Detecting and characterising ramp events in wind power time series

The Science of Making Torque from Wind 2012

Gallego, Cristóbal^1 ; Cuerva, Álvaro^2 ; Costa, Alexandre^3

DVA-ETSI.Aeronáuticos, Universidad Politécnica de Madrid, Madrid

28040, Spain^1

IDR-ETSI.Aeronáuticos, Universidad Politécnica de Madrid, Madrid

28040, Spain^2

Centro de Energias Renováveis, Universidade Federal de Pernambuco, Brazil^3

关键词: Binary classification;    Different time scale;    Large power;    Ramp events;    Ramp function;    Ramp up;    Time step;    Wind farm;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/555/1/012040/pdf
DOI  :  10.1088/1742-6596/555/1/012040

来源: IOP

【 摘 要 】

In order to implement accurate models for wind power ramp forecasting, ramps need to be previously characterised. This issue has been typically addressed by performing binary ramp/non-ramp classifications based on ad-hoc assessed thresholds. However, recent works question this approach. This paper presents the ramp function, an innovative wavelet- based tool which detects and characterises ramp events in wind power time series. The underlying idea is to assess a continuous index related to the ramp intensity at each time step, which is obtained by considering large power output gradients evaluated under different time scales (up to typical ramp durations). The ramp function overcomes some of the drawbacks shown by the aforementioned binary classification and permits forecasters to easily reveal specific features of the ramp behaviour observed at a wind farm. As an example, the daily profile of the ramp-up and ramp-down intensities are obtained for the case of a wind farm located in Spain.