Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance
© 2016 Elsevier B.V. Participation of plug-in electric vehicles (PEVs) is expected to grow in emerging smart grids. A strategy to overcome potential grid overloading caused by large penetrations of PEVs is to optimize their battery charge-rates to fully explore grid capacity and maximize the custome...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Elsevier BV
2016
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| Online Access: | http://hdl.handle.net/20.500.11937/21769 |
| _version_ | 1848750682834731008 |
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| author | Hajforoosh, S. Masoum, Mohammad Sherkat Islam, Syed |
| author_facet | Hajforoosh, S. Masoum, Mohammad Sherkat Islam, Syed |
| author_sort | Hajforoosh, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2016 Elsevier B.V. Participation of plug-in electric vehicles (PEVs) is expected to grow in emerging smart grids. A strategy to overcome potential grid overloading caused by large penetrations of PEVs is to optimize their battery charge-rates to fully explore grid capacity and maximize the customer satisfaction for all PEV owners. This paper proposes an online dynamically optimized algorithm for optimal variable charge-rate scheduling of PEVs based on coordinated aggregated particle swarm optimization (CAPSO). The online algorithm is updated at regular intervals of Δt = 5 min to maximize the customers’ satisfactions for all PEV owners based on their requested plug-out times, requested battery state of charges (SOCReq) and willingness to pay the higher charging energy prices. The algorithm also ensures that the distribution transformer is not overloaded while grid losses and node voltage deviations are minimized. Simulation results for uncoordinated PEV charging as well as CAPSO with fixed charge-rate coordination (FCC) and variable charge-rate coordination (VCC) strategies are compared for a 449-node network with different levels of PEV penetrations. The key contributions are optimal VCC of PEVs considering battery modeling, chargers’ efficiencies and customer satisfaction based on requested plug-out times, driving pattern, desired final SOCs and their interest to pay for energy at a higher rate. |
| first_indexed | 2025-11-14T07:40:43Z |
| format | Journal Article |
| id | curtin-20.500.11937-21769 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:40:43Z |
| publishDate | 2016 |
| publisher | Elsevier BV |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-217692018-09-07T00:38:04Z Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance Hajforoosh, S. Masoum, Mohammad Sherkat Islam, Syed © 2016 Elsevier B.V. Participation of plug-in electric vehicles (PEVs) is expected to grow in emerging smart grids. A strategy to overcome potential grid overloading caused by large penetrations of PEVs is to optimize their battery charge-rates to fully explore grid capacity and maximize the customer satisfaction for all PEV owners. This paper proposes an online dynamically optimized algorithm for optimal variable charge-rate scheduling of PEVs based on coordinated aggregated particle swarm optimization (CAPSO). The online algorithm is updated at regular intervals of Δt = 5 min to maximize the customers’ satisfactions for all PEV owners based on their requested plug-out times, requested battery state of charges (SOCReq) and willingness to pay the higher charging energy prices. The algorithm also ensures that the distribution transformer is not overloaded while grid losses and node voltage deviations are minimized. Simulation results for uncoordinated PEV charging as well as CAPSO with fixed charge-rate coordination (FCC) and variable charge-rate coordination (VCC) strategies are compared for a 449-node network with different levels of PEV penetrations. The key contributions are optimal VCC of PEVs considering battery modeling, chargers’ efficiencies and customer satisfaction based on requested plug-out times, driving pattern, desired final SOCs and their interest to pay for energy at a higher rate. 2016 Journal Article http://hdl.handle.net/20.500.11937/21769 10.1016/j.epsr.2016.08.017 Elsevier BV fulltext |
| spellingShingle | Hajforoosh, S. Masoum, Mohammad Sherkat Islam, Syed Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| title | Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| title_full | Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| title_fullStr | Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| title_full_unstemmed | Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| title_short | Online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| title_sort | online optimal variable charge-rate coordination of plug-in electric vehicles to maximize customer satisfaction and improve grid performance |
| url | http://hdl.handle.net/20.500.11937/21769 |