Planning of Regional Urban Bus Charging Facility: A Case Study of Fengxian, Shanghai

Abstract

The electrification of public transport is of great significance to alleviating environmental pollution and energy problems. The construction of charging stations for electric buses (EBs) is the key step for the electrification of public transport and receives more and more attention. This paper proposes a new urban electric bus charging station planning algorithm which consists of two parts, park-maintaining (PM) charging station planning and midway supply (MS) charging station planning. Firstly, bus routes are classified based on charging demands. Accordingly, the PM charging station planning model is divided into full slow charging (FSC) model, Bus Rapid Transit (BRT) model and Hybrid model. Secondly, the improved grid AP algorithm is applied to plan MS charging stations to enhance the EB operation reliability. Then by multi-terminal charging pile optimization model, the economics of charging facilities construction is enhanced. Finally, via an ordered control charging algorithm, the economic profits of overall planning schemes are enhanced. The bus system in Fengxian, Shanghai is taken as an example to demonstrate the proposed method. Results prove that the proposed method can effectively meet the charging demands of EBs and improve the operating reliability of the EB system.

Research Progress and Prospects of Public Transportation Charging Station Layout Methods

“…On the other hand, to obtain the charging demand of electric buses, Wu [13] started from the actual operation scheduling of public transportation, obtained the spatial and temporal distribution characteristics of buses based on the operation scheduling data, and simulated the daily operation based on the spatial and temporal distribution characteristics. Similarly, Wang [14] calculated the charging demand of daytime buses based on their daily operating cycles and scheduling arrangements. Chen [15] conducted a more detailed study on the charging demand.…”

“…Year Classification and Data Support Majidpour et al [4] 2016 Station side; customer profile and socket data Zhang et al [5] 2021 Station side; traffic flows of road sections and open index of parking lots Arias et al [6] 2017 Station side; arrival rates of vehicles at road sections near charging stations Nicolaides et al [12] 2019 Bus side; bus speed, positional coordinates, and electric motor performance Wang et al [14] 2022 Bus side; daily bus operating cycles and scheduling arrangements Su et al [16] 2019 Bus side; EV fleet composition, market share, and charging patterns…”