Estimation of variability and predictability of large‐scale wind energy in The Netherlands

摘要: This paper presents a data-driven approach for estimating the degree of variability and predictability associated with large-scale wind energy production planned integration in given geographical area, an application to The Netherlands. A new method is presented generating realistic time series aggregated power realizations forecasts. To this end, simultaneous speed series—both actual predicted—at farm locations are needed, but not always available. 1-year data set 10-min averaged speeds measured at several weather stations used. measurements first transformed from sensor height hub height, then spatially interpolated using multivariate normal theory, finally over market resolution interval. Day-ahead forecast created atmospheric model HiRLAM (High Resolution Limited Area Model). Actual forecasted passed through multi-turbine curves summed up create power. Two insights derived developed set: long-term when Dutch national or participant level. For 7.8 GW installed scenario, system level, imbalance requirements due variations across 15-min intervals ±14% total capacity, while errors vary between 53% down- 56% up-regulation. When aggregating balancing 2–3% higher. Copyright © 2008 John Wiley & Sons, Ltd.