A Geospatial Comparison of Distributed Solar Heat and Power in Europe and the US

The global trends for the rapid growth of distributed solar heat and power in the last decade will likely continue as the levelized cost of production for these technologies continues to decline. To be able to compare the economic potential of solar technologies one must first quantify the types and amount of solar resource that each technology can utilize; second, estimate the technological performance potential based on that resource; and third, compare the costs of each technology across regions. In this analysis, we have performed the first two steps in this process. We use physical and empirically validated models of a total of 8 representative solar system types: non-tracking photovoltaics, 2d-tracking photovoltaics, high concentration photovoltaics, flat-plate thermal, evacuated tube thermal, concentrating trough thermal, concentrating solar combined heat and power, and hybrid concentrating photovoltaic/thermal. These models are integrated into a simulation that uses typical meteorological year weather data to create a yearly time series of heat and electricity production for each system over 12,846 locations in Europe and 1,020 locations in the United States. Through this simulation, systems composed of various permutations of collector-types and technologies can be compared geospatially and temporally in terms of their typical production in each location. For example, we see that silicon solar cells show a significant advantage in yearly electricity production over thin-film cells in the colder climatic regions, but that advantage is lessened in regions that have high average irradiance. In general, the results lead to the conclusion that comparing solar technologies across technology classes simply on cost per peak watt, as is usually done, misses these often significant regional differences in annual performance. These results have implications for both solar power development and energy systems modeling of future pathways of the electricity system.

[1]  V. Quaschning.  Technical and economical system comparison of photovoltaic and concentrating solar thermal power systems depending on annual global irradiation , 2004 .

[2]  Soteris A. Kalogirou,et al.  Hybrid PV/T solar systems for domestic hot water and electricity production , 2006 .

[3]  William A. Beckman,et al.  Solar transmittance characteristics of evacuated tubular collectors with diffuse back reflectors , 1985 .

[4]  Todd Otanicar,et al.  Photovoltaic/thermal system performance utilizing thin film and nanoparticle dispersion based optical filters , 2013 .

[5]  Ha T. Nguyen,et al.  Quantifying Rooftop Solar Photovoltaic Potential for Regional Renewable Energy Policy , 2010, Comput. Environ. Urban Syst..

[6]  T. Chang.  The Sun’s apparent position and the optimal tilt angle of a solar collector in the northern hemisphere , 2009 .

[7]  W. Beckman,et al.  Evaluation of hourly tilted surface radiation models , 1990 .

[8]  Mark Z. Jacobson,et al.  Providing all global energy with wind, water, and solar power, Part I: Technologies, energy resources, quantities and areas of infrastructure, and materials , 2011 .

[9]  M. McLinden,et al.  NIST Standard Reference Database 23: Reference Fluid Thermodynamic and Transport Properties-REFPROP, Version 9.1 | NIST , 2013 .

[10]  J. Coventry.  Performance of a concentrating photovoltaic/thermal solar collector , 2005 .

[11]  Norman Chigier,et al.  Progress in Energy and Combustion Science , 1984 .

[12]  Spatially Varying Extinction Coefficient for Direct Absorption Solar Thermal Collector Optimization , 2011 .

[13]  Soteris A. Kalogirou,et al.  Solar thermal collectors and applications , 2004 .

[14]  H. Beyer,et al.  Mapping the performance of PV modules, effects of module type and data averaging , 2010 .

[15]  Todd Otanicar,et al.  Parametric analysis of a coupled photovoltaic/thermal concentrating solar collector for electricity generation , 2010 .

[16]  J. Remund,et al.  Solar Radiation and Uncertainty Information of Meteonorm 7 , 2011 .

[17]  S. Wilcox,et al.  Users Manual for TMY3 Data Sets (Revised) , 2008 .

[18]  Hans Müller-Steinhagen,et al.  Collector test method under quasi dynamic conditions according to the European Standard EN 12975-2 , 2004 .

[19]  A. D. Vos,et al.  Detailed balance limit of the efficiency of tandem solar cells , 1980 .

[20]  E. Dunlop,et al.  A power-rating model for crystalline silicon PV modules , 2011 .

[21]  Issa Batarseh,et al.  Improved solar PV cell Matlab simulation model and comparison , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[22]  Daniel M. Kammen,et al.  Life cycle analysis of distributed concentrating solar combined heat and power: economics, global warming potential and water , 2012 .

[23]  William E. Boyson,et al.  Photovoltaic array performance model. , 2004 .

[24]  Angelika Bayer,et al.  Solar Engineering Of Thermal Processes , 2016 .

[25]  E. Skoplaki,et al.  ON THE TEMPERATURE DEPENDENCE OF PHOTOVOLTAIC MODULE ELECTRICAL PERFORMANCE: A REVIEW OF EFFICIENCY/ POWER CORRELATIONS , 2009 .