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author:

Zheng, Wendi (Zheng, Wendi.) [1] | Zhang, Min (Zhang, Min.) [2] | Li, Yixin (Li, Yixin.) [3] | Shao, Zhenguo (Shao, Zhenguo.) [4] | Wang, Xiangjie (Wang, Xiangjie.) [5]

Indexed by:

EI

Abstract:

The ongoing growth of green vehicles had led to an increase in demand of cost-effective and driver-satisfactory hydrogen/electric vehicle aggregators (HEVAs). However, existing approaches for cost minimization of HEVA can lead to poor performance due to the inaccurate modelling of power–gas exchange system and neglection of schedulable characteristics of loads. Furthermore, the behaviour of drivers was rarely considered from a psychological perspective. To resolve these limitations, the optimal dispatch scheme of HEVA, equipped with reversible solid oxide cell (rSOC), is investigated by quantifying drivers’ charging decision response toward pricing stimuli. As the core of the bi-directional energy conversion, rSOC is modelled by considering the climbing power constraints and time-dependent restart-up cost. At the driver side, EVs are aggregated as clusters for efficient computation. Two charging modes are designed for drivers with incentive discounts. To measure the relationship between external factors and charging decision response, the stimuli-responsive charging decision estimation is proposed by introducing Weber–Fechner law (W–F Law). To minimum operation cost, a mixed integer nonlinear programming (MINP) method is presented. The results validate that the operation cost of HEVA can be decreased by 19.37%, and the maximum utilization of energy is realised in the proposed scheme. Additionally, the impacts of sizes of power–gas exchange devices are investigated for practical reference. Under a given charging demand, the proposed dispatch scheme can realise installation of smaller devices, and thereby, resulting in lower construction cost. © 2021 Hydrogen Energy Publications LLC

Keyword:

Charging (batteries) Cost effectiveness Electric load dispatching Energy conversion Integer programming Nonlinear programming Operating costs Solid oxide fuel cells (SOFC)

Community:

  • [ 1 ] [Zheng, Wendi]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350 108, China
  • [ 2 ] [Zheng, Wendi]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou University, Fuzhou; 350 108, China
  • [ 3 ] [Zhang, Min]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350 108, China
  • [ 4 ] [Zhang, Min]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou University, Fuzhou; 350 108, China
  • [ 5 ] [Li, Yixin]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350 108, China
  • [ 6 ] [Li, Yixin]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou University, Fuzhou; 350 108, China
  • [ 7 ] [Shao, Zhenguo]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350 108, China
  • [ 8 ] [Shao, Zhenguo]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou University, Fuzhou; 350 108, China
  • [ 9 ] [Wang, Xiangjie]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou; 350 108, China
  • [ 10 ] [Wang, Xiangjie]Fujian Smart Electrical Engineering Technology Research Center, Fuzhou University, Fuzhou; 350 108, China

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Source :

International Journal of Hydrogen Energy

ISSN: 0360-3199

Year: 2022

Issue: 13

Volume: 47

Page: 8502-8513

7 . 2

JCR@2022

8 . 1 0 0

JCR@2023

ESI HC Threshold:66

JCR Journal Grade:1

CAS Journal Grade:2

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 12

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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