Designing an Electric Transit Route Network Utilizing Energy Storage Technology to Mitigate Annual Demand Charge

Abstract

The electrification of traditional transit route networks has been a promising option for urban public transit. Compared with fast chargers, energy storage (ES) technology benefits the planner in relation to cost savings and avoiding high electricity demand charges. Although many studies ignored the potentiality of utilizing ES chargers, this study uses this concept with demand charges to design an electric transit route network by proposing a bi-level optimization model. The upper-level model aims to minimize the total travel times of passengers along with the total number of indirect trips. In comparison, the lower-level problem plans to minimize the total costs of purchasing two types of fast and ES chargers and demand charges for the transit network that entirely operates with battery electric buses (BEBs). Because of the NP-hard nature of the proposed model, the discrete multi-objective grey wolf optimizer algorithm is suggested in a discrete space to search for a feasible solution by providing the Pareto frontier of two objective functions. Also, the initial route set generation algorithm has been applied to generate a new set of transit routes. To validate the proposed model, our model has been tested on a benchmark network of Mumford0 in a small and a Fargo–Moorhead area in a medium size. Our results confirmed that considering ES chargers could save 4.8% and 76.5% (for the user cost), 2.3%, and 111.9% (for the operator cost) of the total network and demand charges.