Influence of materials and management on greenhouse energy demand: the role of decision support systems

Energy consumption for heating greenhouses plays a key role on the profitability of protected productions. Therefore, much effort should be focused to increase the heating efficiency in floriculture as it is strongly related to quality and timeliness aspects. Besides, considering the global energy crisis and the environmental impasse, the improvement of energy efficiency and management ability wil1 require reducing cost and energy consumption. A prediction of the energy requirement of greenhouses configurations is therefore needed. For these reasons, the CRA-ING Research Laboratory and the University of Milan analyzed some representative greenhouses in Lombardy Region (Italy) under the point ofview ofthe energy consumption. A decision support system (DSS) is applied to reproduce and simulate observed greenhouses in order to analyze their energy consumption and to predict possible improvements. Aim of this study is to observe structural and management factors in greenhouses relating their influence on energy consumption. The DSS used is VirtualGrower 2.0, a free software developed by the Application Technology Research Unit USDA (United States Department of Agriculture) in Toledo, Ohio, USA. Four different greenhouses are used for energy analysis: three plastic covered tunnels (one of these covered by double layers) and one traditional glass and aluminium greenhouse. A series ofsimulations is carried out in order to evaIuate a number of possible improvement actions to contain thermal energy costs, with different and gradual upgrades. The applied heating scheme provides a constant temperature of 15° e with a heating period of 152 days, from November I to March 31. The variables analysed as improvements are: i) the cover materials (glass or plastic single or duallayer), ii) the energy curtain materials (typically in aluminium and polyethylene) and iii) the heating system (forced air, hot water pipes, heated floors). Also the possibility to change the fuel was evaluated considering minerai fuels vs. renewable ones. From the simulated results generated by VirtualGrower, the yearly cost for heating the greenhouses and the peak of energy required by the system are obtained. In addition, the observation of the unit cost per square meter has allowed the identification of optimized conditions. The data analysis may be used to improve the construction and performance of new greenhouses or to a better management of existing ones. Il may be aIso used to implement a methodology suitable for decision-making systems.