We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Energy storage sizing for wind power: impact of the autocorrelation of day-ahead forecast errors.
- Authors
Haessig, Pierre; Multon, Bernard; Ahmed, Hamid Ben; Lascaud, Stéphane; Bondon, Pascal
- Abstract
ABSTRACT The availability of day-ahead production forecast is an important step toward better dispatchability of wind power production. However, the stochastic nature of forecast errors prevents a wind farm operator from holding a firm production commitment. In order to mitigate the deviation from the commitment, an energy storage system connected to the wind farm is considered. One statistical characteristic of day-ahead forecast errors has a major impact on storage performance: errors are significantly correlated along several hours. We thus use a data-fitted autoregressive model that captures this correlation to quantify the impact of correlation on storage sizing. With a Monte Carlo approach, we study the behavior and the performance of an energy storage system using the autoregressive model as an input. The ability of the storage system to meet a production commitment is statistically assessed for a range of capacities, using a mean absolute deviation criterion. By parametrically varying the correlation level, we show that disregarding correlation can lead to an underestimation of a storage capacity by an order of magnitude. Finally, we compare the results obtained from the model and from field data to validate the model. Copyright © 2013 John Wiley & Sons, Ltd.
- Subjects
WIND power research; ENERGY storage; AUTOREGRESSION (Statistics); ESTIMATION theory; DEVIATION (Statistics)
- Publication
Wind Energy, 2015, Vol 18, Issue 1, p43
- ISSN
1095-4244
- Publication type
Article
- DOI
10.1002/we.1680