Operational-based annual energy production uncertainty: are its components actually uncorrelated?

Nicola Bodini,Mike Optis

doi:10.5194/wes-5-1435-2020

Abstract

Abstract. Calculations of annual energy production (AEP) from a wind power plant – whether based on preconstruction or operational data – are critical for wind plant financial transactions. The uncertainty in the AEP calculation is especially important in quantifying risk and is a key factor in determining financing terms. A popular industry practice is to assume that different uncertainty components within an AEP calculation are uncorrelated and can therefore be combined as the sum of their squares. We assess the practical validity of this assumption for operational-based uncertainty by performing operational AEP estimates for more than 470 wind plants in the United States, mostly in simple terrain. We apply a Monte Carlo approach to quantify uncertainty in five categories: revenue meter data, wind speed data, regression relationship between density-corrected wind speed (from reanalysis data) and measured wind power, length of long-term-correction data set, and future interannual variability. We identify correlations between categories by comparing the results across all 470 wind plants. We observe a positive correlation between interannual variability and the linearized long-term correction; a negative correlation between wind resource interannual variability and linear regression; and a positive correlation between reference wind speed uncertainty and linear regression. Then, we contrast total operational AEP uncertainty values calculated by omitting and considering correlations between the uncertainty components. We quantify that ignoring these correlations leads to an underestimation of total AEP uncertainty of, on average, 0.1 % and as large as 0.5 % for specific sites. Although these are not large increases, these would still impact wind plant financing rates; further, we expect these values to increase for wind plants in complex terrain. Based on these results, we conclude that correlations between the identified uncertainty components should be considered when computing the total AEP uncertainty.

Highlights

Calculations of wind plant annual energy production (AEP) – whether based on preconstruction data before a wind power plant is built or on operational data after a wind plant has started its operations – are vital for wind plant financial transactions
While in the analysis we focus on operational AEP calculations, we expect that the results from this analysis – namely, the potential identification of correlated uncertainty components – can be relevant for informing and improving preconstruction AEP methods
The number of years used for the long-term windiness correction does not have a large impact on the overall uncertainty in operational AEP, at least for the sampled range of 10–20 years

Summary

Introduction

Calculations of wind plant annual energy production (AEP) – whether based on preconstruction data before a wind power plant is built or on operational data after a wind plant has started its operations – are vital for wind plant financial transactions. Preconstruction estimates of AEP are needed to secure and set the terms for new project financing, whereas operational estimates of long-term AEP are required for important wind plant transactions, such as refinancing, purchasing/selling, and mergers/acquisitions. The need for AEP analyses of wind plants is increasing because global wind capacity increased to 539 GW in 2017, representing 11 % and 91 % increases over 1- and 5-year periods, respectively; ca-. Optis: Correlation of uncertainties for wind plant operational AEP pacity is expected to increase by another 56 %, to 841 GW, by 2022 (Global Wind Energy Council, 2018). In the United States, wind plants generated more than 300 000 GWh in 2019, about 7.5 % of the total US electricity generation from utility-scale facilities that year, with a 50 % increase over a 6-year period (Energy Information Administration, 2020)

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Conclusion