EconPapers    
Economics at your fingertips  
 

Load flexibility evaluation of fast-charging stations considering Drivers' choice uncertainty and Price-varying spatial correlation

Mengjie Liu, Min Chen, Yixun Xue, Yujie Sheng and Qinglai Guo

Applied Energy, 2024, vol. 373, issue C, No S0306261924012662

Abstract: Power systems need flexible resources to support renewable energy integration, where electric vehicles (EVs) provide a prospective solution. This study utilizes a charging station operator as a spatial aggregator to evaluate load flexibility of fast-charging stations (FCSs) with price incentives. First, FCSs' load flexibility is related with drivers' charging station choice uncertainty. Therefore, this uncertainty is analyzed by the logistic regression model and real-world data is utilized to obtain the model parameters and clarify drivers' choice preferences. Second, the price-varying load-transfer probabilities and spatial correlation parameters among FCSs are analyzed. Based on them, the probability theory is employed to obtain the spatially correlated probability distribution of FCS loads with price incentives. Third, the evaluation model of FCSs' load flexibility with real characteristics is established with drivers' choice uncertainty and spatial correlation as the basis of building a future general virtual power plant that considers spatial correlations, considering that the flexibility range varies with the response probability in a single FCS and that the price-varying spatial correlation between multiple FCSs flexibility. Case studies validate the effectiveness of the proposed method. The results validate the driver preferences obtained from real-world data, the price-varying spatial correlation of FCSs for different types of drivers, and the feasibility of grid congestion alleviation with obtained FCSs' load flexibility.

Keywords: Electric vehicle; Fast-charging station; Load flexibility evaluation; Drivers' choice uncertainty; Price-varying spatial correlation (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261924012662
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:373:y:2024:i:c:s0306261924012662

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2024.123883

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:appene:v:373:y:2024:i:c:s0306261924012662