Abstract
We propose a model of a battery switching station (BSS) for electric buses (EBs) that captures the predictability of bus operation. We schedule battery charging in the BSS so that every EB arrives to find a battery ready for switching. We develop an efficient algorithm to compute an optimal schedule. It uses dual decomposition to decouple the charging decisions at different charging boxes so that independent subproblems can be solved in parallel at individual charging boxes, making the algorithm inherently scalable as the size of the BSS grows. We propose a direct projection method that solves these subproblems rapidly. Numerical results illustrate that the proposed approach is far more efficient and scalable than generic algorithms and existing solvers.
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