Managing Electric Vehicles in the Smart Grid Using Artificial Intelligence: A Survey
Abstract
Along with the development of smart grids, the wide adoption of electric vehicles (EVs) is seen as a catalyst to the reduction of CO2emissions and more intelligent transportation systems. In particular, EVs augment the grid with the ability to store energy at some points in the network and give it back at others and, therefore, help optimize the use of energy from intermittent renewable energy sources and let users refill their cars in a variety of locations. However, a number of challenges need to be addressed if such benefits are to be achieved. On the one hand, given their limited range and costs involved in charging EV batteries, it is important to design algorithms that will minimize costs and, at the same time, avoid users being stranded. On the other hand, collectives of EVs need to be organized in such a way as to avoid peaks on the grid that may result in high electricity prices and overload local distribution grids. In order to meet such challenges, a number of technological solutions have been proposed. In this paper, we focus on those that utilize artificial intelligence techniques to render EVs and the systems that manage collectives of EVs smarter. In particular, we provide a survey of the literature and identify the commonalities and key differences in the approaches. This allows us to develop a classification of key techniques and benchmarks that can be used to advance the state of the art in this space.
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Rigas et al. detail methods by which ML can improve charge scheduling, congestion management, and vehicle-to-grid algorithms.
“Rigas et al. [684] detail methods by which ML can improve charge scheduling, congestion management, and vehicle-to-grid algorithms.”
From Tackling climate change with machine learning (2023) · cites this paper as [684]
Cites
Kennedy, J., & Eberhart, R. (2002) · Proceedings of ICNN'95 - International Conference on Neural Networks · doi:10.1109/icnn.1995.488968 · Cited by 58,192 · see citing works
Artificial intelligence: a modern approach
Kumar, D. A., Balasubramanian, S., Byeon, D. H., & Manerkar, P. G. V. (1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 22,182 · see citing works
Shapley, L. (1988) · Cambridge University Press eBooks · doi:10.1017/cbo9780511528446.003 · Cited by 10,698 · see citing works
What are batteries, fuel cells, and supercapacitors?
Winter, M., & Brodd, R. J. (2004) · Chemical Reviews · doi:10.1021/cr020730k · Cited by 7,389 · see citing works
Farhangi, H. (2010) · IEEE Power and Energy Magazine · doi:10.1109/mpe.2009.934876 · Cited by 2,967 · see citing works
The Impact of Charging Plug-In Hybrid Electric Vehicles on a Residential Distribution Grid
Clement-Nyns, K., Haesen, E., & Driesen, J. (2010) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2036481 · Cited by 2,847 · see citing works
An introduction to multisensor data fusion
Hall, D. L., & Llinas, J. (1997) · Proceedings of the IEEE · doi:10.1109/5.554205 · Cited by 2,629 · see citing works
Vehicle-to-grid power fundamentals: Calculating capacity and net revenue
Kempton, W., & Tomić, J. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.12.025 · Cited by 2,323 · see citing works
Kempton, W., & Tomić, J. (2005) · Journal of Power Sources · doi:10.1016/j.jpowsour.2004.12.022 · Cited by 2,126 · see citing works
L -Shaped Linear Programs with Applications to Optimal Control and Stochastic Programming
Slyke, R. M. V., & Wets, R. J. ‐. (1969) · SIAM Journal on Applied Mathematics · doi:10.1137/0117061 · Cited by 1,288 · see citing works
Efficient Algorithms for Shortest Paths in Sparse Networks
Johnson, D. B. (1977) · Journal of the ACM · doi:10.1145/321992.321993 · Cited by 1,054 · see citing works
Using fleets of electric-drive vehicles for grid support
Tomić, J., & Kempton, W. (2007) · Journal of Power Sources · doi:10.1016/j.jpowsour.2007.03.010 · Cited by 1,018 · see citing works
Optimal decentralized protocol for electric vehicle charging
Gan, L., Topcu, U., & Low, S. H. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2210288 · Cited by 1,016 · see citing works
Decentralized Charging Control of Large Populations of Plug-in Electric Vehicles
Ma, Z., Callaway, D. S., & Hiskens, I. A. (2011) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2011.2174059 · Cited by 985 · see citing works
Meso-gamma scale forecasts using the nonhydrostatic model LM
Steppeler, J., Doms, G., Schättler, U., et al. (2002) · Meteorology and Atmospheric Physics · doi:10.1007/s00703-001-0592-9 · Cited by 912 · see citing works
Plug-in Vehicles and Renewable Energy Sources for Cost and Emission Reductions
Saber, A. Y., & Venayagamoorthy, G. K. (2010) · IEEE Transactions on Industrial Electronics · doi:10.1109/tie.2010.2047828 · Cited by 863 · see citing works
Contraction Hierarchies: Faster and Simpler Hierarchical Routing in Road Networks
Geisberger, R., Sanders, P., Schultes, D., & Delling, D. (2008) · Springer eBooks · doi:10.1007/978-3-540-68552-4_24 · Cited by 728 · see citing works
Market Structure and Equilibrium
von Stackelberg, H. (2010) · Springer eBooks · doi:10.1007/978-3-642-12586-7 · Cited by 596 · see citing works
SLAW: A New Mobility Model for Human Walks
Lee, K., Hong, S., Kim, S. J., Rhee, I., & Chong, S. (2009) · IEEE Conference on Computer Communications (INFOCOM) · doi:10.1109/infcom.2009.5061995 · Cited by 550 · see citing works
From probabilistic forecasts to statistical scenarios of short‐term wind power production
Pinson, P., Madsen, H., Nielsen, H. A., Papaefthymiou, G., & Klöckl, B. (2008) · Wind Energy · doi:10.1002/we.284 · Cited by 531 · see citing works
A Novel Approach for Unit Commitment Problem via an Effective Hybrid Particle Swarm Optimization
Ting, T. O., Rao, M. V. C., & Loo, C. K. (2006) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2005.860907 · Cited by 448 · see citing works
Economics of Electric Vehicle Charging: A Game Theoretic Approach
Tushar, W., Saad, W., Poor, H. V., & Smith, D. B. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2012.2211901 · Cited by 410 · see citing works
Fichman, B. T. (2012) · doi:10.2172/1212312 · Cited by 338 · see citing works
A correction to the algorithm in reiter's theory of diagnosis
Greiner, R., Smith, B. A., & Wilkerson, R. W. (1989) · Artificial Intelligence · doi:10.1016/0004-3702(89)90079-9 · Cited by 315 · see citing works
Human mobility characterization from cellular network data
Becker, R., Cáceres, R., Hanson, K. J., Isaacman, S., Loh, J. M., Martonosi, M., Rowland, J. R., Urbanek, S., Varshavsky, A., & Volinsky, C. T. (2013) · Communications of the ACM · doi:10.1145/2398356.2398375 · Cited by 307 · see citing works
Decentralized charging control for large populations of plug-in electric vehicles
Ma, Z., Callaway, D. S., & Hiskens, I. A. (2010) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2010.5717547 · Cited by 272 · see citing works
A Multi-Agent System for Controlled Charging of a Large Population of Electric Vehicles
Karfopoulos, E. L., & Hatziargyriou, N. D. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2211624 · Cited by 246 · see citing works
Reinventing the automobile: personal urban mobility for the 21st century
(2010) · Choice Reviews Online · doi:10.5860/choice.48-1430 · Cited by 240 · see citing works
Electric vehicles charge forward
Chan, C. C., & Wong, Y. S. (2004) · IEEE Power and Energy Magazine · doi:10.1109/mpae.2004.1359010 · Cited by 236 · see citing works
Charging scheduling with minimal waiting in a network of electric vehicles and charging stations
Qin, H., & Zhang, W. (2011) · doi:10.1145/2030698.2030706 · Cited by 232 · see citing works
Identifying management procedures to deal with connection of Electric Vehicles in the grid
Lopes, J. P., Soares, F. J., & Almeida, P. M. R. (2009) · doi:10.1109/ptc.2009.5282155 · Cited by 230 · see citing works
Mitchell, W. J. T., Hainley, B. E., & Burns, L. D. (2010) · The MIT Press eBooks · doi:10.7551/mitpress/8490.001.0001 · Cited by 202 · see citing works
The Shortest Path Problem Revisited: Optimal Routing for Electric Vehicles
Artmeier, A., Haselmayr, J., Leucker, M., & Sachenbacher, M. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16111-7_35 · Cited by 193 · see citing works
Profile of Charging Load on the Grid Due to Plug-in Vehicles
Shahidinejad, S., Filizadeh, S., & Bibeau, E. (2012) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2011.2165227 · Cited by 187 · see citing works
Electric Power Allocation in a Network of Fast Charging Stations
Bayram, I. S., Michailidis, G. C., Devetsikiotis, M., et al. (2013) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2013.130707 · Cited by 184 · see citing works
Agent-Based Demand-Modeling Framework for Large-Scale Microsimulations
Balmer, M., Axhausen, K. W., & Nagel, K. (2006) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/1985-14 · Cited by 182 · see citing works
Efficient Energy-Optimal Routing for Electric Vehicles
Sachenbacher, M., Leucker, M., Artmeier, A., & Haselmayr, J. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v25i1.7803 · Cited by 178 · see citing works
Lopes, J. P., Almeida, P. M. R., Silva, A. M., & Soares, F. J. (2009) · Cited by 160 · see citing works
Electrical Vehicles in the Smart Grid: A Mean Field Game Analysis
Couillet, R., Perlaza, S. M., Tembiné, H., et al. (2012) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2012.120707 · Cited by 156 · see citing works
Planning electric-drive vehicle charging under constrained grid conditions
Sundstrom, O., & Binding, C. (2010) · International Conference on Power System Technology (POWERCON) · doi:10.1109/powercon.2010.5666620 · Cited by 151 · see citing works
Optimal Route Planning for Electric Vehicles in Large Networks
Eisner, J., Funke, S., & Storandt, S. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v25i1.7991 · Cited by 140 · see citing works
Caramanis, M. C., & Foster, J. M. (2009) · doi:10.1109/cdc.2009.5399955 · Cited by 136 · see citing works
Performance evaluation of a PHEV parking station using Particle Swarm Optimization
Su, W., & Chow, M. (2011) · IEEE Power and Energy Society General Meeting (PESGM) · doi:10.1109/pes.2011.6038937 · Cited by 133 · see citing works
Online mechanism design for electric vehicle charging
Gerding, E., Robu, V., Stein, S., et al. (2011) · ePrints Soton (University of Southampton) · doi:10.5555/2031678.2031733 · Cited by 130 · see citing works
The role of electric vehicles in smart grids
Galus, M. D., Vayá, M. G., Krause, T., & Andersson, G. (2013) · WIREs Energy and Environment · doi:10.1002/wene.56 · Cited by 129 · see citing works
A noncooperative game for double auction-based energy trading between PHEVs and distribution grids
Saad, W., Han, Z., Poor, H. V., et al. (2011) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2011.6102331 · Cited by 111 · see citing works
Centralized and decentralized approaches to smart charging of plug-in Vehicles
Vayá, M. G., & Andersson, G. (2012) · IEEE Power and Energy Society General Meeting (PESGM) · doi:10.1109/pesgm.2012.6344902 · Cited by 108 · see citing works
Distributed control of electric vehicle charging
Ardakanian, O., Rosenberg, C., & Keshav, S. (2013) · ACM International Conference on Future Energy Systems (e-Energy) · doi:10.1145/2487166.2487178 · Cited by 108 · see citing works
Electric vehicle charging station placement
Lam, A. Y. S., Leung, Y.-W., & Chu, X. (2013) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2013.6688009 · Cited by 107 · see citing works
Deploying power grid-integrated electric vehicles as a multi-agent system
Kamboj, S., Kempton, W. M., & Decker, K. (2011) · doi:10.5555/2030470.2030473 · Cited by 103 · see citing works
Finding minimum-cost paths for electric vehicles
Sweda, T. M., & Klabjan, D. (2012) · IEEE International Electric Vehicle Conference · doi:10.1109/ievc.2012.6183286 · Cited by 99 · see citing works
Is “smart charging” policy for electric vehicles worthwhile?
Lyon, T. P., Michelin, M., Jongejan, A., & Leahy, T. (2011) · Energy Policy · doi:10.1016/j.enpol.2011.10.045 · Cited by 90 · see citing works
Optimal Power Market Participation of Plug-In Electric Vehicles Pooled by Distribution Feeder
Foster, J. M., & Caramanis, M. C. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2232682 · Cited by 84 · see citing works
A model-based online mechanism with pre-commitment and its application to electric vehicle charging
Stein, S., Gerding, E., Robu, V., et al. (2012) · ePrints Soton (University of Southampton) · doi:10.5555/2343776.2343792 · Cited by 77 · see citing works
Quick and energy-efficient routes
Storandt, S. (2012) · ACM SIGSPATIAL International Workshop on Computational Transportation Science (IWCTS) · doi:10.1145/2442942.2442947 · Cited by 76 · see citing works
Decentralized coordination of plug-in hybrid vehicles for imbalance reduction in a smart grid
Vandael, S., Boucké, N., Holvoet, T., et al. (2011) · Lirias · doi:10.5555/2031678.2031732 · Cited by 73 · see citing works
Location-Based Forecasting of Vehicular Charging Load on the Distribution System
Omran, N. G., & Filizadeh, S. (2014) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2013.2282773 · Cited by 63 · see citing works
Coalition formation under uncertainty
Chalkiadakis, G., Markakis, E., & Boutilier, C. E. (2007) · Adaptive Agents and Multi-Agents Systems · doi:10.1145/1329125.1329203 · Cited by 57 · see citing works
Congestion management for urban EV charging systems
Rigas, E. S., Ramchurn, S. D., Bassiliades, N., & Koutitas, G. C. (2013) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2013.6687944 · Cited by 56 · see citing works
Self-citationIntention-aware routing to minimise delays at electric vehicle charging stations
Weerdt, M. M. D., Gerding, E., Stein, S., Robu, V., & Jennings, N. R. (2013) · doi:10.1145/2516911.2516923 · Cited by 55 · see citing works
Electric vehicle charge planning using Economic Model Predictive Control
Halvgaard, R., Poulsen, N. K., Madsen, H., et al. (2012) · IEEE International Electric Vehicle Conference · doi:10.1109/ievc.2012.6183173 · Cited by 50 · see citing works
On-line Decentralized Charging of Plug-In Electric Vehicles in Power SystemsPreprint
Li, Q., Cui, T., Negi, R., et al. (2011) · arXiv (Cornell University) · doi:10.48550/arxiv.1106.5063 · Cited by 49 · see citing works
Decentralised coordination of continuously valued control parameters using the max-sum algorithm
Stranders, R., Farinelli, A., Rogers, A., & Jennings, N. R. (2009) · Adaptive Agents and Multi-Agents Systems · doi:10.65109/zmkp4320 · Cited by 49 · see citing works
Decentralized charging algorithm for electrified vehicles connected to smart grid
Ahn, C., Li, C.-T., & Peng, H. (2011) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.1109/acc.2011.5990895 · Cited by 48 · see citing works
Decentralized control of electric vehicles in a network of fast charging stations
Bayram, I. S., Michailidis, G. C., Papapanagiotou, I. S., et al. (2013) · Globecom · doi:10.1109/glocom.2013.6831496 · Cited by 47 · see citing works
The value of consensus in online stochastic scheduling
Bent, R. W., & Hentenryck, P. V. (2004) · Cited by 43 · see citing works
Two-sided online markets for electric vehicle charging
Gerding, E., Stein, S., Robu, V., et al. (2013) · ePrints Soton (University of Southampton) · doi:10.5555/2484920.2485076 · Cited by 39 · see citing works
Escudero-Garzas, J. J., & Seco‐Granados, G. (2012) · IEEE PES Innovative Smart Grid Technologies Conference (ISGT) · doi:10.1109/isgt.2012.6175791 · Cited by 37 · see citing works
Yang, G., Andreu-Pérez, J., Hu, X., et al. (2014) · Springer eBooks · doi:10.1007/978-1-4471-6374-9_8 · Cited by 36 · see citing works
Wehinger, L. A., Galus, M. D., & Andersson, G. (2010) · International Conference on the European Energy Market (EEM) · doi:10.1109/eem.2010.5558718 · Cited by 36 · see citing works
Cruising with a Battery-Powered Vehicle and Not Getting Stranded
Storandt, S., & Funke, S. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v26i1.8326 · Cited by 35 · see citing works
Optimal bidding strategy of a plug-in electric vehicle aggregator in day-ahead electricity markets
Vayá, M. G., & Andersson, G. (2013) · International Conference on the European Energy Market (EEM) · doi:10.1109/eem.2013.6607304 · Cited by 32 · see citing works
Routing EV Users Towards an Optimal Charging Plan
Bessler, S., & Grønbæk, J. (2012) · World Electric Vehicle Journal · doi:10.3390/wevj5030688 · Cited by 31 · see citing works
Electric power resource provisioning for large scale public EV charging facilities
Bayram, I. S., Michailidis, G. C., & Devetsikiotis, M. (2013) · IEEE International Conference on Smart Grid Communications (SmartGridComm) · doi:10.1109/smartgridcomm.2013.6687946 · Cited by 30 · see citing works
Vayá, M. G., & Andersson, G. (2013) · IEEE Grenoble Conference · doi:10.1109/ptc.2013.6652150 · Cited by 30 · see citing works
Bayram, I. S., Michailidis, G. C., Devetsikiotis, M., et al. (2011) · Springer eBooks · doi:10.1007/978-1-4614-1605-0_6 · Cited by 26 · see citing works
Self-Adapting Coalition Formation Among Electric Vehicles in Smart Grids
Ramos, G. D. O., Burguillo, J. C., & Bazzan, A. L. C. (2013) · IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO) · doi:10.1109/saso.2013.12 · Cited by 20 · see citing works
Enabling E-Mobility: Facility Location for Battery Loading Stations
Storandt, S., & Funke, S. (2013) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v27i1.8478 · Cited by 20 · see citing works
Galus, M. D., & Andersson, G. (2012) · Electra · Cited by 18 · see citing works
Placement of Loading Stations for Electric Vehicles: No Detours Necessary!
Funke, S., Nusser, A., & Storandt, S. (2014) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v28i1.8766 · Cited by 17 · see citing works
Constraint-Based Charging Scheduler Design for Electric Vehicles
Kim, H., Lee, J., & Park, G.-L. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-28493-9_29 · Cited by 17 · see citing works
Aris, P. A., Chalkiadakis, G., & Koutroulis, E. (2012) · Frontiers in artificial intelligence and applications · doi:10.3233/978-1-61499-098-7-981 · Cited by 15 · see citing works
Learning policies for battery usage optimization in electric vehicles
Ermon, S., Xue, Y., Gomes, C. P., et al. (2013) · Machine Learning · doi:10.1007/s10994-013-5378-z · Cited by 14 · see citing works
Risk-aware day-ahead scheduling and real-time dispatch for plug-in electric vehicles
Yang, L., Zhang, J., & Qian, D. (2012) · Globecom · doi:10.1109/glocom.2012.6503578 · Cited by 12 · see citing works
Chatzivasileiadis, S., Galus, M. D., Reckinger, Y., & Andersson, G. (2011) · doi:10.1109/ptc.2011.6019360 · Cited by 11 · see citing works
California Statewide Charging Survey: What Do Drivers Want?
Nicholas, M. A., Tal, G., & Woodjack, J. (2013) · Transportation Research Board 92nd Annual MeetingTransportation Research Board · Cited by 8 · see citing works
Learning Policies for Battery Usage Optimization in Electric Vehicles
Ermon, S., Xue, Y., Gomes, C. P., & Selman, B. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33486-3_13 · Cited by 8 · see citing works
Evaluating the Urban Electric Vehicle
Dille, P., Duescher, M., Nourbakhsh, I., et al. (2018) · Figshare · doi:10.1184/r1/6554774 · Cited by 5 · see citing works
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- Authors
- Rigas, E. S., Ramchurn, S. D., & Bassiliades, N.
- Affiliations
- Aristotle University of Thessaloniki (GR)
- University of Southampton (GB)
- Venue
- IEEE Transactions on Intelligent Transportation Systems
- Published
- 2015-08
- Volume
- 16
- Issue
- 4
- Pages
- 1619-1635
- ISSN
- 1524-9050 (ISSN-L)
- 1558-0016
- OpenAlex
- W2090861152
- Cited by
- 280
- References
- 88
- Citations by year
- 2026: 6 · 2025: 28 · 2024: 32 · 2023: 26 · 2022: 31 · 2021: 33 · 2020: 30 · 2019: 27 · 2018: 24 · 2017: 23 · 2016: 17 · 2015: 3
- FWCI
- 7.61
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Intelligent Transportation Systems (publishedVersion)
- Funders
- Engineering and Physical Sciences Research Council (EP/K012347/1)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Automotive Engineering › Electric and Hybrid Vehicle Technologies
- Keywords
- electric vehicles, smart grid, artificial intelligence, electric vehicle charging, load balancing, peak shaving, renewable energy integration, charging cost minimization, battery energy storage
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