IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v162y2016icp763-771.html
   My bibliography  Save this item

A data-driven approach for characterising the charging demand of electric vehicles: A UK case study

Citations

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


Cited by:

  1. Godina, Radu & Rodrigues, Eduardo M.G. & Matias, João C.O. & Catalão, João P.S., 2016. "Smart electric vehicle charging scheduler for overloading prevention of an industry client power distribution transformer," Applied Energy, Elsevier, vol. 178(C), pages 29-42.
  2. Qiang Xing & Zhong Chen & Ziqi Zhang & Xiao Xu & Tian Zhang & Xueliang Huang & Haiwei Wang, 2020. "Urban Electric Vehicle Fast-Charging Demand Forecasting Model Based on Data-Driven Approach and Human Decision-Making Behavior," Energies, MDPI, vol. 13(6), pages 1-32, March.
  3. Lixing Chen & Xueliang Huang & Hong Zhang, 2020. "Modeling the Charging Behaviors for Electric Vehicles Based on Ternary Symmetric Kernel Density Estimation," Energies, MDPI, vol. 13(7), pages 1-17, March.
  4. Liu, Yuechen Sophia & Tayarani, Mohammad & Gao, H. Oliver, 2022. "An activity-based travel and charging behavior model for simulating battery electric vehicle charging demand," Energy, Elsevier, vol. 258(C).
  5. Turrentine, Tom & Hardman, Scott & Garas, Dahlia, 2018. "Steering the Electric Vehicle Transition to Sustainability," Institute of Transportation Studies, Working Paper Series qt1w3836d3, Institute of Transportation Studies, UC Davis.
  6. Chen, Yu & Lin, Boqiang, 2022. "Are consumers in China’s major cities happy with charging infrastructure for electric vehicles?," Applied Energy, Elsevier, vol. 327(C).
  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. Pampa Sinha & Kaushik Paul & Sanchari Deb & Sulabh Sachan, 2023. "Comprehensive Review Based on the Impact of Integrating Electric Vehicle and Renewable Energy Sources to the Grid," Energies, MDPI, vol. 16(6), pages 1-39, March.
  9. Murat Akil & Emrah Dokur & Ramazan Bayindir, 2021. "The SOC Based Dynamic Charging Coordination of EVs in the PV-Penetrated Distribution Network Using Real-World Data," Energies, MDPI, vol. 14(24), pages 1-19, December.
  10. Calearo, Lisa & Marinelli, Mattia & Ziras, Charalampos, 2021. "A review of data sources for electric vehicle integration studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
  11. Zhang, Ziqi & Chen, Zhong & Xing, Qiang & Ji, Zhenya & Zhang, Tian, 2022. "Evaluation of the multi-dimensional growth potential of China's public charging facilities for electric vehicles through 2030," Utilities Policy, Elsevier, vol. 75(C).
  12. Wei Wei & Ming Cao & Qianling Jiang & Sheng-Jung Ou & Hong Zou, 2020. "What Influences Chinese Consumers’ Adoption of Battery Electric Vehicles? A Preliminary Study Based on Factor Analysis," Energies, MDPI, vol. 13(5), pages 1-15, February.
  13. 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).
  14. Simona Bigerna & Silvia Micheli, 2018. "Attitudes Toward Electric Vehicles: The Case of Perugia Using a Fuzzy Set Analysis," Sustainability, MDPI, vol. 10(11), pages 1-14, November.
  15. Chengxiang Zhuge & Chunfu Shao & Xia Li, 2019. "Empirical Analysis of Parking Behaviour of Conventional and Electric Vehicles for Parking Modelling: A Case Study of Beijing, China," Energies, MDPI, vol. 12(16), pages 1-21, August.
  16. Arias, Mariz B. & Kim, Myungchin & Bae, Sungwoo, 2017. "Prediction of electric vehicle charging-power demand in realistic urban traffic networks," Applied Energy, Elsevier, vol. 195(C), pages 738-753.
  17. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
  18. Xydas, Erotokritos & Marmaras, Charalampos & Cipcigan, Liana M., 2016. "A multi-agent based scheduling algorithm for adaptive electric vehicles charging," Applied Energy, Elsevier, vol. 177(C), pages 354-365.
  19. Zhouquan Wu & Pradeep Krishna Bhat & Bo Chen, 2023. "Optimal Configuration of Extreme Fast Charging Stations Integrated with Energy Storage System and Photovoltaic Panels in Distribution Networks," Energies, MDPI, vol. 16(5), pages 1-20, March.
  20. 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).
  21. Andrenacci, N. & Genovese, A. & Ragona, R., 2017. "Determination of the level of service and customer crowding for electric charging stations through fuzzy models and simulation techniques," Applied Energy, Elsevier, vol. 208(C), pages 97-107.
  22. Einolander, Johannes & Lahdelma, Risto, 2022. "Multivariate copula procedure for electric vehicle charging event simulation," Energy, Elsevier, vol. 238(PA).
  23. Sheng, Yujie & Zeng, Hongtai & Guo, Qinglai & Yu, Yang & Li, Qiang, 2023. "Impact of customer portrait information superiority on competitive pricing of EV fast-charging stations," Applied Energy, Elsevier, vol. 348(C).
  24. Vincent Barthel & Jonas Schlund & Philipp Landes & Veronika Brandmeier & Marco Pruckner, 2021. "Analyzing the Charging Flexibility Potential of Different Electric Vehicle Fleets Using Real-World Charging Data," Energies, MDPI, vol. 14(16), pages 1-16, August.
  25. Shepero, Mahmoud & Munkhammar, Joakim & Widén, Joakim & Bishop, Justin D.K. & Boström, Tobias, 2018. "Modeling of photovoltaic power generation and electric vehicles charging on city-scale: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 61-71.
  26. Helmus, J.R. & Spoelstra, J.C. & Refa, N. & Lees, M. & van den Hoed, R., 2018. "Assessment of public charging infrastructure push and pull rollout strategies: The case of the Netherlands," Energy Policy, Elsevier, vol. 121(C), pages 35-47.
  27. Xiong, Yingqi & Wang, Bin & Chu, Chi-cheng & Gadh, Rajit, 2018. "Vehicle grid integration for demand response with mixture user model and decentralized optimization," Applied Energy, Elsevier, vol. 231(C), pages 481-493.
  28. Hye-Seung Han & Eunsung Oh & Sung-Yong Son, 2018. "Study on EV Charging Peak Reduction with V2G Utilizing Idle Charging Stations: The Jeju Island Case," Energies, MDPI, vol. 11(7), pages 1-13, June.
  29. Milan Straka & Pasquale De Falco & Gabriella Ferruzzi & Daniela Proto & Gijs van der Poel & Shahab Khormali & v{L}ubov{s} Buzna, 2019. "Predicting popularity of EV charging infrastructure from GIS data," Papers 1910.02498, arXiv.org.
  30. Chung, Yu-Wei & Khaki, Behnam & Li, Tianyi & Chu, Chicheng & Gadh, Rajit, 2019. "Ensemble machine learning-based algorithm for electric vehicle user behavior prediction," Applied Energy, Elsevier, vol. 254(C).
  31. Zhang, Chaobo & Xue, Xue & Zhao, Yang & Zhang, Xuejun & Li, Tingting, 2019. "An improved association rule mining-based method for revealing operational problems of building heating, ventilation and air conditioning (HVAC) systems," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
  32. Yuxuan Wang & Bingxu Zhang & Chenyang Li & Yongzhang Huang, 2022. "Collaborative Robust Optimization Strategy of Electric Vehicles and Other Distributed Energy Considering Load Flexibility," Energies, MDPI, vol. 15(8), pages 1-22, April.
  33. Sun, Lishan & Huang, Yuchen & Liu, Shuli & Chen, Yanyan & Yao, Liya & Kashyap, Anil, 2017. "A completive survey study on the feasibility and adaptation of EVs in Beijing, China," Applied Energy, Elsevier, vol. 187(C), pages 128-139.
  34. Hu, Dingding & Zhou, Kaile & Li, Fangyi & Ma, Dawei, 2022. "Electric vehicle user classification and value discovery based on charging big data," Energy, Elsevier, vol. 249(C).
  35. Mingdong Sun & Chunfu Shao & Chengxiang Zhuge & Pinxi Wang & Xiong Yang & Shiqi Wang, 2022. "Uncovering travel and charging patterns of private electric vehicles with trajectory data: evidence and policy implications," Transportation, Springer, vol. 49(5), pages 1409-1439, October.
  36. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
  37. Hao, Ying & Dong, Lei & Liang, Jun & Liao, Xiaozhong & Wang, Lijie & Shi, Lefeng, 2020. "Power forecasting-based coordination dispatch of PV power generation and electric vehicles charging in microgrid," Renewable Energy, Elsevier, vol. 155(C), pages 1191-1210.
  38. Moon, Sang-Keun & Kim, Jin-O, 2017. "Balanced charging strategies for electric vehicles on power systems," Applied Energy, Elsevier, vol. 189(C), pages 44-54.
  39. Fischer, David & Harbrecht, Alexander & Surmann, Arne & McKenna, Russell, 2019. "Electric vehicles’ impacts on residential electric local profiles – A stochastic modelling approach considering socio-economic, behavioural and spatial factors," Applied Energy, Elsevier, vol. 233, pages 644-658.
  40. Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2016. "Energy Internet: The business perspective," Applied Energy, Elsevier, vol. 178(C), pages 212-222.
  41. Liu, Ke & Liu, Yanli, 2023. "Stochastic user equilibrium based spatial-temporal distribution prediction of electric vehicle charging load," Applied Energy, Elsevier, vol. 339(C).
  42. Yvenn Amara-Ouali & Yannig Goude & Pascal Massart & Jean-Michel Poggi & Hui Yan, 2021. "A Review of Electric Vehicle Load Open Data and Models," Energies, MDPI, vol. 14(8), pages 1-35, April.
  43. Crozier, Constance & Morstyn, Thomas & McCulloch, Malcolm, 2020. "The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems," Applied Energy, Elsevier, vol. 268(C).
  44. Heredia, Willy Bernal & Chaudhari, Kalpesh & Meintz, Andrew & Jun, Myungsoo & Pless, Shanti, 2020. "Evaluation of smart charging for electric vehicle-to-building integration: A case study," Applied Energy, Elsevier, vol. 266(C).
  45. Shi, Jiaqi & Liu, Nian & Huang, Yujing & Ma, Liya, 2022. "An Edge Computing-oriented Net Power Forecasting for PV-assisted Charging Station: Model Complexity and Forecasting Accuracy Trade-off," Applied Energy, Elsevier, vol. 310(C).
  46. Wang, Wanying & Zhang, Qiang & Peng, Zhanglin & Shao, Zhen & Li, Xuefang, 2020. "An empirical evaluation of different usage pattern between car-sharing battery electric vehicles and private ones," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 115-129.
  47. Michel Noussan & Francesco Neirotti, 2020. "Cross-Country Comparison of Hourly Electricity Mixes for EV Charging Profiles," Energies, MDPI, vol. 13(10), pages 1-14, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.