Introduction

Faced with dwindling fossil fuels and the increasingly negative impact of climate change on society, several countries have instigated national plans to reduce carbon emissions. The electrification of transport, via the extensive use of Electric Vehicles (EVs) is seen as one of the main pathways to achieve significant reductions in CO2 emissions.

To control the activities of EVs demands algorithms that can solve problems that involve a large number of heterogeneous entities (e.g., EV owners, charging point owners), each one having its own goals, needs and incentives (e.g., amount of energy to charge, profit maximization), while they will operate in highly dynamic environments (e.g., variable number of EVs, variable intentions of the drivers) and having to deal with a number of uncertainties (e.g., future arrival of EVs, energy demand, energy production from Renewable Energy Sources (RES)). Artificial Intelligence techniques such as search algorithms, optimization and multi-agent systems are proven efficient in solving such problems.

Areas of research

1. Market-based techniques for EV charging scheduling
   1. Mechanism design
   2. Mathematical-optimization
   3. Multi-agent systems
2. EV charging scheduling in Mobility-on-Demand schemes
   1. Search algorithms
   2. Local search
   3. Mathematical optimization
3. EV charging with Vehicle-to-Grid energy transfer
   1. Mathematical optimization
4. Tools
   1. EVLib
   2. EVLibSim

People

• Prof. Nick Bassiliades, Aristotle University of Thessaloniki
• Dr. Emmanouil Rigas, Aristotle University of Thessaloniki
• Mr. Andreas Seitaridis, Aristotle University of Thessaloniki
• Mr. Alexandros Koufakis, Center for Research and Technology- Hellas
• Mr. Sotiris Karapostolakis, Travelfusion
• (External collaborator) Prof. Sarvapali D. Ramchurn, University of Southampton

Awards

• Scholarship of excellence for Dr. Rigas for his research on this area in 2015.
• The article entitled “Algorithms for Electric Vehicle Scheduling in Large-Scale Mobility-on-Demand Schemes” that was published at the “Artificial Intelligence Journal” was featured as an exceptional work through a news article that was published at the journal’s website with aim to promote research with positive environmental-social impact (https://www.journals.elsevier.com/artificial-intelligence/news/getting-more-electric-cars-on-the-road)

Publications

1. E. Rigas, K. Tsompanidis, Algorithms to Manage Congestion in Large-Scale Mobility-on-Demand Schemes that Use Electric Vehicles. SN Comput. Sci. 2(4): 292 (2021)
2. A. Seitaridis, E. Rigas, N. Bassiliades, S. D. Ramchurn, “An agent-based negotiation scheme for the distribution of electric vehicles across a set of charging stations”, Simul. Model. Pract. Theory 100: 102040 (2020)
3. A.-M. Koufakis, E. Rigas, N. Bassiliades, S. D. Ramchurn, “Offline and Online Electric Vehicle Charging Scheduling With V2V Energy Transfer”, IEEE Trans. Intell. Transp. Syst. 21(5): 2128-2138 (2020)
4. E. Rigas, K. Tsompanidis, “Congestion Management for Mobility-on-Demand Schemes that Use Electric Vehicles”, EUMAS/AT 2020: 52-66
5. E. Rigas, E. Gerding, S. Stein, S. D. Ramchurn, N. Bassiliades, “Mechanism design for efficient allocation of electric vehicles to charging stations. SETN 2020: 10-15
6. E. Rigas, S. Karapostolakis, N. Bassiliades, S. D. Ramchurn, “EVLibSim: A Tool for the Simulation of Electric Vehicles’ Charging Stations Using the EVLib Library”, Simulation Modelling Practice and Theory, Vol. 87, pp. 99-119, 2018.
7. E. Rigas, S. Ramchurn, N. Bassiliades, “Algorithms for Electric Vehicle Scheduling in Large-Scale Mobility-on-Demand Schemes”, Artificial Intelligence, Volume 262, September 2018, Pages 248-278.
8. E. Rigas, S. Ramchurn, N. Bassiliades, “Managing Electric Vehicles in the Smart Grid Using Artificial Intelligence: A Survey”, IEEE Transactions on Intelligent Transportation Systems, Vol. 16, No. 4, pp. 1619-1635, 2015.
9. M. Koufakis, E. Rigas, N. Bassiliades, S. Ramchurn, “Towards an Optimal EV Charging Scheduling Scheme with V2G and V2V Energy Transfer”, 7th IEEE International Conference on Smart Grid Communications (SmartGridComm 2016), 6-9 Nov 2016, Sydney, Australia, pp. 302-307
10. S. Karapostolakis, E. Rigas, N. Bassiliades, S. Ramchurn, “EVLib: A Library for the Management of the Electric Vehicles in the Smart Grid”, Proc. 9th Hellenic Conference on Artificial Intelligence (SETN ’16), Thessaloniki, Greece, May 18-20 2016, ACM, New York, USA, Article 13, 4 pages, 2016.
11. E. Rigas, S. Ramchurn, N. Bassiliades, “Algorithms for Electric Vehicle Scheduling in Mobility-on-Demand Schemes”, Proc. 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC), Las Palmas de Gran Canaria, Spain, 15-18 Sep 2015, pp. 1339-1344.
12. A. Seitaridis, E. Rigas, N. Bassiliades, S. Ramchurn, “Towards an Agent-based Negotiation Scheme for Scheduling Electric Vehicles Charging”, Proc. 13th European Conference on Multi-Agent Systems (EUMAS 2015), Athens, 17-18 December 2015, LNAI 9571, Springer, pp. 157-171, 2016.
13. E. Rigas, S. Ramchurn, N. Bassiliades, G. Koutitas, “Congestion Management for Urban EV Charging Systems”, 4th IEEE International Conference on Smart Grid Communications (SmartGridComm 2013), IEEE, Vancouver, Canada, 21-24 Oct 2013, 2013.