Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions
Abstract In the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2021-09-01
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| Series: | Energy Informatics |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42162-021-00157-5 |
| _version_ | 1818715927518117888 |
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| author | Tayenne Dias de Lima John F. Franco Fernando Lezama João Soares Zita Vale |
| author_facet | Tayenne Dias de Lima John F. Franco Fernando Lezama João Soares Zita Vale |
| author_sort | Tayenne Dias de Lima |
| collection | DOAJ |
| description | Abstract In the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in the desired integration of this technology is to allocate EV charging stations (EVCSs). Efforts have been made towards the development of EVCSs, with the ability to recharge the vehicle at a similar time than conventional vehicle filling stations. Besides, EVs can bring environmental benefits by reducing greenhouse gas emissions. However, depending on the energy matrix of the country in which the EVs fleet circulates, there may be indirect emissions of polluting gases. Therefore, the development of this technology must be combined with the growth of renewable generation. Thus, this proposal aims to develop a mathematical model that includes EVs integration in the distribution system. To this end, a mixed-integer linear programming (MILP) model is proposed to solve the allocation problem of EVCSs including renewable energy sources. The model addresses the environmental impact and uncertainties associated with demand (conventional and EVs) and renewable generation. Moreover, an EV charging forecast method is proposed, subject to the uncertainties related to the driver's behavior, the energy required by these vehicles, and the state of charge of the EVs. The proposed model was implemented in the AMPL modelling language and solved via the commercial solver CPLEX. Tests with a 24-node system allow evaluating the proposed method application. |
| first_indexed | 2024-12-17T19:11:08Z |
| format | Article |
| id | doaj.art-78ab307db10c41628a33425a4ab5aa04 |
| institution | Directory Open Access Journal |
| issn | 2520-8942 |
| language | English |
| last_indexed | 2024-12-17T19:11:08Z |
| publishDate | 2021-09-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Energy Informatics |
| spelling | doaj.art-78ab307db10c41628a33425a4ab5aa042022-12-21T21:35:52ZengSpringerOpenEnergy Informatics2520-89422021-09-014S211810.1186/s42162-021-00157-5Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 EmissionsTayenne Dias de Lima0John F. Franco1Fernando Lezama2João Soares3Zita Vale4Departamento de Engenharia Elétrica, Universidade Estadual PaulistaEscola de Engenharia de Energia da Universidade Estadual PaulistaGECA D, Politécnico do PortoGECA D, Politécnico do PortoPolitécnico do PortoAbstract In the coming years, several transformations in the transport sector are expected, associated with the increase in electric vehicles (EVs). These changes directly impact electrical distribution systems (EDSs), introducing new challenges in their planning and operation. One way to assist in the desired integration of this technology is to allocate EV charging stations (EVCSs). Efforts have been made towards the development of EVCSs, with the ability to recharge the vehicle at a similar time than conventional vehicle filling stations. Besides, EVs can bring environmental benefits by reducing greenhouse gas emissions. However, depending on the energy matrix of the country in which the EVs fleet circulates, there may be indirect emissions of polluting gases. Therefore, the development of this technology must be combined with the growth of renewable generation. Thus, this proposal aims to develop a mathematical model that includes EVs integration in the distribution system. To this end, a mixed-integer linear programming (MILP) model is proposed to solve the allocation problem of EVCSs including renewable energy sources. The model addresses the environmental impact and uncertainties associated with demand (conventional and EVs) and renewable generation. Moreover, an EV charging forecast method is proposed, subject to the uncertainties related to the driver's behavior, the energy required by these vehicles, and the state of charge of the EVs. The proposed model was implemented in the AMPL modelling language and solved via the commercial solver CPLEX. Tests with a 24-node system allow evaluating the proposed method application.https://doi.org/10.1186/s42162-021-00157-5Allocation of electric vehicle charging stationsElectric vehicle charging stationsEV charging forecast methodRenewable energy sources |
| spellingShingle | Tayenne Dias de Lima John F. Franco Fernando Lezama João Soares Zita Vale Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions Energy Informatics Allocation of electric vehicle charging stations Electric vehicle charging stations EV charging forecast method Renewable energy sources |
| title | Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions |
| title_full | Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions |
| title_fullStr | Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions |
| title_full_unstemmed | Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions |
| title_short | Joint Optimal Allocation of Electric Vehicle Charging Stations and Renewable Energy Sources Including CO2 Emissions |
| title_sort | joint optimal allocation of electric vehicle charging stations and renewable energy sources including co2 emissions |
| topic | Allocation of electric vehicle charging stations Electric vehicle charging stations EV charging forecast method Renewable energy sources |
| url | https://doi.org/10.1186/s42162-021-00157-5 |
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