LAPSE:2018.0582
Published Article
LAPSE:2018.0582
An Electric Bus Power Consumption Model and Optimization of Charging Scheduling Concerning Multi-External Factors
Yajing Gao, Shixiao Guo, Jiafeng Ren, Zheng Zhao, Ali Ehsan, Yanan Zheng
September 21, 2018
With the large scale operation of electric buses (EBs), the arrangement of their charging optimization will have a significant impact on the operation and dispatch of EBs as well as the charging costs of EB companies. Thus, an accurate grasp of how external factors, such as the weather and policy, affect the electric consumption is of great importance. Especially in recent years, haze is becoming increasingly serious in some areas, which has a prominent impact on driving conditions and resident travel modes. Firstly, the grey relational analysis (GRA) method is used to analyze the various external factors that affect the power consumption of EBs, then a characteristic library of EBs concerning similar days is established. Then, the wavelet neural network (WNN) is used to train the power consumption factors together with power consumption data in the feature library, to establish the power consumption prediction model with multiple factors. In addition, the optimal charging model of EBs is put forward, and the reasonable charging time for the EB is used to achieve the minimum operating cost of the EB company. Finally, taking the electricity consumption data of EBs in Baoding and the data of relevant factors as an example, the power consumption prediction model and the charging optimization model of the EB are verified, which provides an important reference for the optimal charging of the EB, the trip arrangement of the EB, and the maximum profit of the electric public buses.
Keywords
modeling of power consumption, multi external factors, optimal charging scheduling, similar day selection, the grey relational analysis, wavelet neural network
Suggested Citation
Gao Y, Guo S, Ren J, Zhao Z, Ehsan A, Zheng Y. An Electric Bus Power Consumption Model and Optimization of Charging Scheduling Concerning Multi-External Factors. (2018). LAPSE:2018.0582
Author Affiliations
Gao Y: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
Guo S: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
Ren J: State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Baoding 071003, China
Zhao Z: Department of Automation, North China Electric Power University, Baoding 071003, China
Ehsan A: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China [ORCID]
Zheng Y: Energy Research Institute, Academy of Macroeconomic Research, NDRC, Beijing 100038, China
[Login] to see author email addresses.
Journal Name
Energies
Volume
11
Issue
8
Article Number
E2060
Year
2018
Publication Date
2018-08-08
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en11082060, Publication Type: Journal Article
Record Map
Published Article

LAPSE:2018.0582
This Record
External Link

doi:10.3390/en11082060
Publisher Version
Download
Files
[Download 1v1.pdf] (3.9 MB)
Sep 21, 2018
Main Article
License
CC BY 4.0
Meta
Record Statistics
Record Views
562
Version History
[v1] (Original Submission)
Sep 21, 2018
 
Verified by curator on
Sep 21, 2018
This Version Number
v1
Citations
Most Recent
This Version
URL Here
https://psecommunity.org/LAPSE:2018.0582
 
Original Submitter
Calvin Tsay
Links to Related Works
Directly Related to This Work
Publisher Version