IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v274y2020ics0306261920305754.html
   My bibliography  Save this item

Daily electric vehicle charging load profiles considering demographics of vehicle users

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Li, Alan G. & Wang, Weizhong & West, Alan C. & Preindl, Matthias, 2022. "Health and performance diagnostics in Li-ion batteries with pulse-injection-aided machine learning," Applied Energy, Elsevier, vol. 315(C).
  2. Li, Alan G. & West, Alan C. & Preindl, Matthias, 2022. "Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review," Applied Energy, Elsevier, vol. 316(C).
  3. Han Su & Qian Zhang & Wanying Wang & Xiaoan Tang, 2021. "A Driving Behavior Distribution Fitting Method Based on Two-Stage Hybrid User Classification," Sustainability, MDPI, vol. 13(13), pages 1-24, June.
  4. Zhao, Yang & Jiang, Ziyue & Chen, Xinyu & Liu, Peng & Peng, Tianduo & Shu, Zhan, 2023. "Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets," Energy, Elsevier, vol. 285(C).
  5. Xiuli Wang & Junkai Wei & Fushuan Wen & Kai Wang, 2023. "A Trading Mode Based on the Management of Residual Electric Energy in Electric Vehicles," Energies, MDPI, vol. 16(17), pages 1-23, August.
  6. M. Zulfiqar & Nahar F. Alshammari & M. B. Rasheed, 2023. "Reinforcement Learning-Enabled Electric Vehicle Load Forecasting for Grid Energy Management," Mathematics, MDPI, vol. 11(7), pages 1-20, March.
  7. Yan, Jie & Zhang, Jing & Liu, Yongqian & Lv, Guoliang & Han, Shuang & Alfonzo, Ian Emmanuel Gonzalez, 2020. "EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs," Renewable Energy, Elsevier, vol. 159(C), pages 623-641.
  8. Muhammad Ahsan Khan & Akhtar Hussain & Woon-Gyu Lee & Hak-Man Kim, 2023. "An Incentive-Based Mechanism to Enhance Energy Trading among Microgrids, EVs, and Grid," Energies, MDPI, vol. 16(17), pages 1-23, September.
  9. Ouyang, Xu & Xu, Min, 2022. "Promoting green transportation under the belt and Road Initiative: Locating charging stations considering electric vehicle users’ travel behavior," Transport Policy, Elsevier, vol. 116(C), pages 58-80.
  10. Despoina Kothona & Aggelos S. Bouhouras, 2022. "A Two-Stage EV Charging Planning and Network Reconfiguration Methodology towards Power Loss Minimization in Low and Medium Voltage Distribution Networks," Energies, MDPI, vol. 15(10), pages 1-17, May.
  11. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
  12. Powell, Siobhan & Cezar, Gustavo Vianna & Rajagopal, Ram, 2022. "Scalable probabilistic estimates of electric vehicle charging given observed driver behavior," Applied Energy, Elsevier, vol. 309(C).
  13. C. Birk Jones & Matthew Lave & William Vining & Brooke Marshall Garcia, 2021. "Uncontrolled Electric Vehicle Charging Impacts on Distribution Electric Power Systems with Primarily Residential, Commercial or Industrial Loads," Energies, MDPI, vol. 14(6), pages 1-16, March.
  14. Jiao, Feixiang & Ji, Chengda & Zou, Yuan & Zhang, Xudong, 2021. "Tri-stage optimal dispatch for a microgrid in the presence of uncertainties introduced by EVs and PV," Applied Energy, Elsevier, vol. 304(C).
  15. Richard, René & Cao, Hung & Wachowicz, Monica, 2022. "EVStationSIM: An end-to-end platform to identify and interpret similar clustering patterns of EV charging stations across multiple time slices," Applied Energy, Elsevier, vol. 322(C).
  16. Siobhan Powell & Gustavo Vianna Cezar & Liang Min & Inês M. L. Azevedo & Ram Rajagopal, 2022. "Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption," Nature Energy, Nature, vol. 7(10), pages 932-945, October.
  17. Einolander, Johannes & Lahdelma, Risto, 2022. "Multivariate copula procedure for electric vehicle charging event simulation," Energy, Elsevier, vol. 238(PA).
  18. Zhang, Xiaofeng & Kong, Xiaoying & Yan, Renshi & Liu, Yuting & Xia, Peng & Sun, Xiaoqin & Zeng, Rong & Li, Hongqiang, 2023. "Data-driven cooling, heating and electrical load prediction for building integrated with electric vehicles considering occupant travel behavior," Energy, Elsevier, vol. 264(C).
  19. Sheng Ding & Chengmei Xu & Yao Rao & Zhaofang Song & Wangwang Yang & Zexu Chen & Zitong Zhang, 2022. "A Time-Varying Potential Evaluation Method for Electric Vehicle Group Demand Response Driven by Small Sample Data," Sustainability, MDPI, vol. 14(9), pages 1-21, April.
  20. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
  21. Ki-Beom Lee & Mohamed A. Ahmed & Dong-Ki Kang & Young-Chon Kim, 2020. "Deep Reinforcement Learning Based Optimal Route and Charging Station Selection," Energies, MDPI, vol. 13(23), pages 1-22, November.
  22. Florian Maurer & Christian Rieke & Ralf Schemm & Dominik Stollenwerk, 2023. "Analysis of an Urban Grid with High Photovoltaic and e-Mobility Penetration," Energies, MDPI, vol. 16(8), pages 1-18, April.
  23. Yin, Wanjun & Ji, Jianbo & Qin, Xuan, 2023. "Study on optimal configuration of EV charging stations based on second-order cone," Energy, Elsevier, vol. 284(C).
  24. Ahmed M. Abed & Ali AlArjani, 2022. "The Neural Network Classifier Works Efficiently on Searching in DQN Using the Autonomous Internet of Things Hybridized by the Metaheuristic Techniques to Reduce the EVs’ Service Scheduling Time," Energies, MDPI, vol. 15(19), pages 1-25, September.
  25. Zhong, Zewei & Zeng, Yun & Zhao, Xiaoli & Zhang, Sufang, 2024. "The social benefits resulting from electric vehicle smart charging balancing economy and decarbonization," Transport Policy, Elsevier, vol. 147(C), pages 113-124.
  26. Pokpong Prakobkaew & Somporn Sirisumrannukul, 2022. "Practical Grid-Based Spatial Estimation of Number of Electric Vehicles and Public Chargers for Country-Level Planning with Utilization of GIS Data," Energies, MDPI, vol. 15(11), pages 1-19, May.
  27. Einolander, Johannes & Lahdelma, Risto, 2022. "Explicit demand response potential in electric vehicle charging networks: Event-based simulation based on the multivariate copula procedure," Energy, Elsevier, vol. 256(C).
  28. Ruisheng Wang & Zhong Chen & Qiang Xing & Ziqi Zhang & Tian Zhang, 2022. "A Modified Rainbow-Based Deep Reinforcement Learning Method for Optimal Scheduling of Charging Station," Sustainability, MDPI, vol. 14(3), pages 1-14, February.
  29. Sheik Mohammed S. & Femin Titus & Sudhakar Babu Thanikanti & Sulaiman S. M. & Sanchari Deb & Nallapaneni Manoj Kumar, 2022. "Charge Scheduling Optimization of Plug-In Electric Vehicle in a PV Powered Grid-Connected Charging Station Based on Day-Ahead Solar Energy Forecasting in Australia," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
  30. Simolin, Toni & Rauma, Kalle & Viri, Riku & Mäkinen, Johanna & Rautiainen, Antti & Järventausta, Pertti, 2021. "Charging powers of the electric vehicle fleet: Evolution and implications at commercial charging sites," Applied Energy, Elsevier, vol. 303(C).
  31. Secinaro, Silvana & Calandra, Davide & Lanzalonga, Federico & Ferraris, Alberto, 2022. "Electric vehicles’ consumer behaviours: Mapping the field and providing a research agenda," Journal of Business Research, Elsevier, vol. 150(C), pages 399-416.
  32. Dusan Medved & Lubomir Bena & Maksym Oliinyk & Jaroslav Dzmura & Damian Mazur & David Martinko, 2023. "Assessing the Effects of Smart Parking Infrastructure on the Electrical Power System," Energies, MDPI, vol. 16(14), pages 1-16, July.
  33. Yang, Zhichun & Yang, Fan & Min, Huaidong & Tian, Hao & Hu, Wei & Liu, Jian & Eghbalian, Nasrin, 2023. "Energy management programming to reduce distribution network operating costs in the presence of electric vehicles and renewable energy sources," Energy, Elsevier, vol. 263(PA).
  34. Alexandra Märtz & Uwe Langenmayr & Sabrina Ried & Katrin Seddig & Patrick Jochem, 2022. "Charging Behavior of Electric Vehicles: Temporal Clustering Based on Real-World Data," Energies, MDPI, vol. 15(18), pages 1-26, September.
  35. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
  36. Huang, Wenxin & Wang, Jianguo & Wang, Jianping & Zeng, Haiyan & Zhou, Mi & Cao, Jinxin, 2024. "EV charging load profile identification and seasonal difference analysis via charging sessions data of charging stations," Energy, Elsevier, vol. 288(C).
  37. Liu, Ke & Liu, Yanli, 2023. "Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load," Applied Energy, Elsevier, vol. 339(C).
  38. Heping Jia & Qianxin Ma & Yun Li & Mingguang Liu & Dunnan Liu, 2023. "Integrating Electric Vehicles to Power Grids: A Review on Modeling, Regulation, and Market Operation," Energies, MDPI, vol. 16(17), pages 1-18, August.
  39. Zhang, Fan & Lv, Huitao & Xing, Qiang & Ji, Yanjie, 2024. "Deployment of battery-swapping stations: Integrating travel chain simulation and multi-objective optimization for delivery electric micromobility vehicles," Energy, Elsevier, vol. 290(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.