Optimal design of a storage system coupled with intermittent renewables
Laurent Bridier,
Mathieu David and
Philippe Lauret
Renewable Energy, 2014, vol. 67, issue C, 2-9
Abstract:
In this paper, two ways of increasing the integration of wind and solar energy into the electricity grid through energy storage are analyzed. The first service (S1) to the electricity grid is related to a smoothed and hourly scheduled daily production while the second one (S2) concerns a constant and guaranteed minimal production. A power bid, based on meteorological forecasts, is transmitted a day ahead by the producer to the utility grid operator. This leads to a yearly default time rate for which the actual power supplied does not meet the announcement within a given tolerance. The modelling approach developed in this study enables to infer the optimal operation of the system and more specifically the optimal size of the energy storage, aiming at reducing the default time rate (DTR) under 5%. The simulations consider PV or wind with storage systems having discharge time in the range of minutes. Two real test cases are examined: Guadeloupe Island for wind and Reunion Island for PV. The results show that both of the two services can be achieved under specific conditions and that an optimal day-ahead power bid with a 2% DTR is possible with a storage capacity of 1 MWh per installed MWp. In addition, a linear strategy of forecasting this optimal power is highly correlated to the precision of upstream meteorological forecast.
Keywords: Wind power; Photovoltaics; Energy storage sizing; Optimization (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960148113006265
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:renene:v:67:y:2014:i:c:p:2-9
DOI: 10.1016/j.renene.2013.11.048
Access Statistics for this article
Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides
More articles in Renewable Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().