Coordinated charging and discharging strategies for plug‐in electric bus fast charging station with energy storage system. Issue 9 (14th March 2018)

• Record Type: Journal Article
• Authors: Chen, Huimiao; Hu, Zechun; Zhang, Hongcai; Luo, Haocheng
• Is Part Of: IET generation, transmission & distribution. Volume 12:Issue 9(2018)
• Page Start: 2019
• Page End: 2028
• Publication Date: 2018-03-14
• Subjects: battery powered vehicles -- public transport -- pricing -- electric vehicle charging -- energy storage; coordinated charging -- discharging strategies -- plug‐in electric bus fast charging station -- energy storage system -- public transportation -- PEB fast charging stations -- PEBFCS -- maximum economic benefits -- electricity price arbitrage -- heuristics‐based method -- ESS capacity; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2017.0636
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Plug‐in electric bus (PEB) is an environmentally friendly mode of public transportation and PEB fast charging stations (PEBFCSs) play an essential role in the operation of PEBs. Under effective control, deploying an energy storage system (ESS) within a PEBFCS can reduce the peak charging loads and the electricity purchase costs. To deal with the (integrated) scheduling problem of (PEBs charging and) ESS charging and discharging, in this study, the authors propose an optimal real‐time coordinated charging and discharging strategy for a PEBFCS with ESS to achieve maximum economic benefits. According to whether the PEB charging loads are controllable, the corresponding mathematical models are, respectively, established under two scenarios, i.e. coordinated PEB charging scenario and uncoordinated PEB charging scenario. The price and lifespan of ESS, the capacity charge of PEBFCS and the electricity price arbitrage are considered in the models. Further, under the coordinated PEB charging scenario, a heuristics‐based method is developed to get the approximately optimal strategy with computation efficiency dramatically enhanced. Finally, the authors validate the effectiveness of the proposed strategies, interpret the effect of ESS prices on the usage of ESS and provide the sensitivity analysis of ESS capacity through the case studies.