Ejsing Jørgensen, Hans

Mortensen, Niels Gylling

Nielsen, Morten

Online Research Database In Technology

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Downloaded from orbit.dtu.dk on: Nov 08, 2017Comparison of Resource and Energy Yield Assessment Procedures 2011-2015What have we learned and what needs to be done?Mortensen, Niels Gylling; Nielsen, Morten; Ejsing Jørgensen, HansPublication date:2015Document VersionPeer reviewed versionLink back to DTU OrbitCitation (APA):Mortensen, N. G., Nielsen, M., & Ejsing Jørgensen, H. (2015). Comparison of Resource and Energy YieldAssessment Procedures 2011-2015: What have we learned and what needs to be done? European WindEnergy Association (EWEA). [Sound/Visual production (digital)]. EWEA Annual Conference and Exhibition 2015, Paris, France, 17/11/2015Comparison of Resource and Energy Yield Assessment Procedures 2011-2015 What have we learned and what needs to be done?  Niels G Mortensen, Morten Nielsen and Hans E Jørgensen  EWEA 2015 Paris, France DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” Comparison of Resource and Energy Yield Assessment Procedures EWEA CREYAP concept • Industry benchmarking • In-house training and R&D • Identification of R&D issues Issues for today • Review of the 4 CREYAP exercises – Methodologies – Magnitudes and uncertainties – Modelled vs observed yields • Mostly conclusions presented here – Keep in mind the limited data set – Prioritised list of actions – Reference list in handout CREYAP history • Onshore Part 1, Bruxelles 2011 – Scotland W, 14×2 MW (28 MW) • Onshore Part 2, Dublin 2013 – Scotland E, 22×1.3 MW (29 MW) • Offshore Part 1, Frankfurt 2013 – Gwynt y Môr, 160×3.6 (576 MW) • Offshore Part 2, Helsinki 2015 – Barrow, 30×3 MW (90 MW) Summary • 157 submissions from 27 countries – 97 for onshore – 60 for offshore EWEA 2015 2 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” The CREYAP wind farms EWEA 2015 3 Barrow Irish Sea 30 turbines 90 MW Gwynt y Môr Irish Sea 160 turbines 576 MW Hilly/complex Scotland W 14 turbines 28 MW Hilly/complex Scotland E 22 turbines 29 MW • Estimated wind turbine yields (local color scales from Pmin to Pmax) DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” Methodology and limitations • Open exercises, no team requirements – Results may not reflect industry • Blind test with independent evaluation – Team identities unknown to evaluator – Peer review of evaluations • Results based on group statistics – Limited data in forms and groups – Statistics sensitive to outliers – Non-parametric and normal stat’s • Definitions – Bias ≡ difference between average of estimates and observations (mean) – Uncertainty ≡ standard deviation (spread) of distribution of estimates. EWEA 2015 4 • N teams make predictions for one wind farm • Input data are identical; methods different • Mean and spread compared for each step DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer”  1  Long-term extrapolation • LT extrapolation effects small and uncertain  0 to 1.8% on average (onshore)  −2.2 to 0.2% on average (offshore) • Methodologies used – Not well defined at all • Uncertainty  80 to 280% (CV) • Special issues  5-13% outliers • CREYAP results – Difficult analysis of ill-defined methods – Inconclusive results. EWEA 2015 5 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” 2  Vertical extrapolation EWEA 2015 6 • Vertical extrapolations not so challenging – Mast height/hub height = 0.83-1.07 – Profile effects less than 3% on U • Methodologies used (onshore) – Shearing-up by ½ of the teams – Flow modelling by ½ of the teams • Uncertainty (CV) – 10-22% on mean shear exponent – 0.7-3.6% on observed wind speed • Special issues – 7-11% outliers on exponent value • CREYAP results – Inconclusive, but a bit scary! – Challenging case study needed.  DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” 3  Horizontal extrapolation • Model results not significantly different, e.g. linearized and CFD-type flow models • Magnitude of effect (onshore only) – Extrapolation: +3.2 and −8.7% of yield – Topographical: 22 to 23% of yield • Methodologies used – Flow modelling only; many different – Model name and specification important • Uncertainty – Spread on extrapolation high: 59-132% • Special issues – Few (0-2%) outliers • Additional results – Model results ranges too narrow. EWEA 2015 7 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” 4  Wake modelling EWEA 2015 8 • Wake models disagree inside wind farms: uncertainty (CV)  WTG wake loss • Wakes represent a significant wind farm loss – Onshore: 6-10% – Offshore: 8-14% • Modelled with a separate wake model – Model name and specification important – Model configuration must be known too! • WF wake modelling uncertainty (CV) – Onshore: 13-18% – Offshore: 16-22% – Uncertainty  WF wake loss • Classic models seem to provide realistic results for Barrow Offshore Wind Farm DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” 5  Technical losses estimation • Technical losses large and uncertain  8-9.2% on average (onshore) • Methodologies used – Not well defined at all • Uncertainty – 32-34% coefficient of variation • Special issues – 2-3% outliers • Additional results – Calculation procedure sometimes wrong: losses added, not factored together.   EWEA 2015 9 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” 6  Uncertainty estimation and calculation Wind farm Estimated uncertainty CV σP50 Onshore W Hilly/complex 11% 34% 5% Onshore E Hilly/complex 08% 28% 6% Offshore Gwynt y Môr 10% 29% 7% Offshore Barrow 10% 23% 3% • Uncertainty estimates large and uncertain  8% to 11% on average • Methodologies used – Not well defined at all • Uncertainty  23% to 34% coefficient of variation • Special issues – About ¼ of the teams make errors when calculating P90 from P50 and uncertainty • Additional results – Spread of estimates < estimated spread. EWEA 2015 10 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” Predicted vs observed AEP • Only Barrow provided AEP comparison – Estimated = 104% of observed P50 – Spread  3% for net yield – Measured yield has an uncertainty too • Methodologies used – No simple relation between methodology and how well teams perform. • Uncertainty – Nice bell-shaped distribution – Uncertainty (CV)  3% • Special issues – No or fewer outliers in Barrow study • CREYAP results – Results seem to improve over time. EWEA 2015 11 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” What needs to be done? 1. Calculation, documentation and reporting – Robust, unambiguous framework 2. Long-term extrapolation methods – Well-defined and proven (NWA) 3. Uncertainty estimation and calculation – Framework, methodology and tools 4. Wake modelling (especially offshore) – Best practice based on validation data 5. Systematic technical losses estimation – Methodology and tools 6. Flow modelling – Vertical + horizontal extrapolation =  flow modelling – Best practice based on validation data        • Future CREYAP exercises 2016-2020 – Very steep or forested terrain – Tall turbines, challenging climatology, … – Wind conditions and site suitability • So, the final word (as always) is…  – High-quality wind farm data are in high demand for future studies and research! EWEA 2015 12 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” EWEA 2015 13 Thank you for your attention! Contributions by RES, Dong Energy, Iberdrola, Crown Estate, EWEA and all the teams are gratefully acknowledged! DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” CREYAP references Land-based wind farms • Mortensen, N. G., & Ejsing Jørgensen, H. (2011). Comparison of resource and energy yield assessment procedures. EWEA Wind Resource Assessment Technology Workshop, Brussels, Belgium, 10-11 May. • Mortensen, N. G., Ejsing Jørgensen, H., Anderson, M., & Hutton, K-A. (2012). Comparison of resource and energy yield assessment procedures. EWEA 2012, Copenhagen, Denmark, 16-19 April.  • Mortensen, N. G., & Ejsing Jørgensen, H. (2013). Comparative Resource and Energy Yield Assessment Procedures (CREYAP) Pt. II. EWEA Technology Workshop: Resource Assessment, Dublin, Ireland, 26 June. • Anderson, M., & Mortensen, N. G. (2013). Comparative Resource and Energy Yield Assessment Procedures (CREYAP) Pt. II. AWEA Wind Resource & Project Energy Assessment Seminar, Las Vegas, United States, 10-12 December. • Mortensen, N. G., Ejsing Jørgensen, H. & Nielsen, M. (2014). How well can the industry predict the wind resources? Overview of the results from EWEA CREYAP exercises. Danish Wind Industry Annual Event 2014, Herning, Denmark, 26-27 March. Offshore wind farms • Mortensen, N. G., Nielsen, M., & Ejsing Jørgensen, H. (2013). First Offshore Comparative Resource and Energy Yield Assessment Procedures (CREYAP). EWEA Offshore 2013, Frankfurt, Germany, 19-21 November. • Mortensen, N. G., & Nielsen, M. (2015). Offshore CREYAP Part 2 – preliminary results. EWEA Offshore Conference 2015, Copenhagen, Denmark, 10-12 March. • Mortensen, N. G., & Nielsen, M. (2015). Offshore CREYAP Part 2 – final results. EWEA Technology Workshop, Helsinki, Finland, 2-3 June. • Mortensen, N. G., Nielsen, M., & Ejsing Jørgensen, H. (2015). EWEA CREYAP benchmark exercises: summary for offshore wind farm cases. Wind Energy Denmark 2015, Herning, Denmark, 22-23 September.   Dissemination More than 1500 CREYAP publication downloads from DTU’s web site since 2011: more than ×10 the number of submissions. EWEA 2015 14 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” Score for the different steps – low is more important Scotland West Scotland East Onshore Gwynt y Môr Barrow OWF Offshore Long-term extrapolation 11 9 10 (1) 16 8 12 (3) Vertical extrapolation 18 20 19 (6) n/a 12 12 (4) Horizontal extrapolation 14 12 13 (3) 16 18 17 (6) Wake modelling 18 13 16 (5) 5 11 8 (2) Technical losses 12 14 13 (2) 12 19 16 (5) Uncertainty estimation 11 16 14 (4) 10 6 8 (1) EWEA 2015 15 DTU Wind Energy, Technical University of Denmark 18 November 2015 Add Presentation Title  in Footer via ”Insert”;  ”Header & Footer” What needs to be done? Land-based 1. Long-term extrapolation methods 2. Systematic technical losses estimation 3. Horizontal extrapolation 4. Uncertainty estimation and calculation 5. Wake modelling 6. Vertical extrapolation Offshore 1. Uncertainty estimation and calculation 2. Wake modelling 3. Long-term extrapolation methods 4. Systematic technical losses estimation 5. Vertical extrapolation 6. Horizontal extrapolation EWEA 2015 16 

Comparison of Resource and Energy Yield Assessment Procedures 2011-2015:What have we learned and what needs to be done?

From 2011 to 2015, the European Wind Energy Association arranged four open exercises to benchmark the wind resource and wind farm energy yield assessment procedures of the wind energy industry. Two case studies were for land-based Scottish wind farms in hilly to complex terrain, and two case studies for medium- to large-scale offshore wind farms in the Irish Sea. A total of 157 submissions were received, 97 land-based and 60 offshore, and all four exercises were analysed and presented previously by DTU Wind Energy.Results are summarised here for each of seven specific steps in the resource and energy yield assessment procedure: Site wind observation, long-term extrapolation, vertical extrapolation, horizontal extrapolation, wake modelling, technical losses estimation, uncertainty estimation and calculation.For each step and each wind farm a summary is given of the magnitude of the effects, the spread of the predictions, the methodologies used, and some general, qualitative conclusions. For one offshore wind farm, Barrow, the predicted yield was found to be 104% of the observed yield, with a spread of predictions of 3%.Based on the results of the four case studies and the statistics of the submitted data, two priori-tised lists of actions that could be taken in order to improve the overall process in the most cost-effective way are given; one for land-based and one for offshore wind farms

Comparison of Resource and Energy Yield Assessment Procedures 2011-2015: What have we learned and what needs to be done?

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Comparison of Resource and Energy Yield Assessment Procedures 2011-2015:What have we learned and what needs to be done?

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