Timescale classification in wind forecasting: A review of the state‐of‐the‐art

@article{Roungkvist2020TimescaleCI,
  title={Timescale classification in wind forecasting: A review of the state‐of‐the‐art},
  author={Jannik Sch{\"u}tz Roungkvist and Peter Enevoldsen},
  journal={Journal of Forecasting},
  year={2020},
  volume={39},
  pages={757-768}
}
The intermittency of the wind has been reported to present significant challenges to power and grid systems, which intensifies with increasing penetration levels. Accurate wind forecasting can mitigate these challenges and help in integrating more wind power into the grid. A range of studies have presented algorithms to forecast the wind in terms of wind speeds and wind power generation across different timescales. However, the classification of timescales varies significantly across the… 

Use of State-of-Art Machine Learning Technologies for Forecasting Offshore Wind Speed, Wave and Misalignment to Improve Wind Turbine Performance

TLDR
These models are vital to deploying and installing FOWTs and making them profitable and show that Nonlinear autoregressive with an exogenous input neural network (NARX) is the best algorithm for both wind speed and misalignment forecasting in the time domain and GPR for wave height.

Computation and Analysis of an Offshore Wind Power Forecast: Towards a Better Assessment of Offshore Wind Power Plant Aerodynamics

For the first time, the Weather Research and Forecast (WRF) model with the Wind Farm Parameterization (WFP) modeling method is utilized for a short-range wind power forecast simulation of 48 h of an

A Self-Adaptive Multikernel Machine Based on Recursive Least-Squares Applied to Very Short-Term Wind Power Forecasting

TLDR
A novel self-adaptive approach for kernel recursive least-squares machines named multiple challengers is introduced in this work, which is successfully used to produce very short-term wind power forecasts at eight wind farms in Australia.

Inter-event Times Statistic in Stationary Processes: Nonlinear ARMA Modeling of Wind Speed Time Series

  • C. Cammarota
  • Computer Science
    Nonlinear Phenomena in Complex Systems
  • 2021
TLDR
This work investigates the distribution of the inter-event times of the level-crossing events in ARMA processes in function of the probability corresponding to the level, and establishes a representation of this indicator, proves its symmetry and that it is invariant with respect to the application of a non linear monotonic transformation.

References

SHOWING 1-10 OF 54 REFERENCES

A review of wind power and wind speed forecasting methods with different time horizons

In recent years, environmental considerations have prompted the use of wind power as a renewable energy resource. However, the biggest challenge in integrating wind power into the electric grid is

A Literature Review of Wind Forecasting Methods

In this paper, an overview of new and current developments in wind forecasting is given where the focus lies upon principles and practical implementations. High penetration of wind power in the

An Advanced Statistical Method for Wind Power Forecasting

This paper presents an advanced statistical method for wind power forecasting based on artificial intelligence techniques. The method requires as input past power measurements and meteorological
...