Smart Grid Enabled Indoor Farming: A New Recipe for Energy Management Using Lighting Control

Indoor farming allows for year-round food production, however, its reliance on supplementary artificial lighting significantly strains the grid by increasing energy demand, peak load, and resultant energy costs. Recent research shows that plants can tolerate interruptions in light, thus enabling control mechanisms to strategically schedule lighting as a function of time varying energy prices. These schedules are known as lighting “recipes” with a duration of 24 hours, which can be aligned with day-ahead pricing to optimally schedule lighting intensity to achieve energy cost savings and improve load flexibility. This paper proposes an optimal lighting control strategy that generates a daily lighting recipe with the objectives of reducing daily energy costs and monthly peak demand charges. Plant health considerations, such as minimum light intake and adequate dark/lighting intervals, are formulated as mathematical constraints. A model predictive control approach is used to solve for the optimal lighting recipe. Comprehensive simulations for a one-hectare greenhouse using real-world electricity prices from the Ontario system operator reveal an annual energy cost reduction of ${\$}$ 281,000(22.6%) and a peak load reduction of 850 kW (18.4%). The results indicate the potential for indoor farming operations to become flexible resources within the smart grid paradigm.