Abstract

The demand for minute-scale forecasts of wind power is continuously increasing with the growing penetration of renewable energy into the power grid, as grid operators need to ensure grid stability in the presence of variable power generation. For this reason, IEA Wind Tasks 32 and 36 together organized a workshop on “Very Short-Term Forecasting of Wind Power” in 2018 to discuss different approaches for the implementation of minute-scale forecasts into the power industry. IEA Wind is an international platform for the research community and industry. Task 32 tries to identify and mitigate barriers to the use of lidars in wind energy applications, while IEA Wind Task 36 focuses on improving the value of wind energy forecasts to the wind energy industry. The workshop identified three applications that need minute-scale forecasts: (1) wind turbine and wind farm control, (2) power grid balancing, (3) energy trading and ancillary services. The forecasting horizons for these applications range from around 1 s for turbine control to 60 min for energy market and grid control applications. The methods that can be applied to generate minute-scale forecasts rely on upstream data from remote sensing devices such as scanning lidars or radars, or are based on point measurements from met masts, turbines or profiling remote sensing devices. Upstream data needs to be propagated with advection models and point measurements can either be used in statistical time series models or assimilated into physical models. All methods have advantages but also shortcomings. The workshop’s main conclusions were that there is a need for further investigations into the minute-scale forecasting methods for different use cases, and a cross-disciplinary exchange of different method experts should be established. Additionally, more efforts should be directed towards enhancing quality and reliability of the input measurement data.

Highlights

  • In the past years, minute-scale forecasting of wind power has become an important research topic in the wind energy community

  • The maximum range that radars can measure is given by the wavelength of the signal emitted, but in this paper we only focus on radars which work on wavelengths that are of interest for minute-scale forecasting of wind power

  • Minute-scale forecasting of wind power is a discipline that is becoming crucial to accomplish in globally transitioning power systems with increasing amounts of variable generating power sources from renewables

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Summary

Introduction

Minute-scale forecasting of wind power has become an important research topic in the wind energy community. Whereas traditional forecasting techniques provide a forecasting horizon in the hour or day range [1], new methods allow us to predict the power output of wind turbines or wind farms on a minute scale. The objective of this paper is to provide a summary of the needs of minute-scale forecasting and an overview of the developed methods and the possible solutions to the barriers that prevent end users from adopting them. 39 participants from academia, forecasting service providers, wind farm operators as well as the lidar and wind turbine manufacturers discussed the future needs of minute-scale forecasting, the advantages and barriers of different forecasting techniques and strategies for overcoming those barriers. This paper is organized as follows: Sections 2 and 3 discuss the need for minute-scale forecasting and explain target forecasting horizons for different applications.

Intra-Hour Variability of Wind Power Generation
Wind Turbine and Wind Farm Control
Energy and Ancillary Services Markets
State-of-the-Art of Wind Power Forecasting
Review of Methods for Minute-Scale Forecasting
Minute-Scale Forecasting Based on Preview Data From Remote Sensing Devices
Scanning Lidar-Based Propagation Models
Radar-Based Density Models
Weather Radars for Prediction of Strong Wind Power Fluctuations
Statistical Time Series Models
Statistical Data Assimilation Based on Physical Models
Extreme Event Forecasting Models
Overview of Methods for Minute-Scale Forecasting
Limitations
Conclusions
Methods
A New Research Approach for Observing and Characterizing
Findings
Objective
Full Text
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