Publication
Multi-Scenario-Based Strategic Deployment of Electric Vehicle Ultra-Fast Charging Stations in a Radial Distribution Network
| dc.contributor.author | Nandi, Sharmistha | |
| dc.contributor.author | Ghatak, Sriparna Roy | |
| dc.contributor.author | Acharjee, Parimal | |
| dc.contributor.author | Lopes, Fernando | |
| dc.date.accessioned | 2024-10-02T13:50:35Z | |
| dc.date.available | 2024-10-02T13:50:35Z | |
| dc.date.issued | 2024-09 | |
| dc.description.abstract | ABSTRACT: In the present work, a strategic multi-scenario EV ultra-fast charging station (CS) planning framework is designed to provide advantages to charging station owners, Distribution Network Operators, and EV owners. Locations of CSs are identified using zonal division and the Voltage Stability Index strategy. The number of chargers is determined using the Harris Hawk Optimization (HHO) technique while minimizing the installation, operational costs of CS, and energy loss costs considering all the power system security constraints. To ensure a realistic planning model, uncertainties in EV charging behavior and electricity prices are managed through the 2m-Point Estimate Method. This method produces multiple scenarios of uncertain parameters, which effectively represent the actual dataset, thereby facilitating comprehensive multi-scenario planning. This study incorporates annual EV and system load growth in a long-term planning model of ten years, ensuring the distribution network meets future demand for sustainable transportation infrastructure. The proposed research work is tested on a 33-bus distribution network and a 51-bus real Indian distribution network. To evaluate the financial and environmental benefits of the planning, a cost-benefit analysis in terms of the Return-on-Investment index and a carbon emission analysis are performed, respectively. Furthermore, to prove the efficacy of the HHO technique, the results are compared with several existing algorithms. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | Nandi, S., Ghatak, S.R., Acharjee, P. & Lopes, F. (2024) Multi-Scenario-Based Strategic Deployment of Electric Vehicle Ultra-Fast Charging Stations in a Radial Distribution Network. In: Energies, 2024., vol.17 (17), article nº 4204. https://doi.org/10.3390/en17174204 | pt_PT |
| dc.identifier.doi | 10.3390/en17174204 | pt_PT |
| dc.identifier.eissn | 1996-1073 | |
| dc.identifier.uri | http://hdl.handle.net/10400.9/4361 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.publisher | MDPI | pt_PT |
| dc.relation.publisherversion | https://doi.org/10.3390/en17174204 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Distribution systems | pt_PT |
| dc.subject | Electric systems | pt_PT |
| dc.subject | Electric vehicles | pt_PT |
| dc.subject | Distribution network | pt_PT |
| dc.title | Multi-Scenario-Based Strategic Deployment of Electric Vehicle Ultra-Fast Charging Stations in a Radial Distribution Network | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.title | Energies | pt_PT |
| oaire.citation.volume | 17 | pt_PT |
| person.familyName | Lopes | |
| person.givenName | Fernando | |
| person.identifier.orcid | 0000-0002-2967-627X | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | a1153343-c1b9-406e-a83a-30dbee18d6a3 | |
| relation.isAuthorOfPublication.latestForDiscovery | a1153343-c1b9-406e-a83a-30dbee18d6a3 |