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Article: Dynamic resource allocation for parking lot electric vehicle recharging using heuristic fuzzy particle swarm optimization algorithm
Title | Dynamic resource allocation for parking lot electric vehicle recharging using heuristic fuzzy particle swarm optimization algorithm |
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Authors | |
Keywords | Electric vehicleHeuristics Parking lot Dynamic resource allocation Particle swarm optimization Fuzzy system |
Issue Date | 2018 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/asoc |
Citation | Applied Soft Computing, 2018, v. 71, p. 538-552 How to Cite? |
Abstract | A parking lot (PL) dynamic resource allocation system for recharging electric vehicles (EVs) is introduced in this paper. For scheduling purposes, a day is divided into sequential timeslots. At the beginning of each timeslot, the dynamic system can determine an optimal charging schedule for that timeslot, as well as plan for subsequent timeslots. An EV may arrive at a PL with or without an appointment. Considering the variation in electricity prices during the day, the objective is to minimize the cost of electricity used to charge EVs by scheduling optimal electric quantities at the parking timeslots of each EV. The optimal solution satisfies the EV’s charging rate limit and the PL’s transformer limit. Based on particle swarm optimization (PSO), fuzzy systems and heuristics, this paper describes a heuristic fuzzy particle swarm optimization (PHFPSO) algorithm to solve the optimization problem. From the case studies, the results show the proposed dynamic resource allocation system has a significant improvement in satisfying charging requests and in reducing the electricity cost of the PL when compared with other scheduling mechanisms. |
Persistent Identifier | http://hdl.handle.net/10722/259322 |
ISSN | 2023 Impact Factor: 7.2 2023 SCImago Journal Rankings: 1.843 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Wu, H | - |
dc.contributor.author | Pang, GKH | - |
dc.contributor.author | Choy, KL | - |
dc.contributor.author | Lam, HY | - |
dc.date.accessioned | 2018-09-03T04:05:12Z | - |
dc.date.available | 2018-09-03T04:05:12Z | - |
dc.date.issued | 2018 | - |
dc.identifier.citation | Applied Soft Computing, 2018, v. 71, p. 538-552 | - |
dc.identifier.issn | 1568-4946 | - |
dc.identifier.uri | http://hdl.handle.net/10722/259322 | - |
dc.description.abstract | A parking lot (PL) dynamic resource allocation system for recharging electric vehicles (EVs) is introduced in this paper. For scheduling purposes, a day is divided into sequential timeslots. At the beginning of each timeslot, the dynamic system can determine an optimal charging schedule for that timeslot, as well as plan for subsequent timeslots. An EV may arrive at a PL with or without an appointment. Considering the variation in electricity prices during the day, the objective is to minimize the cost of electricity used to charge EVs by scheduling optimal electric quantities at the parking timeslots of each EV. The optimal solution satisfies the EV’s charging rate limit and the PL’s transformer limit. Based on particle swarm optimization (PSO), fuzzy systems and heuristics, this paper describes a heuristic fuzzy particle swarm optimization (PHFPSO) algorithm to solve the optimization problem. From the case studies, the results show the proposed dynamic resource allocation system has a significant improvement in satisfying charging requests and in reducing the electricity cost of the PL when compared with other scheduling mechanisms. | - |
dc.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/asoc | - |
dc.relation.ispartof | Applied Soft Computing | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Electric vehicleHeuristics | - |
dc.subject | Parking lot | - |
dc.subject | Dynamic resource allocation | - |
dc.subject | Particle swarm optimization | - |
dc.subject | Fuzzy system | - |
dc.title | Dynamic resource allocation for parking lot electric vehicle recharging using heuristic fuzzy particle swarm optimization algorithm | - |
dc.type | Article | - |
dc.identifier.email | Pang, GKH: gpang@eee.hku.hk | - |
dc.identifier.authority | Pang, GKH=rp00162 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1016/j.asoc.2018.07.008 | - |
dc.identifier.scopus | eid_2-s2.0-85050299702 | - |
dc.identifier.hkuros | 289919 | - |
dc.identifier.volume | 71 | - |
dc.identifier.spage | 538 | - |
dc.identifier.epage | 552 | - |
dc.identifier.isi | WOS:000445126100036 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.issnl | 1568-4946 | - |