Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators
This study aims to develop an electricity pricing and multi-objective optimization strategy that can be applied to integrated electric vehicle charging stations (IEVCS) that include photovoltaic (PV) systems and a range of multiple energy storage options. The strategy balances the interests of both...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-08-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525003606 |
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| _version_ | 1850117463835934720 |
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| author | Qin Yan Jinxin Wang Tao Lin Archie James Johnston |
| author_facet | Qin Yan Jinxin Wang Tao Lin Archie James Johnston |
| author_sort | Qin Yan |
| collection | DOAJ |
| description | This study aims to develop an electricity pricing and multi-objective optimization strategy that can be applied to integrated electric vehicle charging stations (IEVCS) that include photovoltaic (PV) systems and a range of multiple energy storage options. The strategy balances the interests of both commercial aggregators and end users, thereby enhancing the grid’s operational efficiency. The model incorporates temperature variations that affect the PV output, energy storage capacity, conversion efficiency, and EV charging demand, all of which improve numerical accuracy. A new pricing algorithm based on peak-valley differences is proposed that considers the impact of EV penetration and temperature fluctuations. By combining the effects of supercapacitors and lithium batteries, the approach therefore utilizes both power and energy densities. Using Multi-Objective Particle Swarm Optimization (MOPSO), the strategy thereby incorporates three main objectives; minimizing grid load fluctuations, maximizing aggregator profits, and reducing user costs. Simulation results show that the proposed model improves grid resilience, enhances economic benefits for both aggregators and users, and optimizes the system’s performance. The findings from this study provide valuable insights that lead to a better understanding of the sustainable development and the intelligent operation of PV-storage EV charging stations, and this then leads to more efficient and resilient power grids. |
| format | Article |
| id | doaj-art-c75506917157486e9cfecb62cfc9f03a |
| institution | OA Journals |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-c75506917157486e9cfecb62cfc9f03a2025-08-20T02:36:06ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-08-0116911081210.1016/j.ijepes.2025.110812Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregatorsQin Yan0Jinxin Wang1Tao Lin2Archie James Johnston3State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410076, PR China; Corresponding author.State Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410076, PR ChinaWuhan University, Wuhan 430072, PR ChinaState Key Laboratory of Disaster Prevention & Reduction for Power Grid, Changsha University of Science & Technology, Changsha 410076, PR ChinaThis study aims to develop an electricity pricing and multi-objective optimization strategy that can be applied to integrated electric vehicle charging stations (IEVCS) that include photovoltaic (PV) systems and a range of multiple energy storage options. The strategy balances the interests of both commercial aggregators and end users, thereby enhancing the grid’s operational efficiency. The model incorporates temperature variations that affect the PV output, energy storage capacity, conversion efficiency, and EV charging demand, all of which improve numerical accuracy. A new pricing algorithm based on peak-valley differences is proposed that considers the impact of EV penetration and temperature fluctuations. By combining the effects of supercapacitors and lithium batteries, the approach therefore utilizes both power and energy densities. Using Multi-Objective Particle Swarm Optimization (MOPSO), the strategy thereby incorporates three main objectives; minimizing grid load fluctuations, maximizing aggregator profits, and reducing user costs. Simulation results show that the proposed model improves grid resilience, enhances economic benefits for both aggregators and users, and optimizes the system’s performance. The findings from this study provide valuable insights that lead to a better understanding of the sustainable development and the intelligent operation of PV-storage EV charging stations, and this then leads to more efficient and resilient power grids.http://www.sciencedirect.com/science/article/pii/S0142061525003606PV-storage charging stationElectric vehiclesPeak-valley differential electricity priceTemperature fluctuations |
| spellingShingle | Qin Yan Jinxin Wang Tao Lin Archie James Johnston Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators International Journal of Electrical Power & Energy Systems PV-storage charging station Electric vehicles Peak-valley differential electricity price Temperature fluctuations |
| title | Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators |
| title_full | Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators |
| title_fullStr | Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators |
| title_full_unstemmed | Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators |
| title_short | Peak-Valley difference based pricing strategy and optimization for PV-storage electric vehicle charging stations through aggregators |
| title_sort | peak valley difference based pricing strategy and optimization for pv storage electric vehicle charging stations through aggregators |
| topic | PV-storage charging station Electric vehicles Peak-valley differential electricity price Temperature fluctuations |
| url | http://www.sciencedirect.com/science/article/pii/S0142061525003606 |
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