A Model for the Sustainable Achievement of the Optimum Return for Crops in Greenhouses

This study provides a tool for accurate estimation of the irrigation water needs for various crop combinations under different environmental conditions; and employs a genetic optimization algorithm to reach optimum combinations. In the interest of sustainability, the source of energy required to drive the pumps is selected to be a renewable source, namely solar energy, which is converted to electricity employing photovoltaic (PV) modules. Having a single crop will lead to an uneconomical system because the PV installed capacity will not be exploited most of the time. This research was conducted by establishing the required database, generating different scenarios, assessing the economic performance along its life, forming the optimization model using genetic algorithm (GA), and implementing the model using Microsoft-Excel. The database includes data on greenhouse crops’ irrigational requirements, crop prices and cultivation costs, as well as data on PV water pumping (PVWP) system. The application of the model is demonstrated for the case of optimizing the selection of a combination of crops in greenhouses from a pool of different crops, for the maximum equivalent annual return for two selected sites in Egypt. The water needed for irrigation was correlated to ambient temperature, soil type, water source, crop type and planting season which led to better determination for the required pumping energy. The output from the irrigation pumps depends on the matching of the characteristics of the PVWP system with the locally available instantaneous solar energy, and on meeting the dynamic characteristics required from the irrigation system. Two optimization criteria are presented: one for the minimum required PV capacity, and the other for the combination producing maximum return on investment. Moreover, using the developed tool, the PVWP system is compared to a conventional diesel driven pumping system taking into consideration the effect of the most sensitive economic and environmental parameters such as crops’ price, irrigation water requirements and groundwater depth. The results show that the PVWP system is more economical than the conventional diesel system, in addition to the environmental gains