Joint Optimization of Regular Charging Electric Bus Transit Network Schedule and Stationary Charger Deployment considering Partial Charging Policy and Time-of-Use Electricity Prices

Abstract

Electric buses (EBs) have been implemented worldwide and exhibited great potential for air pollution reduction and traffic noise control. In regular charging scenarios, the deployment of charging facilities and the operational scheduling of the transit system is crucial to bus transit system management. In this paper, we proposed a joint optimization model of regular charging electric bus transit network schedule and stationary charger deployment considering partial charging policy and time-of-use electricity prices. The objective of the model is to minimize the total investment cost of the transit system including the capital and maintenance cost of EBs and chargers, the power consumption cost, and time-related in-service cost. A solving procedure based on the improved adaptive genetic algorithm (AGA) is further designed and a transit network at inner Anting Town, Shanghai, with 8 individual bus routes and 867 daily service trips is adopted for the model validation. The validation results illustrated that the methodology considering the partial charging policy can arrange the charging schedule adaptive to the time-of-use electricity prices. Compared with the benchmark of single line separate scheduling, the proposed model can yield 3 million RMB investment saving by highly utilizing EBs and battery chargers.