{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,13]],"date-time":"2025-12-13T06:50:10Z","timestamp":1765608610095,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,3]],"date-time":"2018-05-03T00:00:00Z","timestamp":1525305600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Scheduling EV user\u2019s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs). This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN), including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator\u2019s income, reduce the EV users\u2019 costs, and balance the load of the power grid while improving the efficiency of the EV charging system.<\/jats:p>","DOI":"10.3390\/fi10050040","type":"journal-article","created":{"date-parts":[[2018,5,4]],"date-time":"2018-05-04T03:08:21Z","timestamp":1525403301000},"page":"40","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["An EV Charging Scheduling Mechanism Based on Price Negotiation"],"prefix":"10.3390","volume":"10","author":[{"given":"Baocheng","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer, North China University of Technology, Beijing 100144, China"}]},{"given":"Yafei","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer, North China University of Technology, Beijing 100144, China"}]},{"given":"Yu","family":"Xiao","sequence":"additional","affiliation":[{"name":"School of Computer, North China University of Technology, Beijing 100144, China"}]},{"given":"Yi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer, North China University of Technology, Beijing 100144, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,3]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Impacts and Utilization of Electric Vehicles Integration into Power Systems","volume":"34","author":"Hu","year":"2012","journal-title":"Zhongguo Dianji Gongcheng Xuebao"},{"key":"ref_2","first-page":"891","article-title":"A Survey on Battery-Swapping Mode of Electric Vehicles","volume":"37","author":"Gao","year":"2013","journal-title":"Dianwang Jishu"},{"doi-asserted-by":"crossref","unstructured":"Kutt, L., Saarijarvi, E., Lehtonen, M., Rosin, A., and Molder, H. (2014, January 12\u201315). Load Shifting in the Existing Distribution Network and Perspectives for EV Charging-Case Study. Proceedings of the 2014 IEEE Innovative Smart Grid Technologies Europe (ISGT-Europe), Istanbul, Turkey.","key":"ref_3","DOI":"10.1109\/ISGTEurope.2014.7028938"},{"doi-asserted-by":"crossref","unstructured":"Moya, C.V., and Baeze, J.M. (2017, January 18\u201320). Optimization of Centralized Charging Strategy for Electric Vehicle in Power Distribution Network. Proceedings of the 2017 Chilean Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON), Pucon, Chile.","key":"ref_4","DOI":"10.1109\/CHILECON.2017.8229546"},{"doi-asserted-by":"crossref","unstructured":"Ma, K., Xie, L., and Kumar, P.R. (2014, January 3\u20136). A Layered Architecture for EV Charging Stations Based on Time Scale Decomposition. Proceedings of the 2014 IEEE International Conference on Smart Grid Communications (SmartGridComm), Venice, Italy.","key":"ref_5","DOI":"10.1109\/SmartGridComm.2014.7007725"},{"doi-asserted-by":"crossref","unstructured":"Zou, F.Q., Liu, N., and Chen, Q.F. (2015, January 3\u20136). Multi-Party Energy Management for EV Charging Station Cooperated with PV Systems in Smart Grid. Proceedings of the 2015 IEEE Innovative Smart Grid Technologies\u2014Asia (ISGT ASIA), Bangkok, Thailand.","key":"ref_6","DOI":"10.1109\/ISGT-Asia.2015.7387001"},{"doi-asserted-by":"crossref","unstructured":"Wang, B., Wang, Y.B., Qiu, C., Chu, C.C., and Gadh, R. (2015, January 1\u20135). Event-based Electric Vehicle Scheduling Considering Random User Behaviors. Proceedings of the 2015 IEEE International Conference on Smart Grid Communications (SmartGridComm), Miami, FL, USA.","key":"ref_7","DOI":"10.1109\/SmartGridComm.2015.7436319"},{"doi-asserted-by":"crossref","unstructured":"Rivera, J., and Jacobsen, H.A. (2014, January 15\u201317). A Distributed Anytime for Network Utility Maximization with Application to Real-time EV Charging Control. Proceedings of the 53rd IEEE Conference on Decision and Control (CDC), Los Angeles, CA, USA.","key":"ref_8","DOI":"10.1109\/CDC.2014.7039503"},{"doi-asserted-by":"crossref","unstructured":"Chen, Q.F., Liu, N., Lu, X.Y., and Zhang, J.H. (2014, January 20\u201323). A Heuristic Charging Strategy for Real-Time Operation of PV-based Charging Station for Electric Vehicles. Proceedings of the 2014 IEEE Innovative Smart Grid Technologies\u2014Asia (ISGT ASIA), Kuala Lumpur, Malaysia.","key":"ref_9","DOI":"10.1109\/ISGT-Asia.2014.6873836"},{"doi-asserted-by":"crossref","unstructured":"Luo, C., Huang, Y.F., and Gupta, V. (2015, January 11\u201314). A Consumer Behavior Based Approach to Multi-Stage EV Charging Station Placement. Proceedings of the IEEE 81st Vehicular Technology Conference (VTC Spring), Glasgow, UK.","key":"ref_10","DOI":"10.1109\/VTCSpring.2015.7145593"},{"key":"ref_11","first-page":"627","article-title":"Competitive Charging Station Pricing for Plug-In Electric Vehicles","volume":"8","author":"Yuan","year":"2017","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_12","first-page":"3674","article-title":"Reinforcement Learning-Based Plug-In Electric Vehicle Charging with Forecasted Price","volume":"66","author":"Chis","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_13","first-page":"2322","article-title":"Vehicle Driving Pattern Based Modeling and Analysis of Centralized Charging\/Discharging Strategy for Plug-In Electric Vehicles","volume":"38","author":"Wang","year":"2014","journal-title":"Dianwang Jishu"},{"doi-asserted-by":"crossref","unstructured":"Sha\u2019aban, Y.A., Ikpehai, A., Adebisi, B., and Rabie, K.M. (2017). Bi-Directional Coordination of Plug-In Electric Vehicles with Economic Model Predictive Control. Energies, 10.","key":"ref_14","DOI":"10.3390\/en10101507"},{"doi-asserted-by":"crossref","unstructured":"Tan, K.M., Ramachandaramurthy, V.K., Yong, J.Y., Padmanaban, S., Mihet-Popa, L., and Blaabjerg, F. (2017). Minimization of Load Variance in Power Grids\u2014Investigation on Optimal Vehicle-to-Grid Scheduling. Energies, 10.","key":"ref_15","DOI":"10.3390\/en10111880"},{"doi-asserted-by":"crossref","unstructured":"Bhatti, A.R., and Salam, Z. (2016, January 28\u201329). Charging of Electric Vehicle with Constant Price Using Photovoltaic Based Grid-Connected System. Proceedings of the 2016 6th IEEE International Conference on Power and Energy (PECON), Melaka, Malaysia.","key":"ref_16","DOI":"10.1109\/PECON.2016.7951571"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"3720","DOI":"10.3390\/en8053720","article-title":"Utilization of Electric Vehicles and Their Used Batteries for Peak-Load Shifting","volume":"8","author":"Aziz","year":"2015","journal-title":"Energies"},{"doi-asserted-by":"crossref","unstructured":"Fan, H., Hou, H., Ke, X.B., Zhu, G.R., and Chen, W. (2016, January 3\u20134). The Optimal Charging Strategy of EV Rational User Based on TOU Power Price. Proceedings of the 2016 International Conference on Industrial Informatics Computing Technology Intelligent Technology Industrial Information Integration (ICIICII), Wuhan, China.","key":"ref_18","DOI":"10.1109\/ICIICII.2016.0096"},{"doi-asserted-by":"crossref","unstructured":"Zhong, W.F., Lu, C., and Yu, R. (2015, January 24\u201326). Adaptive Price Control for Electric Vehicle Charging in Smart Grid. Proceedings of the 2015 5th International Conference on Information Science and Technology (ICIST), Changsha, China.","key":"ref_19","DOI":"10.1109\/ICIST.2015.7288985"},{"doi-asserted-by":"crossref","unstructured":"Wang, B., Hu, B.Y., Qiu, C., Chu, P., and Gadh, R. (2015, January 18\u201320). EV Charging Algorithm Implementation with User Price Preference. Proceedings of the 2015 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference (ISGT), Washington, DC, USA.","key":"ref_20","DOI":"10.1109\/ISGT.2015.7131895"},{"doi-asserted-by":"crossref","unstructured":"Wang, J.K., and Chen, Y.L. (2007, January 22\u201324). Agent-based Price Negotiation System for Electronic Commerce. Proceedings of the 7th International Conference on Intelligent Systems Design and Applications (ISDA), Rio de Janeiro, Brazil.","key":"ref_21","DOI":"10.1109\/ISDA.2007.4389591"},{"unstructured":"Lu, P.Y., Li, Y.J., and Feng, Y.Q. (2006, January 4\u20136). A Design of Automated Bargaining System Based on Consumers\u2019 Bargaining Pattern. Proceedings of the Multi-conference on \u201cComputational Engineering in Systems Applications\u201d (CESA), Beijing, China.","key":"ref_22"},{"doi-asserted-by":"crossref","unstructured":"Sakurama, K., and Miura, M. (2015, January 3\u20136). Real-time Pricing via Distributed Negotiations between Prosumers in Smart Grid. Proceedings of the 2015 IEEE Innovative Smart Grid Technologies\u2014Asia (ISGT ASIA), Bangkok, Thailand.","key":"ref_23","DOI":"10.1109\/ISGT-Asia.2015.7386991"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/10\/5\/40\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:03:08Z","timestamp":1760194988000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/10\/5\/40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,3]]},"references-count":23,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2018,5]]}},"alternative-id":["fi10050040"],"URL":"https:\/\/doi.org\/10.3390\/fi10050040","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2018,5,3]]}}}