Energy is one of the biggest concerns of today's society, because of the rapid depletion of the world's fossil fuel reserves. Efficient energy technologies and renewable energy sources must therefore be developed and implemented. With a 5% share of the total energy consumption, agriculture can benefit from such developments. To preheat cold and fresh ventilation air for livestock barns, solar collectors are one of the promising renewable energy sources to reduce fossil fuel used in heating. Besides identifying energy saving strategies, the objective of the present project was to evaluate the performance of a specific type of solar air pre-heaters consisting of unprotected black corrugated metal sheeting with 1% perforation, installed over the barn fresh air inlets facing south. In this experiment, the two identically built commercial broilers barns were located in St-Jean-Baptiste, 40 km east of Montreal, Canada at 45.5 ° latitude. Each barn offered three floors with a capacity of 6500 broilers/floor, and 73.65 m2 of solar air preheaters for a total of 221 m2/barn. From November 2007 to March 2009 the project monitored inlet, inside and outside air conditions, ventilation rate and solar energy recovery and, from this data, conducted energy balance analyses. Measured efficiencies in recovering solar radiation varied from 65% to 20% depending on wind velocity and produced an annual return on investment of 4.7%. Air temperature stratification inside each room was responsible for the loss of 25 and 15% in heater energy and recovered solar energy, respectively. Although reducing heating load, the solar air pre-heaters had no impact on livestock performance because of limited effect on ventilation rate. The monitoring of ambient air temperature and relative humidity was complicated by air temperature stratification. Furthermore, the proper monitoring of ventilation rates requires the installation of electromagnetic sensors on all exhaust fans. The pyranometers used in this experiment were able to measure solar radiation with a maximum error of 7%.
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