Evaluating grid-interactive electric bus operation and demand response with load management tariff
File(s)Wu-Guo-Polak-Strbac-AE-accepted-2019.pdf (2.03 MB)
Accepted version
Author(s)
Wu, Zongxiang
Guo, Fangce
Polak, John
Strbac, G
Type
Journal Article
Abstract
Electric Vehicles are expected to play a vital role in the transition of smart energy systems. Lots of recent research has explored numerous underlying mechanisms to achieve the synergetic interactions in the electricity balancing process. In this paper, the grid-interactive operation of electric buses is first time integrated within a dynamic market frame using the Distribution Locational Marginal Price algorithm for load congestion management. Since the defined problem correlates the opportunity charging flexibility with the bus mobility over a network, the tempo-spatial distribution of energy needs can be reflected in the dynamic of service planning. The interactions between bus operators and suppliers are quantitatively modelled by a bi-level optimisation process to represent the electric bus service planning and electricity market clearing separately. The effectiveness of the proposed load management has been demonstrated using data collected from an integrated real-world bus network. Experiments show that engagement of electric bus charging load in demand response is helpful to alleviate the network congestion and to reduce the power loss by 7.2% in the distribution network. However, alleviated charging loads have exhibited counter-intuitive ability for load shifting. The restricted electric bus operational requirements leads to a 8.17% loss of charging demand, while the reliance on large batteries has increased by 10.57%. However, the sensitivity analysis also shows that as the battery cost declines, the such discourage implications on grid-interactive electric bus operation will decrease once the battery cost below 190/kWh. The optimal grid-ebus integration have to consider the trade-off between range add-up, reduced battery cost and additional benefits.
Date Issued
2019-12-01
Date Acceptance
2019-08-27
Citation
Applied Energy, 2019, 255, pp.1-12
ISSN
0306-2619
Publisher
Elsevier
Start Page
1
End Page
12
Journal / Book Title
Applied Energy
Volume
255
Copyright Statement
© 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Identifier
https://www.sciencedirect.com/science/article/pii/S0306261919314850?via%3Dihub
Grant Number
EP/L001039/1
Subjects
Science & Technology
Technology
Energy & Fuels
Engineering, Chemical
Engineering
Electric bus
Opportunity charging
Demand response
Distribution Locational Marginal Price
Congestion load management
Bi-level optimisation
RELIABILITY TEST SYSTEM
COST-BENEFIT-ANALYSIS
EDUCATIONAL PURPOSES
VEHICLE
OPTIMIZATION
INTEGRATION
TRANSPORT
SERVICE
Energy
09 Engineering
14 Economics
Publication Status
Published
Date Publish Online
2019-09-13