2. Contents
1. Utility scale solar energy technologies
2. Physical variables under consideration
3. The need for accurate datasets
4. The effect of climate change direction
5. Our dream for Copernicus (from a solar energy perspective)
3. 1. Utility scale solar energy technologies
Source: REN21 Renewables 2015 Global Status Report
Total World
Installed Power
Capacity ~5TW
Global Solar Capacity, 2004 - 2014
4. 1. Utility scale solar energy technologies
US: New Electric Generating Capacity Additions (2012-2014)
Increasingly, solar is
contributing most in
new power
additions
5. 1. Utility Scale Solar Energy
Technologies
Time of Day
Generation
PV generation follows the
solar resource profile
PV
GenerationGeneration
Time of Day
Time of Day
Solid power deliveryCSP
Production shift capabilityCSP
6. 1. Utility Scale Solar Energy
Technologies• Photovoltaic Systems (PV):
• Operate based on the photovoltaic effect (creation
of voltage in a semiconductor material when
exposed to electromagnetic radiation)
• Utilize the Global component of the solar
radiation.
• Intermittent Operation (i.e. generate only during
sunlight). Storage can be integrated with the use
of batteries (currently at high cost).
• Concentrated Solar Thermal Systems (CSP):
• Utilize concentrated solar radiation to generate
heat at high temperatures to run a thermal power
cycle.
• Utilize the Direct component of the solar
radiation.
• Can integrate thermal energy storage systems
(significantly lower cost than PV+bat)
7. 2. Physical Variables Under
Consideration• Key variables for PV:
• Annual total solar resource (daily or seasonal
variation are not important).
• Temperature (higher temperatures reduce
output).
• Low level dependency on wind speed,
atmospheric attenuation (compared to CSP).
• Concentrated Solar Thermal Systems (CSP):
• Annual total solar resource and short-term
patterns as cloud transients have larger effect
compared to PV.
• Wind, due to mirror stability and convective heat
losses.
• Atmospheric attenuation losses due to
transmission of solar flux over long distances.
8. 3. The need for accurate datasets
The Shams 1 CSP experience
•Satellite data were used to assess solar radiation but
the method didn’t pick up dust particles. The real DNI
was significantly lower than the estimations.
•Dust reduces insolation by about 30% so the
resulting DNI in the site (Abu-Dhabi) was lower than
Spain.
•Further, wind potential was significantly
underestimated
RISK 3: Inaccurate estimation of dust leading to a
requirement for a larger solar field installation.
RISK 4: Higher winds requiring the erection of a
large wind breaker wall around the power plant.
The Ivanpah Experience
•The 3 units of Ivanpah generated less electricity than
expected during the first year.
•Part of the cause was the cloud cover at Ivanpah in
2015 which has been more than expected resulting in a
reduction in solar radiation by nearly 10%.
RISK 1: Relying on only few years of measurements
may not accurately predict long term lows or highs in
meteorological conditions.
RISK 2: Multi year solar radiation “droughts” may not
be forecasted and may result in lower profitability for
years.
Accurate datasets on the general climatic conditions are
essential for the safe operation of solar power plants.
9. 4. The effect of climate change direction
Projects in North Africa & MENA Projects in North America
Projects in South America Projects in South Africa
Most of Solar Energy Projects (especially CSP) are deployed in deserts close to populated centres and the
sites could be considered as boundaries between different climates. So, an extended and rapid climate
change (boundary move) could turn the microclimate of the site from desert to temperate and vice versa in a
term of decade, having significant effect on the DNI values.
The prediction for Climate Change Direction is vital for the development of solar energy projects
Projects in Asia
10. 5. Our dream for Big Data (from a
solar energy perspective)
•Meteorological stations are usually located in population centres.
•Very few meteorological stations populate the desert areas of the Earth (Sahara, Kalahari, Saudi Arabia, Tibet).
Further, very few of the meteorological stations record detailed solar data (global, diffuse, direct)
•Action ->> Copernicus to support the increase of the density of specialised meteorological stations at the
desert areas and especially on the boundaries of the deserts in order to accurately record climate shifts.
A. Increase accuracy of satellite based estimation with ground
measurements at locations where no or sparse ground data exists.
Locations of meteorological Stations
11. 5. Our dream for Big Data (from a solar
energy perspective)
•Accurate cloud tracking is important to CSP as it may or may not lead to a cloud transient event, which
impacts production and may lead to solar field defocusing action, reduced output or even power station shut-
down.
•CSP operators are relying on all-sky cameras to trace clouds.
B. Provide real-time cloud tracking on specific locations
Current State of the Art: In order to increase
accuracy of cloud transient prediction, a CSP
operator has to install a lattice of all-sky cameras
at a distance around the CSP plant.
By merging the
pictures of all the
cameras it is
possible to make a
model of the cloud
formation and
their trajectory.
Action ->> Copernicus could provide
real-time detailed images of the
vicinity of the power plant allowing
the power plant operator to track with
exquisite detail cloud movements and
exact time of future cloud transient
events with 1hour notice.
Good resolution images are required,
circa 10m-25m per pixel
A series of all sky-cameras surrounding the solar power plant
12. Nur Energie Ltd.
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