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Abstract
The penetration of wind power into the power system has been increasing in the recent years. Therefore, a lot of concerns related to the reliable operation of the power system have been addressed. An attractive solution to minimize the limitations faced by the wind power grid integration is to integrate lithium-ion batteries into virtual power plants; thus, the power system stability and the energy quality can be increased. The selection of the best lithium-ion battery candidate for integration with wind power plants is a key aspect for the economic feasibility of the virtual power plant investment. This paper presents a methodology for selection, between three candidates, of a Li-ion battery which offers long cycle lifetime at partial charge/discharge (required by many grid support applications) while providing a low cost per cycle also. For the selected Li-ion battery an impedance-based diagnostic tool for lifetime estimation was developed and verified. This diagnostic tool can be extended into an impedance-based lifetime model that will be able to predict the remaining useful lifetime of Li-ion batteries for specific grid support applications.
Original language | English |
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Title of host publication | Proceedings of the 15th European Conference on Power Electronics and Applications, EPE 2013 |
Number of pages | 10 |
Publisher | IEEE Press |
Publication date | 2013 |
Article number | 6634755 |
ISBN (Print) | 9781479901159 |
ISBN (Electronic) | 978-147990116-6, 9781479901142 |
DOIs | |
Publication status | Published - 2013 |
Event | European Conference on Power Electronics and Applications, EPE 2013 - Lille, France Duration: 3 Sept 2013 → 5 Sept 2013 http://www.epe2013.com/ |
Conference
Conference | European Conference on Power Electronics and Applications, EPE 2013 |
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Country/Territory | France |
City | Lille |
Period | 03/09/2013 → 05/09/2013 |
Internet address |
Fingerprint
Dive into the research topics of 'Selection and impedance based model of a lithium ion battery technology for integration with virtual power plant'. Together they form a unique fingerprint.Projects
- 1 Finished
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ALPBES: Advanced Lifetime Predictions of Battery Energy Storage
Kær, S. K. (Project Participant), Andreasen, S. J. (Project Participant), Teodorescu, R. (Project Participant), Stroe, A.-I. (Project Participant), Barreras, J. V. (Project Participant), Khan, M. R. (Project Participant) & Swierczynski, M. J. (Project Participant)
DSF The Danish Council for Strategic Research
01/02/2013 → 30/08/2017
Project: Research