Jul 2026· International Conference on Control, Decision and Information Technologies· pp. 569-574· 0 citations· 13 references
Abstract
The large-scale deployment of electric vehicles poses significant challenges for distribution grids, particularly in charging parks with limited network capacity. This paper proposes a fair and grid-aware charging management system based on a receding-horizon game formulation. The coordinated charging problem is modeled as a variational generalized Nash equilibrium (GNE), enabling the allocation of charging power among self-interested vehicles under shared grid constraints. Individual objectives capture price signals, charging smoothness, and terminal energy targets, while electricity network limits are explicitly enforced. In a practice-oriented weekly scenario with limited charging infrastructure, the method enforces the transformer constraint at all times and shows that a 2 h charging-time policy eliminates severe shortfalls above 16 kWh, at the cost of higher shortfalls for some vehicles. These results indicate that the proposed receding-horizon v-GNE formulation provides a transparent mechanism for grid-compliant and fairness-oriented charging coordination.
A collaborative optimization framework based on multi-agent reinforcement learning is proposed for orderly charging at electric vehicle charging stations and coordinated interaction with the power grid, providing a technical reference for intelligent charging coordination under grid interaction and electromagnetic comp...
High-penetration electric-vehicle charging increasingly couples charging-service operation with distribution-network voltage security. However, existing pricing strategies often optimize user response or station profit separately from feeder-side voltage constraints. This paper proposes a coordinated rolling optimizati...
: Random vehicle arrivals, heterogeneous charging demands, and the station-level limit on aggregate electric vehicle (EV) charging power pose simultaneous challenges to event-driven ordered charging in terms of causal information constraints, charging economics, and aggregate-load coordination. Existing full-informatio...
Li-Xiao Wang, Jia-Qi Li, Hai-Feng Li et al.· Energy Engineering· 0 citations
As electric vehicle (EV) adoption grows, quantifying the scheduling burden and economic cost of long-distance travel under the existing charging infrastructure becomes increasingly important for infrastructure planning and policy. This paper presents a scalable, optimization-based framework for scheduling EV charging s...
Electric vehicles (EVs) are a key enabler of global decarbonization, and their charging flexibility is crucial for integrating high shares of renewable energy into future power systems. Research on EV charging flexibility in future power systems has largely focused on either the transmission or the distribution level,...
Ambra Van Liedekerke, Lorenzo Zapparoli, Maria Parajeles Herrera et al.· arXiv.org· 0 citations
This paper proposes a tripartite hybrid game-theoretic pricing model for the vehicle-station-grid framework that accounts for the interest demands of all stakeholders. The model aims to balance interests among different stakeholders while guiding charging behavior of electric vehicle (EV) users within the context of gr...
Ning Zhang, Zhong-Qiang Zhang, Juan Yan et al.· IEEE Transactions on Automat...· 0 citations
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