A multi-stage optimization framework for battery electric bus deployment and renewable energy hubs with stochastic energy management and resilience analysis

Artikel i vetenskaplig tidskrift, 2027

The global electrification of bus fleets has advanced significantly in recent years, yet critical technological and operational challenges persist. First, many existing methodologies for battery electric bus (BEB) deployment focus on cost minimization, often using just enough charging stations to meet demand. This limited setup creates rigid schedules that are vulnerable to delays or charger failures, leading to charging station congestion and service disruptions. Second, large-scale BEB systems often depend on both in-depot and on-route charging, resulting in high charging costs. To address these challenges, this study proposes a multi-stage optimization framework. Stage 1 ensures a cost-effective and robust deployment plan by considering in-depot charging activities, differentiated charger costs and integrating mobile charging units (MCUs) as backup solutions. Stage 2 transforms charging stations into profitable renewable energy hubs by incorporating solar photovoltaic (PV) systems and battery energy storage to reduce grid dependence and generate revenue through surplus energy sales. Stage 3 develops detailed MCU operational strategies to mitigate the impacts of charger failures and bus line delays. The model is applied to a city-scale public transit network in the State of Utah, United States. Results show that MCUs significantly reduce the operational delays and enhance system resilience, while the integration of PV and storage reduces charging costs and increases profitability, particularly during summer months. A comprehensive sensitivity analysis is conducted to identify the most influential parameters affecting system cost, energy performance, and resilience. This research offers practical guidance for public transit agencies in both BEB deployment and renewable energy investment planning.