Transcript 8. Renewable Energy - Clim

Climate Forecasting Unit
CLIMRUN WP7: Renewable Energy
IC3
Second Round Workshops
EEWRC
DHMZ
ENEA, PIK
Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert
CLIM-RUN GA, July 8-10th 2013
Product 1: Mediterranean
Climate Forecasting Unit
Seasonal Wind Forecast
Product 2: Europe
Climate Forecasting Unit
Long-term Wind Speed Scenarios
Product 3: Rabat
Climate Forecasting Unit
Long-term Wind Speed Scenarios
Problem:
Climate variability risk in wind decisions
Climate Forecasting Unit
Weather
Forecasts
Hindcasts
PAST
Observations
Hours/days/weeks Months to
seasons
(1month-1year)
PRESENT
-30 years
Climate
Forecasts
Seasonal
Annual-Decadal
Inter/multiannual
(1-30years)
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)
Second round workshops
Climate Forecasting Unit
Workshop
Date
Stakeholder Type
Feedback
(audience
number + direct
feedback)
Focus
Morocco: Maghreb
Wind Energy
Congress, Rabat,
Morocco
21-22
May
2013
Investors,
Wind companies,
International Organisations,
N. Africa Government
30 + 10
All products,
All applications
covered in
presentation
Spain: Weather
Forecasting for the
Energy Markets,
Berlin, Germany
13-14th
June
2013
Energy Traders, Insurance
companies
20 + 5
All products,
Seasonal wind
forecasting
presentation
Spain: International
Conference for
Energy and
Meteorology,
Toulouse, France
June
2528th 2013
Grid operators, Traders,
Insurance, Investors,
Project developers
20 + 8
All products,
Seasonal wind
forecasting
presentation
Croatia:
May-June?
Cyprus:
tbc.
Seasonal Wind Forecasts
Climate Forecasting Unit
Demonstrating the value
obs.
1St validation of the climate forecast system:
Can the wind forecast mean tell us about the
wind resource variability at a specific time?
wind speed
Wind Forecast Skill Assessment
Spring 10m wind resource ensemble mean correlation
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
forecast
+ 1.0
forecast
- 1.0
forecast
example 1
example 2
example 3
time
Perfect
Forecast
Same as
Climatology
Worse
than
Climatology
Seasonal Wind Forecasts
Climate Forecasting Unit
Demonstrating the value
obs.
2nd validation of the climate forecast system:
Can the wind forecast distribution tell us about
the magnitude of the wind resource variability,
and its uncertainty at a specific time?
wind speed
Wind Forecast Skill Assessment
Spring 10m wind resource CR probability skill score
(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
forecast
+ 1.0
forecast
- 1.0
forecast
example 1
example 2
example 3
time
Perfect
Forecast
Same as
Climatology
Worse
than
Climatology
Seasonal Wind Forecasts
Demonstrating the value
Climate Forecasting Unit
Wind Forecast Skill Assessment
Where is wind forecast skill highest?
Spring 10m wind resource variability
forecast skill
Wind resource variability
forecast skill only
Europe
Areas of
interest:
N.Spain/
S.E Europe
Spring 10m wind resource magnitude and its
uncertainty forecast skill
Both wind resource magnitude and its uncertainty
forecast skill
N.America
Mexico/
S.Canada
S.America
E.Brasil
N.Chile
Africa
Asia
Australia
Kenya
Indonesia/ W.
Somalia W.India
Australia
Seasonal Wind Forecasts
Climate Forecasting Unit
Demonstrating the potential
Operational Wind Forecasts
Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile
(ECMWF S4, 1 month forecast lead time)
Areas of Interest Identified:
(Resources and Forecast Skill)
Europe
%
N.America
N.Spain/
S.E Europe
Mexico/
S.Canada
S.America
Australia
E.Brasil
N.Chile
W.
Australia
Africa
Asia
Kenya
Somalia
Indonesia/
W.India
Caveats and further research:
Climate Forecasting Unit
Climate forecasting for wind energy
Caveats
1. 10m 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 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. Run seasonal wind forecasts with wind energy models to get power outputs.
4. Explore the potential of decadal wind forecasts for wind energy sector.
Conclusions:
Climate Forecasting Unit
Climate information for wind energy
1. Climate related wind information can help to minimise risk of future wind variability
on operational, planning and investment decisions: BUT every application is different.
2. The value of such information needs to be demonstrated in the decision making
process i.e. forecast quality → forecast value.
3. Past climate assessment is advanced in the energy sector, but climate forecasting is not.
Reason: Forecast skill is a concern for all, especially for predicting forecast magnitude.
4. Key regions where operational climatic wind information demonstrate the greatest value
could be explored further to evaluate forecast value in DMP.
5. Users want to see the best possible forecasts to benchmark its potential and limitations.
6. An index of operational forecast skill (in practice) over space and time is requested by
many users.
Next Steps
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
Next Steps
Climate Forecasting Unit
Advancing Renewable Energy with Climate Services (ARECS)
Next Steps
Climate Forecasting Unit
Advancing Renewable Energy with Climate Services (ARECS)
Croatia Workshop
Climate Forecasting Unit
Energy Roadmap to 2050
Croatia Workshop
Number of hours working on nominal power for
wind power plants in Croatia (2011)
Zagreb, HEP - OIE, d.o.o
17
Croatia Workshop
Climate Forecasting Unit
Climate change 2011-2040,
A2 scenario
Wind at 10m, summer
Croatia Workshop
Climate Forecasting Unit
Hydro in Croatian power system
- Half of electricity production in Croatia from 2000 – 2007 came
from hydro power plants
- 50% of installed Croatian power capacities are in hydro
- Heat wave in 2003: electricity production in hydro`s down 25%,
similar appeared in 2007
19
Croatia Workshop
Climate Forecasting Unit
Precipitation change
2030-2040
Results from 18 simulations by
13 regional climate models (RCMs)
which participated in the ENSEMBLES
project
Crosses indicate that 66% of the RCMs
agree in the sign of change.
Croatia Workshop
Climate Forecasting Unit
Precipitation change
2030-2040
Bars denote number of RCMs!
Croatia Workshop
Climate Forecasting Unit
From estimation to modeling
To propose the methodology how to model climate
change impact on RES
CLIMRUN
22
Croatia Workshop
Climate Forecasting Unit
Current work
Croatia Workshop
Climate Forecasting Unit
Conclusions
By the midcentury in Croatia expected climate change impact on renewables is:
- neutral impact on solar energy,
- positive impact on wind generation,
- negative impact on generation from hydropower (especially in the summer)
Currently, stakeholders poorly use climate information (not only decadal
projections and seasonal predictions, but also weather forecasts!)
Obstacle for stakeholders: poor understanding of probabilistic approach of
forecasts (instated of span of possibilities, they would like to have deterministic
approach)
During the workshop, there was a clear progress achieved in both way
communication and understanding between two circles (meteorologists and
energy experts)