Estimating icing in Finnish climate conditions

Transcription

1 VTT TECHNICAL RESEARCH CENTRE OF FINLAND LTD Estimating icing in Finnish climate conditions Ville Lehtomäki, Timo Karlsson, Simo Rissanen, VTT Teppo Hilakivi, Puhuri Oy Staffan Asplund, Etha Wind Wind Finland 2015 seminar 29 th October 2015, Helsinki

2 Content Presentation 1) by VTT: Comparing different turbine SCADA to Finnish Icing Atlases Definitions & Introduction to icing Three different Icing Atlases for Finland Case Puhuri Results Conclusions Presentation 2) by Etha Wind: ON ICING: Techno-Commercial Aspects

3 Definitions 3

4 Meteorological and instrumental icing IEA Wind Task 19 international expert group, goal: Gather and provide information about wind energy in cold climates Download free Best practices for wind energy in cold climates Resource assessment and site classification Task 19 website

5 Ice classes: IEA Ice Classification¹ IEA ice class Duration of Meteorological icing [% of year] Duration of Instrumental icing [% of year] Production loss [% of AEP] 5 >10 >20 > < ¹: IEA Wind Recommended Practices for wind energy projects in cold climates edition 2011, Task

6 Introduction

7 Wind farm development process & lifetime costs Site prospecting & site assessment the most critical decision gate in project development for AEP & risk assessment Topic Today Decision gate Prospecting Planning & Resource assessment Turbine purchase Constructions O&M Decomission X1 x6 x50 x20 x20?

8 Icing effects for wind power in Finland Manual de-icing

9 Icing effects for wind power in Finland AEP losses in Finland are expensive for developer because of FIT = 83.5 /MWh starting 2016-> 3MW turbine, -5 % AEP due to icing = 35 k /turbine/year lost Future issues? Ice throw risks need to be assessed Ice hit not an option Results from Sweden: iced turbine noise

10 Icing atlases for Finland 10

11 Three icing atlases for Finland Ø Used for site prospecting & initial risk assessment Method Approach Validation Advantage FMI Icing atlas Kjeller Icing atlas VTT WiceAtlas v1.0 - Numerical weather modelling with AROME - Icing hours for vertical Ø3cm, 1m tall cylinder (ISO 12494) - threshold 10g/m/h - 5yr average conditions - Publically available Only one 15 h icing event - Long-term experience of weather modelling in FI - Numerical weather modelling with WRF - Icing hours for vertical Ø3cm, 1m tall cylinder (ISO 12494) - threshold 10g/m/h - Detail simulation 7/2008-7/2009, 20yrs correction - Publically available Multiple validation points in Sweden & Norway - Internationally known & world-class expertize in icing modelling - Cloud and temperature measurements - Point measurements from met stations N=44 - Icing hours when T<0 C and low level clouds present - No threshold - 20yr mean conditions - Interpolate between points -> color map - Non-public available Multiple validation points in Sweden, Canada - No simulations, only measurements

12 Three icing atlases for Finland Icing hours [% of year] FMI Icing atlas 100m agl FI Ave: 1.1 % Kjeller Icing atlas 140m agl FI Ave: 1.6 % VTT WiceAtlas v m agl FI Ave: 6.7 % 12

13 Case Puhuri 13

14 Case Puhuri - overview Puhuri Oy is a utility owned developer with portfolio of 4 wind farms in Finland Several projects in pipeline Case wind farm: Turbines A & B (3MW, HH140m, D120m) A & B close to each other

15 Case Puhuri datasets used for analysis SCADA from two turbines: A & B Instrumental Icing (heated/unheated anemometers) on top of turbine A nacelle Meteorological Icing (Labkotec LID) on top of turbine A nacelle 3 x icing atlases: FMI, Kjeller, VTT WiceAtlas

16 Methods used Use IEA Wind Task 19 open source software, download T19IceLossMethod here Input Standard SCADA data Ws, temp, pwr, nacdir, mode Software Calc non-iced, ref power Calc icing events Calc AEP losses due to icing Output Icing timeseries AEP losses Turbine A heated/unheated anemometry as ice detector: if unheated < 20 % of heated, then Instrumental Icing Turbine A meteorological ice detector (Labkotec LID): if warning, then Meteorological Icing

17 Site prospecting analysis: 2, 5 or 10 % losses? FMI met ice Kjeller met ice % of year Wice met ice FMI inst ice FMI AEP loss IEA ice class Duration of Meteorological icing [% of year] Duration of Instrumental icing [% of year] Production loss [% of AEP] Turbine A Turbine B Turbine A Ave Production losses due to icing [% of AEP] (3+12) /2 = >20 Turbine B >20 Ice meas needed? Yes Yes/No Yes Yes Met icing ave p-loss = 9.3 % AEP Inst icing ave p-loss = > 20 % AEP AEP loss (FMI) = 5.8 % AEP 5 >10 >20 > < Best estimate: ( )/2 = 7.6 % of AEP Decision: perform icing measurements at site!

18 Results 18

19 Power curve, turbine A

20 Power curve, turbine B

21 Measurement results regarding icing % of year Sublimation! 9-12/ /2015 A losses B losses Rotor ice Met ice Inst Ice Good correlation to measured icing (met & inst) to AEP losses More icing with warmer winter temperatures?

22 Monthly R^2 correlations Meteorological icing: Wice vs Labko has best correlation Instrumental icing: FMI 5-yr average values Labko Wice FMI Inst meas Labko Wice FMI Inst FMI Inst meas Inst FMI

23 Monthly meteorological icing 0,3 May May 2015 R^2=0.79 0,3 % of time 0,2 0,2 0,1 0,1 0,0 met ice Wice met ice Wice overpredicts but correlation good -> calibration needed

24 Monthly instrumental icing % of time 0,7 0,6 0,5 0,4 0,3 0,2 0,1 0,0 May May 2015 R^2=0.50 FMI large values all winter inst ice FMI inst ice

25 Long-term icing from WiceAtlas timeseries mean Last two winters on same level as long-term average

26 IEA Ice Classification of site Icing atlases Source Kjeller 2 Wice 4 FMI (meteorological) 3 FMI (instrumental) 4 FMI (losses) 3 AVE= 3 Ice class Icing atlases results > measurements Each atlas has pros/cons Instrumental icing atlas an answer? Source Case Met icing (Labko) & Rotor icing Instrumental icing 2-3 A losses B losses 2 AVE= 2 Ice class Prospecting estimate Mean meas losses % (atlases) % Ice Class 3 Ice Class

27 Conclusions (1/2) Large scatter of results for one site from 2015: Different meteorological icing atlases 2-8 % of year Turbine A Icing 6 % of year Instrumental icing 7-19 % AEP losses due to icing 1-9 % Are long-term effects same? Site prospecting study: Met icing atlases + IEA ice class Good idea to use more than one icing atlas Kjeller ice class close to case study results FMI and VTT need tuning? Long-term WiceAtlas analysis shows similar icing also in future

28 Conclusions (2/2) Different turbines react diffently to same icing conditions Turbine A = -5.6 % mean AEP losses due to icing Turbine B = -1.3 % mean AEP losses due to icing Prospected losses (-7.6 % AEP) were higher than measured ( % AEP) when using atlases with IEA ice classes Next: Etha Wind continues

29 TECHNOLOGY FOR BUSINESS Ville Lehtomäki

30 Extra slides

31 Low temperature & Icing map of world 150m IEA Ice class AEP loss [%] >

32 Cold climate markets Cumula&ve installed capacity by end of 2012 [MW] Forecasted capacity [MW] Low temperature Light icing: safety risk, some economic risk Moderate to heavy icing: economic and safety risk Low temperature Light icing: safety risk, some economic risk Moderate to heavy icing: economic and safety risk 18,945 41,079 11,478 20,025 22,083 8,003 Total 69,000 (*) Total 45,000 50,000 (*) The total capacity is less than the sum of individual capacities because some of the sites have both low temperatures and icing conditions. 30GW of new installagons to icing condigons by 2017 Ø Compare: new offshore 29GW by 2017! source: BTM World market Update

33 Measurement results A lot of short icing events Ave temps rising Global warming?

34 Icing event example Turbine A stops for one week, turbine B only lightly affected