Food-energy-water nexus considerations in optimal greenhouse farming systems design and operation

Abstract

Greenhouse farming systems have the potential to sustainably relieve the stresses on food supply systems caused by a globally increasing population, together with the reduction of available agricultural land due to urbanization and soil degradation. However, literature regarding the sustainable design and operation optimization of greenhouse process systems remains scarce. This work focuses on the optimal planning and scheduling of a greenhouse farming system dependent on the utilized farming technologies, the available crops, and the selected geographic location. Ad extremum, the derived greenhouse optimization framework enables the generic trade-off analysis among completely isolated and transparent greenhouses, as well as energy and water saving greenhouses. Planning and scheduling decisions include the cover material transmissivity and isolation, cooling, heating, wetting and drying technologies, multi-crops farming strategies, irrigation, as well as artificial lighting and a dynamic shading system. To derive sustainable greenhouse system solutions, this work follows a food-energy-water nexus approach by analyzing not only an economic objective, but also resource-use objectives and a societal benefit objective, in the form of the nutritional value of the produced food basket, over one year of operation at an hourly timescale. Accordingly, this approach results in a multi-objective multi-scale mixed-integer linear programming optimization problem of large size. Various solution strategies to reduce the computational burden and solve this optimization problem to global optimality are discussed. The Pareto-front envelope for Doha, Qatar is characterized by a best-possible solution vector of $2.949M/year, 144 MW/year, 124 m${}^3$/year, and farming of carrot, lettuce, tomato, and spinach. In turn, the best trade-off solution for farming this nutrition optimal food basket consist of an annualized system cost of between $3.2M and $3.5M, energy-use between 186 and 189 MW, and water-use of 138 m${}^3$.