Answers are grounded in this paper and cite their sources.
A battery charging station (BCS) is a charging facility that supplies electric energy for recharging electric vehicles' depleted batteries (DBs). A BCS has a certain number of charging bays and maintains a dynamic inventory of fully charged batteries (FBs). This paper studies a BCS scheduling (BCSS) problem whose target is to schedule the charging processes of the charging bays such that the charging cost is minimized while satisfying the FB demand. Specifically, the BCSS problem has two types of operations: 1) loading DBs into the charging bays and then unloading them to the FB inventory when they are fully charged and 2) controlling the charging rate of each charging bay. We formulate the BCSS problem as a mixed-integer program with quadratic battery degradation cost. A generalized benders decomposition algorithm is then developed to solve the problem efficiently. The salience of the developed algorithm is that: 1) each charging bay can solve its own subproblem separately and 2) each subproblem can be further partitioned into multiple independent and identically structured quadratic programming problems, and thus the algorithm facilitates an efficient parallel implementation. We perform extensive real data simulation to validate the optimization model and demonstrate the efficiency of the proposed algorithm.
No takes yet. Share an insight, caveat, or question.
Tan et al. (2017) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: