EV Charging Load Prediction and Electricity–Carbon Joint Trading Model
Source abstract
Abstract
With the large-scale integration of electric vehicles (EVs) into the power grids, the disorderly charging of EVs may cause local overload and exacerbate peak-valley load difference. The current pricing strategies primarily focus on the supply side while neglecting user urgent charging demands and the impact of carbon trades; hence, an electricity–carbon joint pricing strategy is proposed in this paper. The strategy includes the selection of optimal charging modes based on the charging demand emergency, charging service satisfaction indicators, as well as the establishment of an electricity–carbon joint trading framework. A Stackelberg game model is further developed between the charging stations (CS) and EV users, which is solved under Karush–Kuhn–Tucker (KKT) conditions and duality theory. Simulation experiments have been performed, and the results demonstrate that this strategy can smooth the grid supply and reduce the CS operational costs via the increased carbon revenue while simultaneously satisfying EV users’ emergency power demands.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electric Vehicles and Infrastructure · Smart Grid Energy Management · Transportation and Mobility Innovations
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical and Control Engineering, Guilin University of Technology, Guilin 541006, China
Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
School of International Relations, Sun Yat-sen University, Guangzhou 510275, China
Faculty of Business and Law, Curtin University, Bentley, WA 6102, Australia
Funding
National Key R&D Program of China · National Natural Science Foundation of China · Shenzhen Science and Technology Innovation Commission Project
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