Abstract
This study aims to plan a cost-minimizing charging schedule for electric buses with fast charging stations. The paper conceptualizes the problem as a three-stage procedure, which is oriented around the participation of an electric bus aggregator in a day-ahead energy auction. First, the aggregation stage determines the bid parameters of buses. With bid parameters, aggregated cost-minimizing charging plans are obtained in the second stage conceived as the hourly day-ahead auction. The disaggregation of hourly plans into feasible minutely charging schedules is the third stage. The main contribution is the formulation of mixed-integer linear programming aggregation models to determine charging availability expressed as minimum and maximum hourly energy requirements taking into account detailed, minutely characteristics and constraints of the charging equipment and the buses. No price forecasts are required, and the plans adjust to the wholesale prices of energy. Defining only a few aggregated bids parameters used in linear programming constraints and incorporating them into the auction model is another contributing factor of this paper, allowing the scheduling of storage-based participants economically. The proposed methodology has been verified on a recently published case study of a real-world bus service operated on the Ohio State University campus. We show that the auction-based charging of all 22 buses outperforms as-soon-as-possible schedules by 7% to even 28% of daily cost savings. Thanks to the aggregated bids, buses can flexibly shift charges between high- and low-price periods while preserving constraints of the charging equipment and timetables.
Highlights
According to the plans for the electrification of public transport around the world, we are facing a profound change toward electric bus adoption [1]
We propose the aggregation of periods and buses to let the buses aggregator participate in the day-ahead energy auction and flexibly adjust to uncertain hourly market prices
The most challenging phase is developing MILP aggregation models: they consist of a multiperiod model determining minimum aggregated SoC level at the end of each hour, complemented by models setting the maximum amounts of energy that can be loaded solved separately for each hour
Summary
According to the plans for the electrification of public transport around the world, we are facing a profound change toward electric bus adoption [1]. One of the foremost anticipated challenges related to this growth is in the design and planning of the electric bus charging system [2]. Active demand-side participation enabled by bus aggregators can create an opportunity for mutual benefits, both for transport entities and the power system [5]. It is a challenging issue, as, on the one hand, the constraints of bus timetables and charging infrastructure must be handled, and on the other hand charging flexibility must be transformed into bids that can be traded in the electricity auction [6].
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