.author | Francois, Bruno | |
| dc.contributor.author | Brotcorne, Luce | |
| dc.contributor.institution | Universidade Estadual Paulista (UNESP) | |
| dc.contributor.institution | Ecole Centrale de Lille | |
| dc.contributor.institution | Polytechnic of Porto | |
| dc.contributor.institution | INOCS | |
| dc.date.accessioned | 2025-04-29T20:10:35Z | |
| dc.date.issued | 2023-01-01 | |
| dc.description.abstract | With the anticipated growth in transport sector, emissions in this sector must be 20% by 2030, as required by Net Zero by 2050 Scenario. In this context, the electric vehicles (EVs) industry has grown in recent years, contributing to the developing of new technologies such as autonomous EVs (AEVs). Investment in AEVs charging infrastructure is a key point to support the integration of this new technology. Thus, a mixed-integer linear programming (MILP) model is proposed in this paper for the allocation of AEVs charging stations (AEVCS) equipped with PV generation and energy storage systems. Such technologies are scaled using the proposed model, considering uncertainties related to AEV demand and the renewable generation. Divisions by zone have been considered to distribute AEVCS over the system. Furthermore, environmental constraints are included in the model. Finally, results for applying the optimization model in the 69-bus system demonstrate the applicability of the proposed model. | en |
| dc.description.affiliation | Dept.of Electrical Engineering São Paulo State University | |
| dc.description.affiliation | L2EP Ecole Centrale de Lille | |
| dc.description.affiliation | LASI GECAD Polytechnic of Porto | |
| dc.description.affiliation | INRIA INOCS | |
| dc.description.affiliationUnesp | Dept.of Electrical Engineering São Paulo State University | |
| dc.identifier | http://dx.doi.org/10.1109/ISGTEUROPE56780.2023.10407249 | |
| dc.identifier.citation | IEEE PES Innovative Smart Grid Technologies Conference Europe. | |
| dc.identifier.doi | 10.1109/ISGTEUROPE56780.2023.10407249 | |
| dc.identifier.scopus | 2-s2.0-85187301309 | |
| dc.identifier.uri | https://hdl.handle.net/11449/307902 | |
| dc.language.iso | eng | |
| dc.relation.ispartof | IEEE PES Innovative Smart Grid Technologies Conference Europe | |
| dc.source | Scopus | |
| dc.subject | Autonomous electric vehicles | |
| dc.subject | Autonomous EV charging stations | |
| dc.subject | energy storage systems | |
| dc.subject | low carbon development strategy | |
| dc.subject | photovoltaic units | |
| dc.title | Optimal Planning of Autonomous Electric Vehicles Charging Stations with Photovoltaic Generations and Energy Storage Systems in Electric Distribution Systems | en |
| dc.type | Trabalho apresentado em evento | pt |
| dspace.entity.type | Publication |

