DocumentCode
157670
Title
Probabilistic analysis of stationary batteries performance to deal with renewable variability
Author
Costa, Inaldo C. ; da Rosa, Mauro A. ; Carvalho, Leonel M. ; Soares, F.J. ; Bremermann, Leonardo ; Miranda, V.
Author_Institution
UFSC - Fed. Univ. of Santa Catarina, Florianopolis, Brazil
fYear
2014
fDate
7-10 July 2014
Firstpage
1
Lastpage
6
Abstract
Stationary batteries are currently seen as an interesting solution to deal with the variability of the renewable energy sources. In the same way as other types of storage, e.g. pumped-hydro units, this new type of storage equipment can improve the use of Renewable Energy Sources (RES). Additionally, the stationary batteries location in the grid is not as physically constrained as other storage systems and can be optimally selected to maximize its overall benefits. This paper proposes a new methodology to represent the unique stochastic behavior of stationary batteries while integrated into an electrical power system. This methodology includes not only the technical restrictions of this type of storage system but also how its operation strategy affects its lifetime. The methodology was tested on a small test system, which is based on the IEEE-RTS 79, using sequential Monte Carlo simulation as its core to accurately reproduce the chronology of events of stationary batteries. The results of the simulation are focused on the potential impacts of these storage devices not only in terms of renewable energy used but also in the adequacy of supply.
Keywords
Monte Carlo methods; battery storage plants; probability; secondary cells; IEEE-RTS 79; electrical power system; probabilistic analysis; pumped-hydro units; renewable energy sources; renewable variability; sequential Monte Carlo simulation; small test system; stationary batteries performance; stochastic behavior; storage equipment; Batteries; Discharges (electric); Load modeling; Renewable energy sources; System-on-chip; US Department of Defense; Wind power generation; composite system adequacy assessment; sequential Monte Carlo simulation; stationary batteries; wind power;
fLanguage
English
Publisher
ieee
Conference_Titel
Probabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on
Conference_Location
Durham
Type
conf
DOI
10.1109/PMAPS.2014.6960665
Filename
6960665
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