Spatial Markov chain model for electric vehicle charging in cities using geographical information system (GIS) data
Author
Abstract
Suggested Citation
DOI: 10.1016/j.apenergy.2018.09.175
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.References listed on IDEAS
- Neaimeh, Myriam & Wardle, Robin & Jenkins, Andrew M. & Yi, Jialiang & Hill, Graeme & Lyons, Padraig F. & Hübner, Yvonne & Blythe, Phil T. & Taylor, Phil C., 2015. "A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts," Applied Energy, Elsevier, vol. 157(C), pages 688-698.
- Ramos Muñoz, Edgar & Razeghi, Ghazal & Zhang, Li & Jabbari, Faryar, 2016. "Electric vehicle charging algorithms for coordination of the grid and distribution transformer levels," Energy, Elsevier, vol. 113(C), pages 930-942.
- Anderson, Simon P. & de Palma, Andre, 2004. "The economics of pricing parking," Journal of Urban Economics, Elsevier, vol. 55(1), pages 1-20, January.
- Ioakimidis, Christos S. & Thomas, Dimitrios & Rycerski, Pawel & Genikomsakis, Konstantinos N., 2018. "Peak shaving and valley filling of power consumption profile in non-residential buildings using an electric vehicle parking lot," Energy, Elsevier, vol. 148(C), pages 148-158.
- Christiansen, Petter & Engebretsen, Øystein & Fearnley, Nils & Usterud Hanssen, Jan, 2017. "Parking facilities and the built environment: Impacts on travel behaviour," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 198-206.
- Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
- Matteo Muratori, 2018. "Impact of uncoordinated plug-in electric vehicle charging on residential power demand," Nature Energy, Nature, vol. 3(3), pages 193-201, March.
- Smith, William J., 2010. "Can EV (electric vehicles) address Ireland’s CO2 emissions from transport?," Energy, Elsevier, vol. 35(12), pages 4514-4521.
- Notton, Gilles & Nivet, Marie-Laure & Voyant, Cyril & Paoli, Christophe & Darras, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2018. "Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 96-105.
- Majidpour, Mostafa & Qiu, Charlie & Chu, Peter & Pota, Hemanshu R. & Gadh, Rajit, 2016. "Forecasting the EV charging load based on customer profile or station measurement?," Applied Energy, Elsevier, vol. 163(C), pages 134-141.
- 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.
- Byrd, Hugh & Ho, Anna & Sharp, Basil & Kumar-Nair, Nirmal, 2013. "Measuring the solar potential of a city and its implications for energy policy," Energy Policy, Elsevier, vol. 61(C), pages 944-952.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
- Good, Clara & Shepero, Mahmoud & Munkhammar, Joakim & Boström, Tobias, 2019. "Scenario-based modelling of the potential for solar energy charging of electric vehicles in two Scandinavian cities," Energy, Elsevier, vol. 168(C), pages 111-125.
- Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
- 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.
- 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).
- Byungsung Lee & Haesung Lee & Hyun Ahn, 2020. "Improving Load Forecasting of Electric Vehicle Charging Stations Through Missing Data Imputation," Energies, MDPI, vol. 13(18), pages 1-15, September.
- Manbachi, M. & Sadu, A. & Farhangi, H. & Monti, A. & Palizban, A. & Ponci, F. & Arzanpour, S., 2016. "Impact of EV penetration on Volt–VAR Optimization of distribution networks using real-time co-simulation monitoring platform," Applied Energy, Elsevier, vol. 169(C), pages 28-39.
- 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.
- Kalghatgi, Gautam, 2018. "Is it really the end of internal combustion engines and petroleum in transport?," Applied Energy, Elsevier, vol. 225(C), pages 965-974.
- 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.
- Hoarau, Quentin & Perez, Yannick, 2019.
"Network tariff design with prosumers and electromobility: Who wins, who loses?,"
Energy Economics, Elsevier, vol. 83(C), pages 26-39.
- Quentin Hoarau & Yannick Perez, 2018. "Network tariff design with prosumers and electromobility: who wins, who loses?," Working Papers 1810, Chaire Economie du climat.
- Quentin Hoarau & Yannick Perez, 2019. "Network tariff design with prosumers and electromobility: Who wins, who loses?," Post-Print hal-02265823, HAL.
- Powell, Siobhan & Kara, Emre Can & Sevlian, Raffi & Cezar, Gustavo Vianna & Kiliccote, Sila & Rajagopal, Ram, 2020. "Controlled workplace charging of electric vehicles: The impact of rate schedules on transformer aging," Applied Energy, Elsevier, vol. 276(C).
- Gonzalez Venegas, Felipe & Petit, Marc & Perez, Yannick, 2021. "Active integration of electric vehicles into distribution grids: Barriers and frameworks for flexibility services," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
- Ye, Tinghan & Liu, Shanshan & Kontou, Eleftheria, 2024. "Managed residential electric vehicle charging minimizes electricity bills while meeting driver and community preferences," Transport Policy, Elsevier, vol. 149(C), pages 122-138.
- Jiang, An & Qiu, Jiehong & Li, Aiyuan & Zhang, Guangnan, 2025. "An empirical analysis framework to evaluate the impact of residential electric vehicles on power grid," Transport Policy, Elsevier, vol. 173(C).
- Zhang, Lei & Huang, Zhijia & Wang, Zhenpo & Li, Xiaohui & Sun, Fengchun, 2024. "An urban charging load forecasting model based on trip chain model for private passenger electric vehicles: A case study in Beijing," Energy, Elsevier, vol. 299(C).
- Mu Li & Yingqi Liu & Weizhong Yue, 2022. "Evolutionary Game of Actors in China’s Electric Vehicle Charging Infrastructure Industry," Energies, MDPI, vol. 15(23), pages 1-20, November.
- Miguel Carrión & Rafael Zárate-Miñano & Ruth Domínguez, 2020. "Integration of Electric Vehicles in Low-Voltage Distribution Networks Considering Voltage Management," Energies, MDPI, vol. 13(16), pages 1-23, August.
- 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).
- Munseok Chang & Sungwoo Bae & Gilhwan Cha & Jaehyun Yoo, 2021. "Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network," Sustainability, MDPI, vol. 13(24), pages 1-17, December.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:231:y:2018:i:c:p:1089-1099. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.
Printed from https://ideas.repec.org/a/eee/appene/v231y2018icp1089-1099.html