Cold climate performance study of 89 wind farms,

Transcription

1 Cold climate performance study of 89 wind farms, CanWEA Operations and Maintenance Summit January 31, 2018 Ryan Kilpatrick, M.E.Sc., P.Eng.

2 Safety message You can never be too prepared! 2

3 Background / context Wind development continues to grow, and cold climate sites often have strong wind resource. Negative impacts of cold climate on individual wind turbines and wind farms are well documented. Issues include losses caused by blade ice build-up and cold temperature shutdown, Source: NRCan increased fatigue due to load imbalance etc. Cumulative effects, overall losses to industry, and annual and regional variations are not fully understood. Gaining better insight into big picture impacts will allow for better prediction of future losses, reduced risk and more effective deployment of investment and R&D efforts. 3

4 Cold climate analysis project Current study forms part of a multi-year NRCan project on cold climate operation, comprising: 89 wind farms (2,410 turbines) 4,450 MW installed capacity 10 provinces Jan Dec Monthly generation data obtained from Federal incentive programs: EcoEnergy for Renewable Power (EcoERP) and Wind Power Production Incentive (WPPI) Previous study of 23 wind farms (8 provinces, 1,770 MW) now available on NRCan web page: publications/sciences-technology/ renewable/wind/

5 Study composition Under WPPI and EcoERP, operators provide monthly generation data for first ten years of operation. Installed capacity of study group wind farms by year and by province Installed capacity (MW) 4,500 4,000 3,500 3,000 2,500 2,000 1,500 No new performance data after , BC AB SK MB ON QC NB NS PE NL 5

6 Study composition Installed capacity of study group wind farms compared to national 14,000 70% 12,000 60% Installed capacity of study group as a fraction of total begins to decline as 10-year period expires 10,000 50% Installed capacity (MW) 8,000 6,000 4,000 40% 30% 20% Study representation (%) Limited access to wind farms commissioned after ,000 10% National Study Percent study 0% 6

7 Approach Measure-Correlate-Predict (MCP) method used to predict wind farm generation based on local wind data and historical performance Wind farm specific turbine power curves Proximate weather station data Wind farm actual production Expected production at weather station Linear relationship Legend Input data Modeled output Wind farm forecast production 7

8 Approach Actual wind farm generation vs. expected generation at the weather station for a sample individual wind farm, for summer months only Linear relationship established, and used to create generation forecast Outliers greater than 2 standard deviations removed 8

9 Loss analysis Actual and forecast generation for a sample individual wind farm Start-up losses not included in analysis Losses calculated as difference between forecast and actual generation 9

10 Loss analysis Aggregated losses, New Brunswick Losses spike during winter months 10

11 Energy losses Cold climate loss (GWh) is defined as the difference between winter and summer losses, and represents the additional losses due to cold climate operation for a given year: Cold climate loss = Winter losses Summer losses To compare between years and regions, cold climate losses can be normalized by annual generation: Normalized cold climate loss = Cold climate loss (GWh) Annual generation (GWh) 11

12 Energy loss Cold climate loss (GWh), normalized by annual generation (GWh), by province and by year Cold climate loss (GWh) Annual generation (GWh) BC AB SK MB ON QC NB NS PE NL Average 12

13 Energy loss Annual energy loss due to cold climate, based on 2016 generation (GWh) Energy loss (GWh) BC AB SK MB ON QC NB NS PE NL Nation-wide energy loss due to cold climate (2016): 1,160 GWh (~3.7% of total generation) 13

14 Financial loss Estimated financial cost of cold climate losses, Error bars account for range of PPA rates Total, 2016 Financial loss due to cold climate (millions CAD) BC AB SK MB ON QC NB NS PE NL 0 Total estimated financial loss (nominal, 2016): $107 million Range: $81 - $121 million 14

15 Financial loss Estimated financial loss per turbine, 2016 $80,000 $70,000 $60,000 $50,000 Financial loss ($ / turbine / year) $40,000 $30,000 $20,000 $10,000 $0 BC AB SK MB ON QC NB NS PE NL 15

16 Conclusions Cold climate losses estimated to account for annual energy loss of 1,160 GWh and annual revenue loss to operators of $80M $120M. Highest cold climate losses on per GWh of generation basis observed in NB (0.12 GWh/GWh) and QC (0.06 GWh/GWh). Highest absolute financial losses observed in QC ($52M / year) and ON ($40M / year). 16

17 Limitations Recognized study limitations: Curtailment and other non-weather related losses not separated from other losses at this time. Lack of data including influence of latest cold-climate mitigation technologies. Lack of wind farm-specific weather event data to validate results. Age-related turbine degradation not taken into account. Lack of precision in EcoERP / WPPI data only available on monthly basis. While results presented are preliminary (minor changes to methodology may be implemented prior to publication), trends are unlikely to change significantly. 17

18 Discussion Where do we go from here? Retrofit options limited? Assessing effectiveness of new technologies Operational strategy + improved forecasting Risk analysis and project feasibility Accessing more granular data to improve insights 18

19 Future work and R&D Potential new research: More detailed loss analysis (depending on data availability) Site-specific and/or regional cold climate analysis / weather event correlation Development of high-resolution regional icing maps (Gaspé, NB etc.) Currently underway: Advanced icing forecasting (with TCE and UNB) 19

20 New research proposals CanmetENERGY currently seeking partners for collaborative research Initial concept development taking place 2018 Areas of potential interest: Grid integration Cold climate Remote community renewable energy Data visualization and mapping Other? 20

21 Thank you! Ryan Kilpatrick, M.E.Sc., P.Eng. Research Engineer, CanmetENERGY-Ottawa Natural Resources Canada / Government of Canada ryan.kilpatrick@canada.ca Ingénieur en recherche, CanmetÉNERGIE-Ottawa Resources naturelles Canada / Gouvernement du Canada ryan.kilpatrick@canada.ca 21

22 Appendix 22

23 Capacity factors of study group wind farms Capacity factors of wind farms in study group, by year and by province National average capacity factor of study group, 2016: 31.1% 23

24 Estimate of national wind generation Estimated generation from wind, by year and by province 12,000 10,000 Annual capacity factors from study group used to estimate national annual wind generation Estimated generation (GWh) 8,000 6,000 4,000 2,000 0 AB BC MB NB NL NS ON PE QC SK

25 Estimate of national wind generation Estimated generation from wind, nationally, by year 35,000 30,000 25,000 Estimated generation (GWh) 20,000 15,000 10,000 5,

26 Study composition Number of study group wind farms by year and by province Number of wind farms BC AB SK MB ON QC NB NS PE NL 26

27 Loss analysis Aggregated losses, Alberta 27

28 Loss analysis Aggregated losses, Ontario Losses trending upwards, likely due to dispatch 28

29 Loss factors Loss factors used to compare seasonal differences: Summer period: May October Winter period: November April Annual period: Summer + Winter Annual loss factor = Annual energy loss Annual energy forecast 100% Summer loss factor = Summer period energy loss Summer period forecast 100% Winter loss factor = Winter period energy loss Winter period forecast 100% 29

30 Loss factors Average loss factors , by province 20% 18% Highest spread between winter and summer loss factors in QC and NB 16% 14% Loss factor 12% 10% 8% 6% 4% 2% 0% BC AB SK MB ON QC NB NS PE NL Summer Winter Annual 30

31 0.14 Energy loss Average energy losses due to cold climate , normalized by annual generation Cold climate loss (GWh) Annual generation (GWh) BC AB SK MB ON QC NB NS PE NL 31

32 Estimation of lost revenue associated with cold climate losses: Latest available wind power purchase rates applied to energy losses for sample farms in each province. Publicly available Power Purchase Agreement (PPA) rates used where possible. For provinces with no public data, range of ± 30% applied to mean of other provinces. Assumes all additional energy can be sold to the grid. Financial loss Wind power purchase rates used in study, by province Purchase rate, estimated ($/kwh) High Nominal Low BC AB SK MB ON QC NB NS PE NL 32

33 Financial loss Financial losses attributable to cold climate, normalized by actual generation High Cold climate loss (thousands CAD / GWh generation) Nominal rate Low BC AB SK MB ON QC NB NS PE NL 33