Upload
elvis-gilbert
View
36
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert CLIM-RUN GA, July 8-10 th 2013. IC3. CLIMRUN WP7: Renewable Energy Second Round Workshops. EEWRC. DHMZ. ENEA, PIK. Product 1: Mediterranean Seasonal Wind Forecast. Product 2: Europe Long-term Wind Speed Scenarios. - PowerPoint PPT Presentation
Citation preview
Climate Forecasting Unit
Melanie Davis, Francisco Doblas-Reyes, Fabian Lienert
CLIM-RUN GA, July 8-10th 2013
CLIMRUN WP7: Renewable Energy
Second Round WorkshopsIC3
EEWRC
DHMZ
ENEA, PIK
Climate Forecasting Unit
Problem: Climate variability risk in wind decisions
Operational decisions (Wind farm/grid operator, trader)
Planning decisions (Policy maker, energy planning, grid development)
Investment decisions
Energy generation – balancing resources, energy trading, extremes, insurance?Maintenance – offshore most vulnerable
Market strategies – incentives, energy mixSpatial planning – balancing resources, reinforce/redesign distribution network
Site selection – robust resource assessments, portfolio designRevenue – robust projections, volatility over time, insurance?
(debt financing, throughout project)
-30 years
PAST Observations P
RE
SE
NT
Weather Forecasts
Hours/days/weeks
ClimateForecasts
Months to seasons(1month-1year)
Seasonal Annual-Decadal
Inter/multi-annual (1-30years)
Multi-decadal(30+years)
HindcastsClimate Change
FUTUREPredictions
Climate Forecasting UnitSecond round workshops
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 25-28th 2013
Grid operators, Traders, Insurance, Investors, Project developers
20 + 8 All products,Seasonal wind forecasting presentation
Croatia: May-June?
Cyprus: tbc.
Climate Forecasting Unit
Wind Forecast Skill Assessment1St validation of the climate forecast system:
Spring 10m wind resource ensemble mean correlation(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
time
win
d sp
eed
forecast + 1.0
obs. forecast - 1.0
forecast example 1
forecast - 1.0
example 2
example 3
Perfect Forecast
Same as Climatology
Worse than
Clima-tology
Can the wind forecast mean tell us about the wind resource variability at a specific time?
Seasonal Wind ForecastsDemonstrating the value
Climate Forecasting Unit
Wind Forecast Skill Assessment2nd validation of the climate forecast system:
Spring 10m wind resource CR probability skill score(ECMWF S4, 1 month forecast lead time, once a year from 1981-2010)
time
win
d sp
eed
forecast + 1.0
obs. forecast - 1.0
forecast example 1
forecast - 1.0
example 2
example 3
Perfect Forecast
Same as Climatology
Worse than
Clima-tology
Can the wind forecast distribution tell us about the magnitude of the wind resource variability, and its uncertainty at a specific time?
Seasonal Wind ForecastsDemonstrating the value
Climate Forecasting Unit
Europe
Wind Forecast Skill Assessment
Areas of interest: E.Brasil
N.ChileIndonesia/W.India
W. Australia
S.America Africa Asia Australia
Mexico/S.Canada
N.America
N.Spain/S.E Europe
Spring 10m wind resource magnitude and its uncertainty forecast skill
Spring 10m wind resource variability forecast skill
Wind resource variability forecast skill only
Both wind resource magnitude and its uncertainty forecast skill
KenyaSomalia
Where is wind forecast skill highest?
Seasonal Wind Forecasts Demonstrating the value
Climate Forecasting Unit
Probabilistic forecast of (future) spring 2011,10m wind resource most likely tercile(ECMWF S4, 1 month forecast lead time)
%
Seasonal Wind Forecasts Demonstrating the potential
Areas of Interest Identified:(Resources and Forecast Skill)
Operational Wind Forecasts
Europe
E.BrasilN.Chile
Indonesia/W.India
W. Australia
S.America
Africa Asia
Australia
Mexico/S.Canada
N.America
N.Spain/S.E Europe
KenyaSomalia
Climate Forecasting Unit
1. 10m wind not representative of wind turbine hub height.
Caveats and further research:Climate forecasting for wind energy
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.
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.
Caveats
Further research
4. Explore the potential of decadal wind forecasts for wind energy sector.
Climate Forecasting Unit
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.
Conclusions:Climate information for wind energy
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.
Climate Forecasting Unit
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
Advancing Renewable Energy with Climate Services (ARECS)
Next Steps
Zagreb, HEP - OIE, d.o.o 17
Number of hours working on nominal power for wind power plants in Croatia (2011)
Croatia Workshop
Climate Forecasting Unit
Hydro in Croatian power system
19
- 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
Croatia Workshop
Climate Forecasting Unit
Precipitation change2030-2040
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
Bars denote number of RCMs!
Precipitation change 2030-2040
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
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)
Croatia Workshop