Year: 2019
Type: conference-paper
Abstract: This paper proposes a novel limited activation matching pursuits (LAMP) method to monitor the number of eclectic vehicles (EVs) connected at a charging station and their charging activities. LAMP is able to reflect the two-dimensional characteristics of the number and charging time of the EVs. Constraints are entered on the activation coefficients of the matching pursuits to avoid over matching a particular type of EV. The method includes the development of the basis based on typical EV charging profiles and the improvement of matching pursuits. A case study is undertaken based on real EV data collected from London. The results show that 79.35% EVs can be accurately detected in charging station load profile duration of one week. The number of EVs connected within each half hour can be identified with a relative mean absolute deviation (RMAD) of 21.18%.
Source: Energy Procedia
Authors: Shuangyuan Wang, Ran Li, Adrian Evans, Furong Li
Institution: University of Bath
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W2918881199