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Regional non-intrusive electric vehicle monitoring based on graph signal processing.
- Source :
-
IET Generation, Transmission & Distribution (Wiley-Blackwell) . 2020, Vol. 14 Issue 26, p6512-6517. 6p. - Publication Year :
- 2020
-
Abstract
- Electricity network is leading to a low carbon future with high penetration of plug-in electric vehicles (EVs). However, it is extraordinarily difficult to acquire detailed information on regional EV electrification with an incomplete monitoring system for network operators. In this study, a flexible graph signal processing (GSP)-based non-intrusive monitoring on aggregated EVs is proposed to enhance the EVs visibility for operating power system safely and cost-efficiently. It can deduce the individual EV charging status with the highest possibility iteratively from the limited dataset using a GSP-based possibility calculation after processing a daytime EV characteristic charging patterns. The experiment is developed with realistic EV charging datasets collected in London, and the results show the daily EVs number in a specific region of 500 EVs daily aggregation can be estimated efficiently with an around 4.77% value of relative mean absolute deviation applying the proposed method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 17518687
- Volume :
- 14
- Issue :
- 26
- Database :
- Academic Search Index
- Journal :
- IET Generation, Transmission & Distribution (Wiley-Blackwell)
- Publication Type :
- Academic Journal
- Accession number :
- 149245685
- Full Text :
- https://doi.org/10.1049/iet-gtd.2020.0845