FRAUNHOFER INSTITUTE FOR SOLAR ENERGY SYSTEMS ISE Switching perspectives: From historical averages to forward- looking estimates of solar resources as a basis for lifetime energy yield predictions of PV power plants Björn Müller, Alfons Armbruster, Christian Schill Fraunhofer Institute for Solar Energy Systems ISE, Heidenhofstrasse 2, 79110 Freiburg, Germany, Phone +49 761/4588-5707, [email protected] OBJECTIVE & BACKGROUND Solar resource assessments for lifetime energy yield predictions [1] are usually based on Mean annual irradiance from the past Influence of dimming and brightening trends [2] are neglected Possible trends in the future [3] are not considered DATA & METHOD Our analysis uses the Surface Solar Radiation Data Set - Heliosat (SARAH) data set [5, 6]. The SARAH dataset is a climatological dataset that covers the years 1983 to 2013. It is based on Meteosat images and validated against ground measurements. The data is available as monthly daily and hourly averages with a spatial resolution of 0.05° x 0.05°. CONLUSIONS The SARAH dataset provides useful additional information for solar resource assessments Trends on tilted or tracked planes can be calculated from the dataset (hourly resolution, GHI and DNI available) More realistic measure for the development of PV yields in the past Fig 1: Trends for different components of irradiance (data source: ground measurements of the German weather service „Deutscher Wetterdienst“ in Potsdam) PRINCIPLE FINDINGS REFERENCES [1] Müller, B., Hardt, L., Armbruster, A., Kiefer, K., and Reise, C. (2016) Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties. Prog. Photovolt: Res. Appl., 24: 570–583. doi: 10.1002/pip.2616. [2] Müller B, Wild M, Driesse A, Behrens K. Rethinking solar resource assessments in the context of global dimming and brightening. Solar Energy 2014; 99: 272–82, DOI: 10.1016/j.solener.2013.11.013. [3] Wild M, Folini D, Henschel F, Fischer N, Müller B. Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems. Solar Energy 2015; 116: 12–24, DOI: 10.1016/j.solener.2015.03.039. [4] Wild M. Global dimming and brightening: A review. Journal of geophysical research 2009; 114(D10): D00D16, DOI: 10.1029/2008JD011470. [5] Müller R, Pfeifroth U, Träger-Chatterjee C, Cremer R, Trentmann J, Hollmann R. Surface Solar Radiation Data Set - Heliosat (SARAH): Edition 1; 2015., DOI: 10.5676/EUM_SAF_CM/SARAH/V001. [6] Müller R, Pfeifroth U, Träger-Chatterjee C, Trentmann J, Cremer R. Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation. Remote Sensing 2015; 7(6): 8067–101, DOI: 10.3390/rs70608067. Fig 2: Dimming & Brightening and an uncertain future (data source: measurements of the German weather service „Deutscher Wetterdienst“ in Potsdam) Looking at trends from ground measurements in past decades [2, 4]: Widespread decrease of surface solar radiation (“global dimming”) between the 1950s and 1980s Partial recovery at many locations (“brightening”) since the 1990s Observed in many regions of the world Looking at possible trends in the future [3]: Based on projections of global climate models future trends can be expected Climate models show a tendency to underestimate past decadal variations in surface solar radiation compared to ground measurements GHI trends for the most recent 30 years: Mostly brightening period (temporal and spatial) Most of Europe and Africa show an increase in solar irradiance Calculated trends are in agreement with ground measurements Magnitude of trends is high especially in mountainous regions (Highest deviation in the Alps) Solar resource assessments based on more recent data (10 years): Compared to solar resource assessments using 30 years of data more than 5% higher estimates for some locations In accordance with ground measurements [1, 2] Impact on solar resource assessments: There is no “true” long-term average of solar irradiance in the past that can be used to predict future solar energy availability Solar resource assessments using more recent data (e.g. 10 years, see [2]) will usually estimate higher irradiance values More information on past and future trends for arbitrary locations is needed for a better understanding of uncertainties and risks related to solar resource assessments Fig 3: Trends for GHI over three decades Fig 4: Deviation of the most recent 10 years
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FRAUNHOFER INSTITUTE FOR SOLAR ENERGY SYSTEMS ISE
Switching perspectives: From historical averages to forward-looking estimates of solar resources as a basis for lifetime energy yield predictions of PV power plantsBjörn Müller, Alfons Armbruster, Christian SchillFraunhofer Institute for Solar Energy Systems ISE, Heidenhofstrasse 2, 79110 Freiburg, Germany, Phone +49 761/4588-5707, [email protected]
OBJECTIVE & BACKGROUND
Solar resource assessments for lifetime energy yield predictions [1] are usually based on
Mean annual irradiance from the past
Influence of dimming and brightening trends [2] are neglected
Possible trends in the future [3] are not considered
DATA & METHOD
Our analysis uses the Surface Solar Radiation Data Set - Heliosat (SARAH) data set [5, 6]. The SARAH dataset is a climatological dataset that covers the years 1983 to 2013. It is based on Meteosat images and validated against ground measurements. The data is available as monthly daily and hourly averages with a spatial resolution of 0.05° x 0.05°.
CONLUSIONS
The SARAH dataset provides useful additional information for solar resource assessments
Trends on tilted or tracked planes can be calculated from the dataset (hourly resolution, GHI and DNI available)
More realistic measure for the development of PV yields in the past
Fig 1: Trends for different components of irradiance (data source: ground measurements of the German weather service „Deutscher Wetterdienst“ in Potsdam)
PRINCIPLE FINDINGS
REFERENCES
[1] Müller, B., Hardt, L., Armbruster, A., Kiefer, K., and Reise, C. (2016) Yield predictions for photovoltaic power plants: empirical validation, recent advances and remaining uncertainties. Prog. Photovolt: Res. Appl., 24: 570–583. doi: 10.1002/pip.2616.
[2] Müller B, Wild M, Driesse A, Behrens K. Rethinking solar resource assessments in the context of global dimming and brightening. Solar Energy 2014; 99: 272–82, DOI: 10.1016/j.solener.2013.11.013.
[3] Wild M, Folini D, Henschel F, Fischer N, Müller B. Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems. Solar Energy 2015; 116: 12–24, DOI: 10.1016/j.solener.2015.03.039.
[4] Wild M. Global dimming and brightening: A review. Journal of geophysical research 2009; 114(D10): D00D16, DOI: 10.1029/2008JD011470.
[5] Müller R, Pfeifroth U, Träger-Chatterjee C, Cremer R, Trentmann J, Hollmann R. Surface Solar Radiation Data Set - Heliosat (SARAH): Edition 1; 2015., DOI: 10.5676/EUM_SAF_CM/SARAH/V001.
[6] Müller R, Pfeifroth U, Träger-Chatterjee C, Trentmann J, Cremer R. Digging the METEOSAT Treasure—3 Decades of Solar Surface Radiation. Remote Sensing 2015; 7(6): 8067–101, DOI: 10.3390/rs70608067.
Fig 2: Dimming & Brightening and an uncertain future (data source: measurements of the German weather service „Deutscher Wetterdienst“ in Potsdam)
Looking at trends from ground measurements in past decades [2, 4]:
Widespread decrease of surface solar radiation (“global dimming”) between the 1950s and 1980s
Partial recovery at many locations (“brightening”) since the 1990s
Observed in many regions of the world
Looking at possible trends in the future [3]:
Based on projections of global climate models future trends can be expected
Climate models show a tendency to underestimate past decadal variations in surface solar radiation compared to ground measurements
GHI trends for the most recent 30 years:
Mostly brightening period (temporal and spatial)
Most of Europe and Africa show an increase in solar irradiance
Calculated trends are in agreement with ground measurements
Magnitude of trends is high especially in mountainous regions (Highest deviation in the Alps)
Solar resource assessments based on more recent data (10 years):
Compared to solar resource assessments using 30 years of data more than 5% higher estimates for some locations
In accordance with ground measurements [1, 2]
Impact on solar resource assessments:
There is no “true” long-term average of solar irradiance in the past that can be used to predict future solar energy availability
Solar resource assessments using more recent data (e.g. 10 years, see [2]) will usually estimate higher irradiance values
More information on past and future trends for arbitrary locations is needed for a better understanding of uncertainties and risks related to solar resource assessments
Fig 3: Trends for GHI over three decades
Fig 4: Deviation of the most recent 10 years
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