Smart City Gnosys

Smart city article details

Title	Preemptive Electric Vehicle Charging Strategy In Active Power Distribution Networks
ID_Doc	42903
Authors	Souto L.; Taylor P.C.; Damree S.
Year	2024
Published	IEEE Power and Energy Society General Meeting
DOI	http://dx.doi.org/10.1109/PESGM51994.2024.10689235
Abstract	Electric vehicle technologies, notably electric vehicle charging and vehicle-to-grid, represent a critical flexibility resource in smart grids and smart cities, especially within active power distribution networks. During emergencies, they can provide back-up power supply and/or mobility services for vehicle users, enabled to take proactive action to avoid supply interruption or leave the affected area. In this context, this article presents a preemptive strategy for electric vehicle charging in active power distribution networks, considering electric vehicle technology users' behaviors and the operating constraints of the grid. It incorporates sources of information typically available in a smart grid / smart city context, such as energy management system data, weather forecasts, traffic surveillance and geographic information systems, and users' behavioral patterns. The operating requirements are given by thermal and voltage constraints, whereas the user behaviors affect power exchanges with the grid, including electric vehicle charging, discharging, and load demand profiles. The methodology is written as a mixed-integer linear programming formulation aimed at minimizing the energy not supplied. Furthermore, it is demonstrated on a real-based low voltage network in the United Kingdom over a range of scenarios. © 2024 IEEE.
Author Keywords

Similar Articles

Id	Similarity	Authors	Title	Published
22542	0.881	Soares J.; Almeida J.; Gomes L.; Canizes B.; Vale Z.; Neto E.	Electric Vehicles Local Flexibility Strategies For Congestion Relief On Distribution Networks	Energy Reports, 8 (2022)
40628	0.877	Fernandez V.; Pérez V.	Optimization Of Electric Vehicle Charging Control In A Demand-Side Management Context: A Model Predictive Control Approach	Applied Sciences (Switzerland), 14, 19 (2024)
43000	0.868	Reza Salehizadeh M.; Kubra Erenoglu A.; Sengor I.; Tascikaraoglu A.; Erdinc O.; Liu J.; Catalao J.P.S.	Preventive Energy Management Strategy Before Extreme Weather Events By Modeling Evs' Opt-In Preferences	IEEE Transactions on Intelligent Transportation Systems, 25, 11 (2024)
49243	0.867	Wu O.Q.; Yücel Ş.; Zhou Y.	Smart Charging Of Electric Vehicles: An Innovative Business Model For Utility Firms	Manufacturing and Service Operations Management, 24, 5 (2022)
32086	0.866	Meyer D.; Wang J.	Integrating Ultra-Fast Charging Stations Within The Power Grids Of Smart Cities: A Review	IET Smart Grid, 1, 1 (2018)
31841	0.865	Zhou F.; Li Y.; Wang W.; Pan C.	Integrated Energy Management Of A Smart Community With Electric Vehicle Charging Using Scenario Based Stochastic Model Predictive Control	Energy and Buildings, 260 (2022)
35913	0.865	Shahriar S.; Al-Ali A.R.; Osman A.H.; Dhou S.; Nijim M.	Machine Learning Approaches For Ev Charging Behavior: A Review	IEEE Access, 8 (2020)
22524	0.86	Doda D.K.; Beemkumar N.; Awasthi A.; Gautam A.K.	Electric Vehicle Energy Management: Charging In Sustainable Urban Settings For Smart Cities	E3S Web of Conferences, 540 (2024)
40803	0.858	Fernandez V.; Pérez V.; Roig R.	Optimizing Energy Supply For Full Electric Vehicles In Smart Cities: A Comprehensive Mobility Network Model	World Electric Vehicle Journal, 16, 1 (2025)
22515	0.857	Ahmad A.; Khalid M.; Ullah Z.; Ahmad N.; Aljaidi M.; Malik F.A.; Manzoor U.	Electric Vehicle Charging Modes, Technologies And Applications Of Smart Charging	Energies, 15, 24 (2022)