Smart City Gnosys

Smart city article details

Title	Ai-Empowered Game Theoretic-Enabled Dynamic Electric Vehicles Charging Price Scheme In Smart City
ID_Doc	7054
Authors	Chavhan S.; Gupta D.; Alkhayyat A.; Alharbi M.; Rodrigues J.J.P.C.
Year	2023
Published	IEEE Systems Journal, 17, 4
DOI	http://dx.doi.org/10.1109/JSYST.2023.3307497
Abstract	The huge number of electric vehicles (EVs) penetration resulted in the rapid deployment of charging stations as well as an increase in electricity demands. Due to this, there is a growing interest in the load balance in the power grid. In the power grid, whenever there is a decrease in the overall usable voltage and reactive power, harmonics will be injected, which affects the overall power quality of the grid. In addition to the abovementioned issues, most of the existing works face issues, such as an imbalance of load at the grid, inefficient utilization of resources, and nonoptimal power transactions cost. To reduce and avoid the abovementioned issues, we propose a real-time intelligent method-based energy utilization, conservation, and optimal price at the grid and charging stations using artificial intelligence (AI). We develop the IEEE 69 bus test system and analyze the grid and charging stations. Using the analyzed factors of the grid and charging station, designed an edge-computing enabled optimal charging price scheme using the game theoretic approach. The designed system provides efficient utilization, energy conservation, and adaptive optimal charging price for EVs at charging stations. Discrete-time event simulator is developed to test the proposed scheme with parameters, such as arrival rates, queue length, and reactive power. The proposed scheme's results (analytical, simulation, and comparison) show adaptability and realism. © 2007-2012 IEEE.
Author Keywords	Artificial intelligence (AI); charging stations (CSs); dynamic charging prices; edge computing; electric vehicles (EVs); energy conservation; game theory; smart city

Similar Articles

Id	Similarity	Authors	Title	Published
7022	0.907	Khan A.A.; Mahendran R.K.; Ullah F.; Ali F.; Bashir A.K.; Dabel M.M.A.; Omar M.	Ai-Driven Dynamic Allocation And Management Optimization For Ev Charging Stations	IEEE Transactions on Intelligent Transportation Systems (2025)
4133	0.891	Qaisar S.M.; Alyamani N.	A Review Of Charging Schemes And Machine Learning Techniques For Intelligent Management Of Electric Vehicles In Smart Grid	Managing Smart Cities: Sustainability and Resilience Through Effective Management (2022)
38094	0.889	Pok P.J.; Yeo H.; Woo S.	Multi-Agent Game-Theoretic Modelling Of Electric Vehicle Charging Behavior And Pricing Optimization In Dynamic Ecosystems	Procedia Computer Science, 257 (2025)
35913	0.879	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)
40790	0.879	Suanpang P.; Jamjuntr P.	Optimizing Electric Vehicle Charging Recommendation In Smart Cities: A Multi-Agent Reinforcement Learning Approach	World Electric Vehicle Journal, 15, 2 (2024)
36044	0.877	Neelakantam G.	Machine Learning-Based Decision Making For Charging/Discharging Cost Optimization Of Prev In Smart City	Proceedings of the 1st International Symposium on Parallel Computing and Distributed Systems, PCDS 2024 (2024)
30935	0.876	Youness H.; Mohamed T.; Ahmed G.; Hajar A.; Benachir E.L.H.	Improving The Effectiveness Of Electric Vehicle Charging Infrastructure Within A Smart City Using Artificial Neural Networks (Ann) And The Internet Of Vehicles (Iov)	Proceedings of the International Conference on Microelectronics, ICM (2024)
40628	0.876	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)
32353	0.875	Dey S.; Xu H.	Intelligent Distributed Charging Control For Large Scale Electric Vehicles: A Multi-Cluster Mean Field Game Approach	ACM International Conference Proceeding Series (2023)
8508	0.874	Senthilkumar T.; Sivaraju S.S.; Anuradha T.; Vimalarani C.	An Intelligent Electric Vehicle Charging System In A Smart Grid Using Artificial Intelligence	Optimal Control Applications and Methods, 46, 3 (2025)