Solar Resource Assessment for CSP Projects

Solar Resource Measurements
and Satellite Data
4th Sfera Summer School 2013
Hornberg Castle, Germany
Dr. Norbert Geuder
CSP Services – Almería – Cologne

4th Sfera Summer School, Hornberg Castle, 2013 - 2
1) Introduction
2) Fundamentals on Solar Irradiation
3) Variability of Irradiation
4) Irradiation Sensors
5) Sensor calibration and measurement accuracy enhancement
6) Satellite Based Assessment
7) Outlook / Summary
Outline

Selection of promising sites
Long-term time series
(>10 years)
Meteorological Station:
Accurate irradiation data
+
Irradiation map: spatial distribution Geographical data: land use, etc.
Plant design, inter-annual variability, uncertainty analysis, financing, …
GIS analysis
General Procedure at Solar Resource Assessment

Solar Resource Assessment for CSP Plants
• Direct Beam Irradiation data required for CSP Applications
• Usually not available in suitable sunny regions in the world
• Accessible via measurements or derived from satellite data
Restrictions:
– Measurements: expensive, long duration, not for the past
– Satellite data: high uncertainty (≈ 10 % or more)
• High accuracy required for DNI with long-term performance
not global irradiation – this is quite a difference!

Impact of Solar Resource Uncertainty
on CSP Plant rentability
Annual DNI
Annual
expenses
(redemption,
O&M, …)
Electricity
production
DNI
uncertainty
(e.g. ±10 %)
Earnings
expected long-term value (100%)
Losses
Irradiation uncertainty decides over project realization !
With thoroughly performed measurements an accuracy of approximately 2 % is achievable.

Fundamentals on Solar Irradiation

Solar Constant
Mean solar irradiance (flux density
in W/m²) at normal incidence
outside the atmosphere
at the mean sun-earth distance r.
1367 W/m²
Calculation:
Luminosity of the sun: L = 3.86 x 1026 W
Astronomical unit: r = 149.60×109 m
1320
1330
1340
1350
1360
1370
1380
1390
1400
1410
1420
0 90 180 270 360
IrradianceOutsideAtmosphere(W/m²)
Day of Year
Annual Variation of Solar Constant
22
1367
4 m
W
r
L



Source: DLR
Path of Solar Radiation through the atmosphere
Rayleigh scattering and absorption (ca. 15%)
Absorption (ca. 1%)
Scatter and Absorption ( ca. 15%, max. 100%)
Reflection, Scatter, Absorption (max. 100%)
Absorption (ca. 15%)
Ozone.……….…....
Aerosol…….………..…...……
Water Vapor…….……...………
Clouds………….………..
Air molecules..……
Direct normal irradiance at ground
Radiation at the top of atmosphere

Source: DLR
Radiative Transfer in the Atmosphere
0
200
400
600
800
1000
1200
1400
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
00:00
Hour of Day
DirectNormalIrradiation
(W/m²)
Extraterrestrial
O2 and CO2
Ozone
Rayleigh
Water Vapor
Aerosol
Clouds

Source: DLR
Air Mass
AM = 0 (outside of atmosphere)

Solar Spectrum and Atmospheric Influence
1 Planck curve T=5780 K at mean sun-
earth distance
2 extraterrestrial solar spectrum
3 absorption by 03
4 scattering by 02 und N2
5 scattering by aerosols
6 absorption by H2O vapor
7 absorption by aerosols
UV radiation: 0.01 - 0.39 µm, ~ 7 %
Visible Spectrum: 0.39 – 0.75 µm, ~ 46 %
Near infrared: 0.75 – 2.5 µm, ~ 47 %
www.volker-quaschning.de/articles/fundamentals1/index.php

Characteristics of solar irradiation data
• Component:
– DNI (Direct-Normal Irradiation)
– DHI (Diffus-Horizontal Irradiation)
– GHI (Global-Horizontal Irradiation)
• Source:
– ground measurements:
• precise thermal sensors (thermopiles)
• Rotating Shadowband Irradiometers (RSI)
– satellite data
• Properties of irradiation:
– spatial variability
– inter-annual variability
– long-term drifts

Direct, Diffuse and Global Irradiance
When measuring solar irradiance, the
following components are of particular
interest:
 Direct normal irradiance (DNI)
(also: beam irradiance)
 Diffuse horizontal irradiance (DHI)
(also: diffuse sky radiation)
 Global horizontal irradiance (GHI)
(also: total solar irradiance)
GHI = DHI + DNI * sin ()
Zenith angle θ,
solar elevation 


DNI = BHI / sin 

Example:
 = 50°
BHI = 600W/m²
 DNI = 848W/m²
DNI > BHI
Direct-Normal- Irradiation (DNI)
direct
Direct Normal Irradiation (DNI)
with: BHI = Beam Horizontal Irradiation

GHI = BHI + DIF
Example:
DIF = 150W/m²
BHI = 600W/m²
 GHI = 750W/m²
Global-Horizontal-Irradiation (GHI)
diffuse
direct
diffuse
Global Horizontal Irradiation (GHI)

Long-term variability of solar irradiance
GHI from Potsdam, Germany

Source: DLR
Long-term variability of solar irradiance
7 to 10 years of measurement to get long-term mean within 5%

Source: DLR
Inter-annual variability
Strong inter-annual and
regional variations
1999
2001
2000
2002
2003
deviation
to mean
kWh/m²a
Average of the direct normal
irradiance from 1999 to 2003

Irradiation sensors

Absolute Cavity Radiometer
Principle of Measurements:
- Possibility to measure absolute irradiance
values. All other irradiance measurement
devices need to be calibrated using an absolute
cavity radiometer
- Its principle of operation is based on the
substitution of radiative power by electrical
(heating) power
- Measurement in intervals with minimal length
of 45 s. Constant irradiation required for
measurement campain
- Tracking device required
- No continuous measurement (!)
ftp.pmodwrc.ch/pub/pmo6-cc/user_guide_11.pdf
Valid for calibration purposes

Thermal sensors Semiconductor sensor
Rotating Shadowband Irradiometer,
RSI
(photodiode)
Suitable equipment for irradiance measurements for
Concentrating Solar Power (CSP)
Pyranometer,
pyrheliometer
(thermopiles)

Thermopile Sensors
CMP21 Pyranometer (GHI, DHI shaded)
with ventilation unit CVF3
CHP1 Pyrheliometer (DNI)
Shading assembly with shading ball
Solys 2 sun tracker
Sun sensor

Thermopile Sensors – Pyrheliometer
Principle of Measurement:
- Pyrheliometer = radiometer suitable to
measure direct normal irradiance
- Highly transparent window 97 – 98 %
transmission of solar radiation
- Housing geomerty with 200 mm absorber tube
restricting acceptance angle to 5°
- Sensing element with black coating and
built-in termopile device
- Pt-100 temperature sensor for temperature
corrections
www.kippzonen.com/?product/18172/CHP+1.aspx

Pyrheliometer Specifications
Kipp&Zonen CHP 1 Specifications:
Spectral range: 200 to 4000 nm
Sensitivity: 7 to 14 µV/W/m² (mV/kW/m²)
Response time: < 5 s
Expected daily uncertainty: ± 1 %
Full opening view angle: 5° ± 0.2°
Required tracking accuracy: ± 0.5° from
ideal

Thermopile Sensors – Pyranometer
- Pyrheliometer = radiometer suitable to
measure short-wave (0.2 - 4 µm)
global or diffuse radiation
- Highly transparent glass dome 97 – 98 %
transmission of solar radiation
- Full view on 2π hemisphere
(horizontal levelling required)
- Sensing element with black coating and
built-in termopile
- Pt-100 temperature sensor for temperature
corrections

Thermopile Sensors – Pyranometer
Kipp&Zonen CMP21 Specifications:
Spectral range: 285 to 2800 nm
Sensitivity: 7 to 14 µV/W/m² (mV/kW/m²)
Response time: 5 s www.kippzonen.com/?product/1491/CMP+21.aspx

Rotating Shadowband Pyranometer (RSP)
Rotating shadowband
Licor silicon photodiode
Housing of mechanics

RSI – Principle of Measurement
Source: Solar Millennium AG
Simplified sensor signal during shadow band rotation:
once per minute, rotation lasts about 1.5 seconds

Licor Li-200 Pyranometer Sensor
Specifications:
Sensitivity:
Typically 90 µA per 1000 W/m²
Response time: 10 µs.
Spectral range: 0.4 – 1.1 µm
Calibration:
Calibrated against an Eppley Precision
Spectral Pyranometer under natural
daylight conditions.
Typical error under these conditions is
±3% up to ±5%.
www.licor.com/env/Products/Sensors/200/li200_description.jsp

Precise thermal sensors:
Pyrheliometer and Pyranometer on sun tracker
Advantages:
+ high accuracy (1 to 2%)
+ separate sensors for
GHI, DNI and DHI
(cross-check through redundancy)
Disadvantages:
- high acquisition costs
- high maintenance costs
- high susceptibility for soiling
- high power demand
(grid connection required)
-GHI -DNI
-DHI

Sensor with photo diode:
Rotating Shadowband Irradiometer, RSI
Advantages:
+ fair acquisition costs
+ low maintenance
+ low susceptibility for soiling
+ low power demand (PV-Panel)
Disadvantage:
- reduced accuracy due to systematic
deviations of the photodiode sensor
response:
primordial DNI: ≈ 6 to 10 %
(or even higher)

Measurement uncertainty
Precise instruments (HP) versus RSI
Error source: Pyrheliometer: RSI:
 Calibration < ±1.1% ±3% (... ±5%)
 Temperature < ±0.5% 0% ... ±5%
 Linearity < ±0.2% ±1%
 Stability < ±0.5%/a < ±2%/a
 Spectral dependence <±0.1% 0% ... ±8%
 Sensor soiling -0.7% per day -0.07% per day
systematic errors
can be corrected!!

Choice of Measurement Equipment
High Precision sensors (thermopiles) Rotating Shadowband Irradiometer:
RSI
?
Which equipment is suitable for measurements in Solar Resource Assessment?

Objectives for Irradiance Measurements
Solar Resource Assessment
• at remote site
• no qualified staff
• no electric grid
• often dusty and arid areas
Power Plant Monitoring
• always qualified staff on site
• electric power available

Pyrheliometer soiling in southern Spain
Plataforma Solar de Almería

Comparison of sensor soiling
University of Almería

Soiling characteristics of pyrheliometers and RSI‘s
RSI
sensor head
Pyrheliometer
Solar
Irradiation
direct
sunlight
glass plate
tube with
200 mm
length
absorber
diffusor disk
over
photodiode

Choice of the adequate equipment
For Solar Resource Assessment
• at remote sites and
• daily maintenance not feasible
an RSI is the premium choice for DNI measurements.
However:
• Proper calibration
• Corrections of systematic signal response
• regular maintenance inspections (2 to 4 weeks)
are indispensable for reliable measurements.

Sensor calibration
and measurement accuracy enhancement

Sensor Calibration – Fundamentals I
- The World Standard Group
(WSG) is an assembly of highly
precise absolute cavity
radiometers.
- The measured mean value
(World Radiometric Reference)
is the measurement standard
representing the SI unit of
irradiance with an estimated
accuracy of 0.3 %.
- All other short wave irradiation
measurement systems are
calibrated against this single
value.
www.pmodwrc.ch/pmod.php?topic=wrc
Precision measurement at the
WorldRadiation Center (WRC)

RSI sensor calibration by DLR on PSA
2-monthly calibration of each RSI against
high-precision instruments
at Plataforma Solar de Almería (PSA)
(recommended every 2 years)

RSI sensor calibration duration
Variations of the Calibration Constant with calibration duration
DNI

Variability of the Correction Factors (CF)
Variability of
correction factors
(CF):
radiation components
need to be corrected
with separate CFs.

Recalibration of RSIs
Drift of Calibration Factor within 2 to 4 years

Correction of raw RSI measurement values
Origin of systematic errors of RSI response
• Temperature dependence of semiconductor sensor
• Spectrally varying irradiation
– different for irradiation components (direct beam / diffuse)
– depending on Air Mass
• Angle of incidence
• Pre-calibration of the sensor head (from the manufacturer)

Spectral correction of diffuse irradiation
2
DHI
GHIDNI
Πspec


corrected
raw values
variation with
air mass + altitude

Dependence of response on solar elevationBHIref/ BHIRSI
solar elevation angle in degree
so called „cat-ear effect“
Correction applied only on direct beam portion of the global response

Dependence of response on solar elevationBHIref/ BHIRSI
solar elevation angle in degree
corrected

Reachable accuracy for DNI with RSIs
RMSD = 13 W/m²
Accuracy of RSI
measurements
as derived from a comparison
of the data from 23 RSIs
with precise thermopile
measurements
within the course
of a whole year
RSP
GHI DHI DNI reference
(CHP 1)
unit
raw cor raw cor raw cor
average MB -10.3 ± 4.0 0.3 ± 1.3 -17.3 ± 1.6 -0.4 ± 0.7 24.6 ± 10.5 1.0 ± 0.5 1.0 ± 3.9 W/m²
RMSD 14.2 7.6 18.9 4.5 33.3 13.0 5.3 W/m²
Annual sum up to -2.5 < ±1 up to -15 < ±3.5 up to +7 < ±1 up to 1.3 %
10 min time resolution

Transferability of the results?
The reachable accuracy of the measured beam irradiance data
for the client at his prospected sites depends on 2 crucial points:
• Stability of the sensor sensitivity
• Transferability of the results to other sites
• Regular inspections and data controlling

Transferability to other sites and climates
Parallel measurement campaigns
in UAE:
• Comparision of 6 RSIs to high-precision
thermal sensors
• Measurement periods >3 weeks
• in summer and winter

Relative deviation of DNI sum within measurement
campaign
only summer:
DNI < 730 W/m²
summer + winter:
DNI until 1000 W/m²

Satellite Based Assessment

Satellite Derived Data
Analyze satellite data in two steps:
1. Atmosphere: Gather satellite information of
atmospheric composition (ozone, water vapor
and aerosols) and apply the ‘clear sky model’ to
calculate the fractions of direct and diffuse
irradiance
2. Clouds: Calculate the cloud index as the
difference between actual reflectivity of the
earth as it is seen by the satellite and a
reference image which only includes
reflectance of the ground
www.solemi.de/method.html
0
200
400
600
800
1000
1200
1400
00:00
02:00
04:00
06:00
08:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00
00:00
Hour of Day
DirectNormalIrradiation
(W/m²)
Extraterrestrial
O2 and CO2
Ozone
Rayleigh
Water Vapor
Aerosol
Clouds

Scan
 The Meteosat satellite is
located in a
geostationary orbit
 The satellite scans the
earth line by line every
half hour
How to derive irradiance data from satellites
Source: DLR

How to derive irradiance data from satellites
Derivation of a
cloud index
from the two
channels Scan in infra-red spectrumScan in visible spectrum
Source: DLR

Different Cloud Transmission for GHI and DNI
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
-0.2 0 0.2 0.4 0.6 0.8 1 1.2
cloudtransmission
cloud index
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
-0.2 0 0.2 0.4 0.6 0.8 1 1.2
Sun-satellite angle 60-80
-26 °C
-16 °C
-6 °C
4 °C
14 °C
-30°C - -20°C
-20°C - -10°C
-10 °C - 0°C
0°C - 10 °C
>10°C
Different exponential
functions for varying
viewing angles and
brightness
temperatures
 Global Irradiation
 Direct Irradiation
Source: DLR

Clear sky Model input data
 Aerosol optical thickness
 GACP Resolution 4°x5°, monthly data
 MATCH Resolution 1.9°x1.9°, daily data
 Water Vapor:
NCAR/NCEP Reanalysis
Resolution 1.125°x1.125°, daily values
 Ozone:
TOMS sensor
Resolution 1.25°x1.25°, monthly values
Source: DLR

Uncertainty in Aerosols
All graphs are for
July
Scales are the same!
(0 – 1.5)
Large differences in
Aerosol values and
distribution
GADS
Toms
GOCART
NASA GISS v1 / GACP
NASA GISS v2 1990
AeroCom Linke Turbidity
Source: DLR

satellite pixel
( 3x4 km²)
ground
measurement
instrument
(2x2 cm²)
solar thermal
power plant
(200MW  2x2
km²
Comparing ground and satellite data:
“sensor size”
Source: DLR

0
200
400
600
800
1000
1200
0 6 12 18 24
hour of day
W/m²
ground
satellite
general difficulties:
• point versus area
• time integrated versus
area integrated
Source: DLR
accuracy

12:45 13:00 13:15 13:30 13:45 14:00 14:15
Hi-res satellite pixel in Europe
time scales
 Ground measurements are typically
pin point measurements which are
temporally integrated
 Satellite measurements are
instantaneous spatial averages
 Hourly values are calculated from
temporal and spatial averaging
(cloud movement)
Hourly average Meteosat image Measurement
Source: DLR

Source: DLR
Temporal resolution of input data: 1 hour
Spatial resolution of digital map: 1 km x 1 km per Pixel
Long term analysis: up to 20 years of data
data produced by (DLR, 2004) for MED-CSP
The original digital maps can
be navigated and zoomed with
Geographical Informations
Systems like ArcView or Idrisi.
Results of the satellite-based solar assessment
Digital maps: e.g. annual sum of direct normal irradiation
in 2002 in the Mediterranean Region

Source: DLR
Hourly monthly mean of DNI in Wh/m², Solar Village 2000
hour
Annual sums of DNI [kWh/m²] for one site in Spain
Monthly sums of DNI [kWh/m²] for one site in SpainHourly DNI [Wh/m²] for one site in Spain
Results of the satellite-based solar assessment
Time series: for single sites, e.g. hourly, monthly or annual

Satellite data and nearest neighbour
stations
Satellite derived
data fit better
to a selected
site than
ground
measurements
from a site
farther than
25 km away.
Source: DLR

Ground measurements vs. satellite derived data
Ground measurements
Advantages
+ high accuracy (depending on sensors)
+ high time resolution
Disadvantages
- high costs for installation and O&M
- soiling of the sensors
- possible sensor failures
- no possibility to gain data of the past
Satellite data
Advantages
+ spatial resolution
+ long-term data (more than 20 years)
+ effectively no failures
+ no soiling
+ no ground site necessary
+ low costs
Disadvantages
- lower time resolution
- low accuracy at high time resolution

Combining Ground and Satellite Assessments
• Satellite data
– Long-term average
– Year to year variability
– Regional assessment
• Ground data
– High Precision (if measurements taken thoroughly)
– High temporal resolution possible
(up to 1 min to model transient effects)
– Good distribution function
– Site specific

Procedure for Matching Ground and Satellite Data
Satellite
assessment
Ground
measurements
Comparison
Separation of clear sky
and cloud conditions
Recalculation
with alternative
atmospheric input
Selection
of best atmospheric input
Recalculation
with alternative cloud
transmission tables
Selection
of best cloud
transmission table
Transfer MSG to MFG
Recalculation of
long term time series
Best fit
satellite data
clearskycorrection
cloudcorrection

What you should care for in good
Solar Resource Assessment

Procedure to Follow for Proper Solar Resource
Assessment
• Find a good location: close to site, safe, suitable for collocation of Weather
Station
• Clarify the ground property conditions
• Check/define the budget for:
instrumentation, maintenance and measurement related services
• Select the appropriate measurement equipment and provider
(based on budget considerations, local conditions on site and maintenance
possibilities)
• Find local maintenance personnel
• Prepare the measurement site according to the supplier’s specifications
(foundations, fencing, etc.)
• Installation and commissioning of the measurement equipment
• Steady monitoring of the measurement data,
duration minimum 1 year

Procedure to Follow for Proper Solar Resource
Assessment
• Documenting the selection of instruments
• Choosing a renowned company or institution to conduct or assist the
measurement campaign
• Documenting sensor calibration with proper calibration certificates
• Meticolously documenting the instrument installation and alignment
• Performing and documenting regular sensor cleaning, maintenance and
verification of alignment
• Cautiously and continuously checking data for errors and outliers
• Flagging suspect data, and applying corrections if possible, during and after
the measurement campaign
• Stating and justifying the uncertainty estimate in a detailed report after the
measurement campaign.

 Delivery of hardware
 Installation & commissioning
 Operational supervision and
control
 Equipment monitoring
with inspection visits on site
Daily data retrieval via
modem (GSM/GPRS)
Data collection and processing:
• accuracy enhancement
(correction)
• quality and functionality check
• graphical visualization
Expert office
Daily, monthly,
annual report with
good quality data
to client (via e-mail)
On site
Client
Usual Expert Service for Solar Resource Assessment

Quality Control of Measurement Data
 Are values physically possible ?
Measurement values must met
physical limits
 Are they reasonable?
e.g. comparison to a clear sky
model (Bird) or in kd-kt-space
 Are they consistent?
Comparison of redundant
information
 Visual inspection by an expert

Summary
• Knowledge of accurate irradiation data is indispensable for CSP
projects
(→ proper plant design, financial calculation, efficient plant operation)
• site selection, pre‐feasibility with satellite data
• colocation of a measurement station, taking care on thorough operation
• match long‐term satellite data with good quality measurement data from ground
• monitor the operating plant efficiency thoroughly with high‐precision data

Thank you
very much
for your
attention!

Note – This presentation is not owned by RE-Docs. It has simply been shared for wider
dissemination because of its useful content. The author have been clearly acknowledged on
www.redocs.co In case of any issues you may contacts us at www.redocs.co/contact
Visit us on
www.redocs.co
your personal library on RE
Hope you found the presentation useful!
for similar useful material

Solar Resource Assessment for CSP Projects

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Viewers also liked

Viewers also liked (14)

Similar to Solar Resource Assessment for CSP Projects

Similar to Solar Resource Assessment for CSP Projects (20)

Recently uploaded

Recently uploaded (20)

Solar Resource Assessment for CSP Projects