LAPSE:2021.0713
Published Article
LAPSE:2021.0713
Multi-Objective Coordinated Optimal Allocation of DG and EVCSs Based on the V2G Mode
Lijun Liu, Feng Xie, Zonglong Huang, Mengqi Wang
September 16, 2021
With the vigorous promotion of new energy sources and the development of vehicle-to-grid (V2G) technology, the influence of the V2G mode should be considered in the joint optimal allocation of Distributed Generation (DG) and electric vehicle charging stations (EVCSs). The timing characteristics of the intermittent output of DG, conventional demand for load, and charging load of the electric vehicle (EV) are considered, as is its participation in grid interaction to examine the construction of typical scenarios and the EV cluster dispatching strategy. From the perspective of comprehensively planning the coordination of the distribution network, a DG-EVCSs bi-level joint planning model is established under the peak and valley price mechanism, with the sub-objectives of obtaining a comprehensive profit and high quality of voltage, curbing system load fluctuations, and satisfactorily charging the EV. An improved harmony particle swarm optimization algorithm is proposed to solve the bi-level model. The proposed method was tested on the IEEE-33 and the PG&E-69 (Pacific Gas and Electric Company) bus distribution systems, and the results show that the optimized configuration model that considers the V2G mode can improve the overall performance of the planning scheme, promote the use of clean energy, smoothen the load fluctuations of the system, and improve the quality of voltage and charging satisfaction of EV users.
Keywords
cluster dispatching, distributed power supply, EV charging station, peak and valley electricity prices, V2G mode
Suggested Citation
Liu L, Xie F, Huang Z, Wang M. Multi-Objective Coordinated Optimal Allocation of DG and EVCSs Based on the V2G Mode. (2021). LAPSE:2021.0713
Author Affiliations
Liu L: Department of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China [ORCID]
Xie F: Department of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
Huang Z: State Grid Quanzhou Power Supply Company, Quanzhou 362018, China
Wang M: Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI 48128, USA
Journal Name
Processes
Volume
9
Issue
1
First Page
pr9010018
Year
2020
Publication Date
2020-12-23
Published Version
ISSN
2227-9717
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Original Submission
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PII: pr9010018, Publication Type: Journal Article
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LAPSE:2021.0713
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doi:10.3390/pr9010018
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Sep 16, 2021
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Sep 16, 2021
 
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Calvin Tsay
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