Abstract
The development of alternatives for urban mobility and public transportation has been promoted by the increasing concerns on the environmental issues in the recent years. Along with the evolution of battery technology and charging/discharging control methodology, the diesel buses have been replaced with the electric buses (EBs) gradually. In order to satisfy the increasing charging demand of EBs, the photovoltaic (PV) and energy storage system (ESS) are usually installed on- site, which can not only guarantee sufficient power supply for the transit center, but also decrease the service charge for capacity from the distribution system operator (DSO). Besides, through involving the vehicle- to-grid (V2G) mechanism, the EBs parking in the transit center can also supply power to mitigate the peak load. Considering uncertainty of the office base load, PV generation, and the random availability of EBs, a stochastic energy management approach for such EB transit center is urgently needed. In this study, we focus on minimizing the total cost of the transit center taking into account the service charge for capacity, the energy consumption cost, the battery degradation cost of ESS and EBs, and the power generation revenue. A detailed model is built to investigate the energy management operation in the system as well as the corresponding cost. Then, we decompose the non-linear optimization problem into two stages: In the first stage, we aim to mitigate the target peak load through a modified robust optimization over time (ROOT) approach; Based on the optimal target peak load, the charging/discharging schedule is optimized in the second stage. The corresponding algorithm is developed and the performance of the proposed approach is evaluated in the case study based on the actual data obtained from FortisAlberta and St. Albert Transit, AB, Canada.
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