The world�s growing demand for food can be met by agricultural technology. Use of artificial light to supplement natural sunlight in\ngreenhouse cultivation is one of the most common techniques to increase greenhouse production of food crops. However, artificial\nlight requires significant electrical energy,which increases the cost of greenhouse production and can reduce profit. This paper models\nthe increments to greenhouse productivity aswell as the increases in cost from supplemental electric lighting, in a situation where\nthe greenhouse is one of the elements of a smart grid, a system where the electric energy market is dynamic and prices vary over\ntime.We used our models to calculate the optimum values for supplemental light and the required electrical energy for HPS lamps\nin the greenhouse environment, using cherry tomato cultivation as a case study crop.We considered two optimization techniques:\niterative search (IS) and genetic algorithm (GA). The two approaches produced similar results, although the GA method was much\nfaster. Both approaches verify the advantages of using optimal supplemental light in terms of increasing production and hence profit.
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