Abstract

System performance, crop yield and cost are the major criteria for design optimization of a greenhouse solar heating system. While experimental study and evaluation of each plausible design are cost-prohibitive, resorting to detailed computer simulations would enable the prediction of system performance at specified locations. This paper discusses the development of a design procedure for greenhouse space heating. A simulation model that describes the greenhouse thermal environment and thermal storage, is verified by short-term actual data. Monthly average meteorological data were then used as inputs to the computer program for predicting long-term system performance, as indicated by the fraction of annual heating load supplied by solar energy. Results from simulation runs suggested that monthly solar heating fraction may be correlated with a dimensionless variable that involved mean daily solar radiation on an outside horizontal surface, total capture factor of the greenhouse cover, and night-time heat load. Such correlation was presented as a preliminary guidline for designers. Crop yield and economic analyses have to be carried out before selecting an optimum design for a particular location.

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