Wind Power Generation Variations and Aggregations

Cong Wu; Xiao-Ping Zhang; Michael Sterling

doi:10.17775/CSEEJPES.2021.03070

CSEE Journal of Power and Energy Systems 2022, 8(1): 17-38 https://doi.org/10.17775/CSEEJPES.2021.03070

Open Access | Issue | Published: 13 November 2021

Wind Power Generation Variations and Aggregations

Show Author's Information Hide Author's Information Cong Wu, Xiao-Ping Zhang(

), Michael Sterling

Department of Energy Strategy and Planning, State Grid Energy Research Institute, Beijing, China

Department of Electronic, Electrical and Systems Engineering, School of Engineering, University of Birmingham, Birmingham B15 2TT, U.K

Keywords:

Energy quality, meteorological re-analysis data, wind power aggregation, wind power ramping rate, wind power variation, wind power variability

Cite this article:

Wu C, Zhang X-P, Sterling M. Wind Power Generation Variations and Aggregations. CSEE Journal of Power and Energy Systems, 2022, 8(1): 17-38. https://doi.org/10.17775/CSEEJPES.2021.03070

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Abstract

Climate and weather-propelled wind power is characterized by significant spatial and temporal variability. It has been substantiated that the variability of wind power, in addition to contributing hugely to the instability of power grids, can also send the balancing costs of electricity markets soaring. Existing studies on the same establish that curtailment of such variability can be achieved through the geographic aggregation of various widespread production sites; however, there exists a dearth of comprehensive evaluation concerning different levels/scales of such aggregation, especially from a global perspective. This paper primarily offers a fundamental understanding of the relationship between the wind power variations and aggregations from a systematic viewpoint based on extensive wind power data, thereby enabling the benefits of these aggregations to be quantified from a state scale ranging up to a global scale. Firstly, a meticulous analysis of the wind power variations is undertaken at 6 different levels by converting the 7-year hourly meteorological re-analysis data with a high spatial resolution of 0.25 $^{\circ}$ $\times$ 0.25 $^{\circ}$ (approximate 28 km $\times$ 28 km) into a wind power series globally. Subsequently, the proposed assessment framework employs a coefficient of variation of wind power as well as a standard deviation of wind power ramping rate to quantify the variations of wind power and wind power ramping rate to exhibit the characteristics and benefits yielded by the wind power aggregation at 6 different levels. A system planning example is adopted to illustrate the correlation between the coefficient of variation reduction of wind power and investment reduction, thereby emphasizing the benefits pertaining to significant investment reduction via aggregation. Furthermore, a wind power duration curve is used to exemplify the availability of wind power aggregated at different levels. Finally, the results provide insights into devising a universal approach towards the deployment of wind power, principally along the lines of Net-Zero.

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About this article

Wind Power Generation Variations and Aggregations

Show Author's information Hide Author's Information Cong Wu, Xiao-Ping Zhang(

), Michael Sterling

Department of Energy Strategy and Planning, State Grid Energy Research Institute, Beijing, China

Department of Electronic, Electrical and Systems Engineering, School of Engineering, University of Birmingham, Birmingham B15 2TT, U.K

Abstract

Keywords: Energy quality, meteorological re-analysis data, wind power aggregation, wind power ramping rate, wind power variation, wind power variability

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Acknowledgements

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Publication history

Received: 20 April 2021

Revised: 24 September 2021

Accepted: 31 October 2021

Published: 13 November 2021

Issue date: January 2022

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Acknowledgements

This work was supported partly by the Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/N032888/1 and Grant EP/L017725/1, and by GEIDCO under Grant 1474100.