Impacts of photovoltaic and energy storage system adoption on public transport: A simulation-based optimization approach

Abstract

Photovoltaic and energy storage system (PESS) adoption in public transport (PT) can offer a promising alternative towards reducing the charging and carbon emission costs of transit agencies. However, the quantitative impacts of PESS on operational cost, carbon emission cost, bus scheduling, and energy management in PT remain unclear. This study is performed with the aim of filling this research gap by presenting an impact analysis framework incorporating multisource datasets and a simulation-based optimization approach. A simulation is designed to capture bus scheduling and energy management on a day-to-day transit operation. A surrogate-based optimization method is adopted to determine an optimal PESS configuration for battery electric bus (BEB) charging stations. A case study is performed by introducing PESS at BEB charging stations in Beijing, China, leveraging historical weather and bus operational data. Compared with conventional charging stations, the novel transit system with PESS reduces the annual charging costs and carbon emissions of a single bus route in this case study by 17.6% and 8.8% on average, respectively. The results suggest that the recycling electricity price of PV generation is the key to influencing charging costs and carbon emissions. Battery capacities also impact the scheduling pattern of PESS considerably. Further comparison across five bus routes in Beijing reveals that the deployment locations of PESS are key decisions influencing the operational cost and carbon emissions in PT at the network level when the investment budget is limited.