Solar Energy Collectors and Applications
Solar energy collectors are special kind of heat exchangers that transform solar radiation energy to internal energy of the transport medium. The major component of any solar system is the solar collector. This is a device which absorbs the incoming solar radiation, converts it into heat, and transfers this heat to a fluid (usually air, water, or oil) flowing through the collector. The solar energy thus collected is carried from the circulating fluid either directly to the hot water or space conditioning equipment or to a thermal energy storage tank from which can be drawn for use at night and/or cloudy days.
There are basically two types of solar collectors: non-concentrating or stationary and concentrating. A non-concentrating collector has the same area for intercepting and for absorbing solar radiation whereas a sun-tracking concentrating solar collector usually has concave reflecting surfaces to intercept and focus the sun’s beam radiation to a smaller receiving area, thereby increasing the radiation flux. Solar energy collectors are also distinguished by their motion, i.e., stationary, single axis tracking and two-exes tracking, and the operating temperature.
The performance of a solar collector depends mainly on its optical and thermal efficiencies, determined according to various methods outlined in international standards. The collector optical efficiency depends on the properties of the materials (and their coating) used for the collector construction (absorptance, transmittance, emittance), and the incident angle modifier, which applies to both stationary and concentrating collector. For the latter, the collector acceptance angle, which determines the tracking mechanism allowable error, is also required. The collector thermal performance depends on the collector instantaneous thermal efficiency and the collector time constant, which depends on the thermal capacity of the collector.
The performance of a solar system can be evaluated with various design methods, like the f-chart and the utilizability method, whereas a detailed analysis of the systems can be obtained by using a number of programs, like TRNSYS, WATSUN, Polysun, F-Chart and many others. Lately artificial intelligence methods have been used for the design, simulation and prediction of long-term performance of solar collectors and systems. These include the use of artificial neural networks, genetic algorithms, expert systems, fuzzy systems and various hybrid systems which combine two or more the above technologies.
Solar collectors can be used in a large variety of applications. The main areas of applications include:
- Solar water heating, which includes thermosyphon, integrated collector storage systems, air systems, direct circulation and indirect water heating systems.
- Solar space heating systems, which includes both water and air systems.
- Solar refrigeration, which includes both adsorption and absorption systems.
- Industrial process heat systems, which include both low temperature (air and water based) applications and solar steam generation systems.
- Solar desalination systems, which include both direct (solar stills) and indirect systems (conventional desalination equipment powered by solar collectors).
- Solar thermal power generation systems, which include the parabolic trough systems, the power tower or central receiver systems and the parabolic dish systems (dish/Stirling engine).
Current research trend is focused on the development of new coating materials for solar collectors, which could increase absorptance and reduce emittance, thus increase the optical and thermal efficiency of the collector. This includes the use of innovative coatings and nanotechnology.
Further reading
- Kalogirou, S., Solar Thermal Collectors and Applications, Progress in Energy and Combustion Science, Vol. 30, No. 3, pp. 231-295, 2004. (Link »)
- Kalogirou, S., Seawater Desalination Using Renewable Energy Sources, Progress in Energy and Combustion Science, Vol. 31, No. 3, pp. 242- 281, 2005. (Link »)
- Kalogirou, S., Environmental Benefits of Domestic Solar Energy Systems, Energy Conversion and Management, Vol. 45, No. 18-19, pp. 3075-3092, 2004. (Link »)
- Kalogirou, S., Artificial Neural Networks in Renewable Energy Systems: A Review, Renewable & Sustainable Energy Reviews, Vol. 5, No. 4, pp. 373-401, 2001. (Link »)
- Kalogirou, S., Panteliou, S. and Dentsoras, A., Modelling of Solar Domestic Water Heating Systems Using Artificial Neural Networks, Solar Energy, Vol. 65, No. 6, pp. 335-342, 1999. (Link »)
- Kalogirou, S. and Panteliou, S., Thermosyphon Solar Domestic Water Heating Systems Long- Term Performance Prediction Using Artificial Neural Networks, Solar Energy, Vol. 69, No. 2, pp. 163-174, 2000. (Link »)
- Kalogirou, S., Prediction of Flat-Plate Collector Performance Parameters Using Artificial Neural Networks, Solar Energy, Vol. 80, No. 3, pp. 248-259, 2006. (Link »)
- Kalogirou, S., Optimisation of Solar Systems Using Artificial Neural Networks and Genetic Algorithms, Applied Energy, Vol. 77, No. 4, pp. 383-405, 2004. (Link »)
- Florides, G., Kalogirou, S., Tassou, S. and Wrobel, L.. Modelling and Simulation of an Absorption Solar Cooling System for Cyprus, Solar Energy, Vol. 72, No. 1, pp. 43-51, 2002. (Link »)
- Kalogirou, S., The Potential of Solar Industrial Process Heat Applications, Applied Energy, Vol. 76, No. 4, pp. 337-361, 2003. (Link »)
- Florides, G., Kalogirou, S., Tassou, S. and Wrobel, L., Modelling, Simulation and Warming Impact Assessment of a Domestic-Size Absorption Solar Cooling System, Applied Thermal Engineering, Vol. 22, No. 12, pp. 1313-1325, 2002. (Link »)
- Kalogirou, S.A., Lalot, S., Florides, G. and Desmet, B., Development of a Neural Network- Based Fault Diagnostic System for Solar Thermal Applications, Solar Energy, Vol. 82, No. 2, pp. 164-172, 2008. (Link »)


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