Climate Forecasting Unit StateoftheArt Climate Forecasting for Wind

  • Slides: 19
Download presentation
Climate Forecasting Unit State-of-the-Art Climate Forecasting for Wind Energy Melanie Davis, Francisco Doblas-Reyes, Fabian

Climate Forecasting Unit State-of-the-Art Climate Forecasting for Wind Energy Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert CLIMRUN General Assembly, ENEA, Rome, July 2013

Presentation Outline: Climate Forecasting Unit Climate forecasting for wind energy Problem: How can climate

Presentation Outline: Climate Forecasting Unit Climate forecasting for wind energy Problem: How can climate variability be a risk in wind energy decisions? Solution: How can climate forecasting minimise this risk? Methodology: Climate forecasting of wind speed, a seasonal example. Caveats/Further research: What are the limitations and potential for wind energy forecasting? Conclusions: State-of-the-art climate forecasting for wind energy, current status.

Problem: Climate Forecasting Unit Climate variability risk in wind decisions Problem: How can climate

Problem: Climate Forecasting Unit Climate variability risk in wind decisions Problem: How can climate variability be a risk in wind energy decisions? 15 10 Observations 5 0 1980 1990 2000 2010 Time in yrs (lines represent 1 st May. /yr) JJA '13 Mean Wind Speed (m/s) Seasonal Variability in Wind Resource at Site X 2020 - Reduced uncertainty of future wind variability - Identify likelihood of extreme events High Low High Forecast Uncertainty High Low High Climatology Uncertainty

Problem: Climate variability risk in wind decisions Climate Forecasting Unit Weather Forecasts Hindcasts PAST

Problem: Climate variability risk in wind decisions Climate Forecasting Unit Weather Forecasts Hindcasts PAST Observations Hours/days/weeks Months to seasons (1 month-1 year) PRESENT -30 years Climate Forecasts Seasonal Annual-Decadal Inter/multiannual (1 -30 years) Climate Change Multidecadal (30+years) FUTURE Predictions Operational decisions (Wind farm/grid operator, trader) Energy generation – balancing resources, energy trading, extremes, insurance? Maintenance – offshore most vulnerable Investment decisions Planning decisions (Policy maker, energy planning, grid development) Market strategies – incentives, energy mix Spatial planning – balancing resources, reinforce/redesign distribution network Site selection – robust resource assessments, portfolio design Revenue – robust projections, volatility over time, insurance? (debt financing, throughout project)

Solution: Climate Forecasting Unit Climate forecasting of wind resources GUIDANCE/ RISK MANAGEMENT Planning decisions

Solution: Climate Forecasting Unit Climate forecasting of wind resources GUIDANCE/ RISK MANAGEMENT Planning decisions ACTION/ RISK MINIMISATION Operational decisions Investment decisions - Robust assessments - Contingency plans - Early-warning systems - Monitoring - Mobilise resources - Prepare measures - Instruction - Action

Methodology: Climate Forecasting Unit Climate forecasting of wind speed Stage A: Wind Resource Assessment

Methodology: Climate Forecasting Unit Climate forecasting of wind speed Stage A: Wind Resource Assessment Wind energy potential: Where does the highest wind occur? Wind energy volatility: Where does the wind vary the greatest? Stage B: Wind Forecast Skill Assessment Validation of the climate forecasts: How well can it reproduce the wind resources and its variability over past timescales Stage C: Operational Wind Forecasts Probabilistic forecast of future wind resource information

Methodology: Climate Forecasting Unit Stage Wind Forecasts Stages A: Wind Resource Assessment Wind energy

Methodology: Climate Forecasting Unit Stage Wind Forecasts Stages A: Wind Resource Assessment Wind energy potential: Where is it the windiest? Spring 10 m wind speed from 1981 -2011 (ERA-Interim) in m/s

Methodology: Climate Forecasting Unit Wind Forecasts Stage A: Wind Resource Assessment Wind energy volatility:

Methodology: Climate Forecasting Unit Wind Forecasts Stage A: Wind Resource Assessment Wind energy volatility: Where does the wind vary the greatest? Spring 10 m wind inter-annual variability from 1981 -2011 (ERA-Interim) in m/s

Methodology: Wind Forecasts Stages Climate Forecasting Unit Stage A: Wind Resource Assessment Where is

Methodology: Wind Forecasts Stages Climate Forecasting Unit Stage A: Wind Resource Assessment Where is wind resource potential and variability the highest? Spring 10 m wind resource availability Areas of interest: Europe UK/ Baltic Sea N. America N. Mexico/ N. Canada Spring 10 m wind inter-annual variability S. America Patagonia/ E. Brasil Africa Asia Central China/ Sahara, Mongolia/ Sahel N. Russia Australia W. Australia/ Tasmania

Methodology: Climate Forecasting Unit Wind Forecasts Stage B: Wind Forecast Skill Assessment 1 St

Methodology: Climate Forecasting Unit Wind Forecasts Stage B: Wind Forecast Skill Assessment 1 St validation of the climate forecast system: Can the wind forecast mean tell us about the future wind resource variability at a specific time? Spring 10 m wind resource ensemble mean correlation (ECMWF S 4, 1 month forecast lead time, once a year from 1981 -2010) Perfect Forecast Same as Climatology Worse than Climatology

Methodology: Climate Forecasting Unit Wind Forecasts Stage B: Wind Forecast Skill Assessment 2 nd

Methodology: Climate Forecasting Unit Wind Forecasts Stage B: Wind Forecast Skill Assessment 2 nd validation of the climate forecast system: Can the wind forecast distribution tell us about both the magnitude of the wind resource variability, and its uncertainty at a specific time? Spring 10 m wind speed continuous ranked probability skill score (ECMWF S 4, 1 month forecast lead time, once a year from 1981 -2010, no calibration) Perfect Forecast Same as Climatology Worse than Climatology

Methodology: Wind Forecasts Stages Climate Forecasting Unit Stage B: Wind Forecast Skill Assessment Where

Methodology: Wind Forecasts Stages Climate Forecasting Unit Stage B: Wind Forecast Skill Assessment Where is wind forecast skill highest? Spring 10 m wind resource variability forecast skill Wind resource variability forecast skill only Areas of interest: Europe N. Spain/ S. E Europe Spring 10 m wind resource magnitude and its uncertainty forecast skill Both wind resource magnitude and its uncertainty skill N. America Mexico/ S. Canada S. America E. Brasil N. Chile Africa Asia Australia Kenya Indonesia/ W. Somalia W. India Australia

Methodology Conclusion: Global Wind Forecasts in Spring Climate Forecasting Unit Climate m/s Wind resource

Methodology Conclusion: Global Wind Forecasts in Spring Climate Forecasting Unit Climate m/s Wind resource availability Areas of Interest: Europe UK/ (Resources) Baltic Sea Variability forecast skill Europe N. Spain/ (Forecast skill) S. E Europe Areas of Interest: N. America N. Mexico/ N. Canada Wind resource inter-annual variability S. America Patagonia/ E. Brazil E. Brasil N. America Mexico/ Mexico S. Canada m/s Africa Australia Asia W. Australia C. Sahara, China/ Mongolia/ W. Australia/ Sahel N. Russia Tasmania Magnitude + uncertainty forecast skill S. America E. Brazil E. Brasil N. Chile Africa Asia Kenya Indonesia/ Somalia W. India Australia W. W. Australia

Methodology: Climate Forecasting Unit Wind Forecasts Stage C: Operational Wind Forecasts Probabilistic forecast of

Methodology: Climate Forecasting Unit Wind Forecasts Stage C: Operational Wind Forecasts Probabilistic forecast of (future) spring 2011, 10 m wind resource most likely tercile (ECMWF S 4, 1 month forecast lead time) Areas of Interest Identified: (Resources and Forecast Skill) N. America Mexico S. America E. Brasil Australia W. W. Australia

Methodology: Climate Forecasting Unit Wind Forecasts Stage C: Operational Wind Forecasts Probabilistic forecast of

Methodology: Climate Forecasting Unit Wind Forecasts Stage C: Operational Wind Forecasts Probabilistic forecast of spring 2011, 10 m wind resource most likely tercile (ECMWF S 4, 1 month forecast lead time) Areas of Interest Identified: (Resources and Forecast Skill) N. America Mexico S. America E. Brasil Australia W. W. Australia

Caveats and further research: Climate Forecasting Unit Climate forecasting for wind energy Caveats 1.

Caveats and further research: Climate Forecasting Unit Climate forecasting for wind energy Caveats 1. 10 m wind not representative of wind turbine hub height. 2. Lack of relevant, observational wind data for robust validations of forecast skill: reanalysis data used instead. 3. Seasonal wind forecasts assessed with a single climate model with 15 ensemble members: a multi-model, calibrated approach is needed with more ensemble members. Further research 1. Multi-model approach needed for a more robust forecast skill assessment. 2. Seasonal wind forecasts to be made down to site-specific scales. 3. Collaborations undertaken to formulate seasonal wind power forecasts with simple wind energy models to issue theoretical power predictions. 4. Explore the potential of decadal wind forecasts for wind energy sector.

Conclusions: Climate Forecasting Unit Climate forecasting for wind energy 1. Wind forecasting over seasonal

Conclusions: Climate Forecasting Unit Climate forecasting for wind energy 1. Wind forecasting over seasonal to decadal timescales can help to minimise risk of future wind variability on operational, planning and investment decisions 2. Seasonal wind forecasting is an emerging climate service within the renewable energy sector, whilst decadal wind forecasts are yet to be explored. 3. Some global regions are more vulnerable to wind resource variability over seasonal timescales than others 4. Although wind forecast skill is limited in some regions, there are others that show good potential (more so for predicting the resource variability than magnitude) 5. Based on points 3, 4, regions where operational Spring wind forecasts demonstrate the greatest value from research to date includes: Mexico, E. Brasil, W. Australia. 6. Seasonal and decadal wind forecast research to date includes several caveats, and there is scope for significant improvement with further research and better observational datasets.

Climate Forecasting Unit Advancing Renewable Energy with Climate Services (ARECS) Join the initiative at:

Climate Forecasting Unit Advancing Renewable Energy with Climate Services (ARECS) Join the initiative at: www. arecs. org ✔ Seasonal and decadal, wind and solar forecast information ✔ Provide feedback, register your needs ✔ Receive a quarterly seasonal wind forecast newsletter

THANK YOU Climate Forecasting Unit melanie. davis@ic 3. cat The research leading to these

THANK YOU Climate Forecasting Unit melanie. davis@ic 3. cat The research leading to these results has received funding from the European Union Seventh Framework Programme (FP 7/2007 -2013) under the following projects: CLIM-RUN, www. climrun. eu (GA n° 265192) EUPORIAS, www. euporias. eu (GA n° 308291) SPECS, www. specs-fp 7. eu (GA n° 308378)