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This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that make battery swapping requests to a central operator, with the aim of minimizing cost to EVs and congestion at service stations. Inspired by a polynomial-time solvable offline solution via a bipartite matching approach, we develop an efficient online station assignment algorithm that provably achieves a tight (optimal) competitive ratio under mild conditions.

This paper investigates the online station assignment for (commercial) electric vehicles (EVs) that make battery swapping requests to a central operator, with the aim of minimizing cost to EVs and congestion at service stations. Inspired by a polynomial-time solvable offline solution via a bipartite matching approach, we develop an efficient online station assignment algorithm that provably achieves a tight (optimal) competitive ratio under mild conditions.

This work investigates the increasing interactions between power network dynamics and market dynamics. A dynamical spot pricing mechanism for rational market behavior of generators and loads is designed to model market dynamics, which provably drives a power network to an equilibrium operating point, achieving secondary frequency control and economic dispatch.