On the spatio-temporal optimization for the charging scheduling of battery electric buses

Battery electric buses (BEBs) play a crucial role in advancing energy efficiency, reducing emissions, and fostering sustainable public transport. Opportunity charging technology has proven effective in alleviating BEB range anxiety. As BEB networks expand, designing an optimized charging schedule that accounts for spatio-temporal complexities becomes essential. This paper proposes an innovative optimization scheme that leverages the spatio-temporal characteristics of BEB networks. By employing variable charging power, the scheme balances TOU with grid loads. The problem is formulated as a nonlinear, non-convex program with continuous time variables and transformed into a solvable mixed-integer linear programming model via discrete-event-based linear reconstruction. Applied to a real BEB network in Shanghai, the results demonstrate a 7.83% reduction in charging costs by improving grid peak power and a 2.42% cost reduction by increasing charging piles across terminals.