Abstract
The intermittent nature of wind resources is challenging for their integration into the electrical system. The identification of weather systems and the accurate forecast of wind ramps can improve wind-energy management. In this study, extreme wind ramps were characterized at four different geographical sites in terms of duration, persistence, and weather system. Mid-latitude systems are the main cause of wind ramps in Mexico during winter. The associated ramps last around 3 h, but intense winds are sustained for up to 40 h. Storms cause extreme wind ramps in summer due to the downdraft contribution to the wind gust. Those events last about 1 to 3 h. Dynamic downscaling is computationally costly, and statistical techniques can improve wind forecasting. Evaluation of the North American Mesoscale Forecast System (NAM) operational model to simulate wind ramps and two bias-correction methods (simple bias and quantile mapping) was done for two selected sites. The statistical adjustment reduces the excess of no-ramps (≤|0.5| m/s) predicted by NAM compared to observed wind ramps. According to the contingency table-derived indices, the wind-ramp distribution correction with simple bias method or quantile mapping method improves the prediction of positive and negative ramps.
Highlights
Atmosphere 2022, 13, 453. https://Wind energy is an alternative electricity generation prospect, and can reduce carbon dioxide emissions into the atmosphere, unlike fossil fuels
The statistical adjustment reduces the excess of no-ramps (≤|0.5| m/s) predicted by North American Mesoscale Forecast System (NAM) compared to observed wind ramps
The identification of meteorological phenomena causing wind ramps needs to be considered in the development of forecasting systems for wind farms to improve the predictability of wind ramps
Summary
Atmosphere 2022, 13, 453. https://Wind energy is an alternative electricity generation prospect, and can reduce carbon dioxide emissions into the atmosphere, unlike fossil fuels. The intermittent nature of this power source has prompted the development/refinement of wind forecasting systems. One aspect to consider when evaluating models is their ability to reproduce the high-frequency variations of the wind. These changes in the magnitude of the wind in periods ranging from minutes to hours are defined as ramps. Ramp events can represent a critical situation for energy systems, due to an energy imbalance and associated costs. Wind-power ramps obtained from wind farm records can originate from the management of the wind farm and are not necessarily associated with an atmospheric phenomenon [2]. Wind ramps reveal the presence of atmospheric phenomena such as cold fronts, hurricanes, storms, sea–land breezes, valley–mountain breezes, etc
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