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Delegates are invited to meet and discuss with the poster presenters during the poster presentation sessions between 10:30-11:30 and 16:00-17:00 on Thursday, 19 November 2015.

Lead Session Chair:
Stephan Barth, ForWind - Center for Wind Energy Research, Germany
Luis Nuche Vaisala, United States
Co-authors:
Mark Stoelinga (1) F
(1) Vaisala, Seattle, United States

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Poster

Poster Download poster (10.29 MB)

Abstract

Validation of Preconstruction Energy and Uncertainty Assessments

Introduction

The wind energy assessment industry continually strives to align its predictions of wind farm energy production with “ground truth”, so that developers and financiers can confidently rely on those predictions. To this end, several major consultants have conducted validation studies comparing pre-construction assessments with actual energy production. These studies have contributed in a positive way to identifying chronic overprediction, understanding its causes, and recalibrating the industry’s end-to-end assessment methods, but more work remains to be done. An important follow-up task is the validation and calibration of estimates of uncertainty in those pre-construction energy assessments. In demonstrate our capabilities and to expedite the answer to questions on accuracy, Vaisala has completed a significant validation study aimed to:
1. Demonstrate that Vaisala can accurately predict P50’s of expected production
2. Demonstrate that a modern uncertainty approach can characterize risk


Approach

During the past year, Vaisala, Inc., has been conducting a validation study on a large set of operating North American wind farms. Like previous studies, we compare wind farm production values to the pre-construction P50 estimates. We also extend those previous studies in two ways: first, we validate a method that relies heavily on mesoscale modeling to estimate both temporal and spatial variability; and second, we compare our pre-construction uncertainty estimates to the spread of performance error, to test how well the uncertainty estimates are calibrated.



Main body of abstract

The study was in this first phase, targeted at 25 sites and 125 wind farm years. This is chosen based on review of accepted, peer consultant studies. Vaisala has solicited participation for a number of large utility-scale owner operators. In order to perform this study, participants provided Vaisala with pre-construction data sets and post-construction operational data. The study compares Vaisala’s pre-construction energy estimate to actual output, and also compares Vaisala’s uncertainty calculations to the observed error.



Conclusion

The purpose of the study isn’t just to demonstrate accuracy, but is the beginning loop in Vaisala’s ongoing effort to maintain calibration with actual generation.
Vaisala’s approach will be to make needed adjustments frequently and incrementally, avoiding large shocks to estimates of energy production at assessed sites that are noticeable and detrimental to our clients.



Learning objectives
Upon completion, participant will become familiar with how a wind energy assessment validation study is performed using operational wind farm data.
• Upon completion, participant will learn how well a mesoscale model-based wind energy assessment approach validates against production data for a large number of wind farms.
• Upon completion, participant will learn how accurately an uncertainty model, coupled with a wind energy assessment method, can estimate the true uncertainty in wind farm performance.