A photochemistry-based method for optimising greenhouse supplemental light intensity

• Published in: Biosystems engineering Vol. 182; pp. 123 - 137
• Main Authors: Weaver, Geoffrey M., van Iersel, Marc W., Mohammadpour Velni, Javad
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2019
• Subjects: Adaptive lighting; algorithms; Chlorophyll fluorescence; Convex optimisation; electric energy consumption; electricity; electricity costs; greenhouse production; greenhouses; light intensity; Light-emitting diodes; lighting; photochemistry; photosynthesis; Chlorophyll fluorescence; Adaptive lighting; Light-emitting diodes; Convex optimisation
• ISSN: 1537-5110; 1537-5129
• DOI: 10.1016/j.biosystemseng.2019.03.008

Supplemental lighting in greenhouses can increase crop growth, improving rates of greenhouse production. The advent of light-emitting diodes (LEDs) for photosynthetic lighting presents new opportunities for optimising greenhouse supplemental lighting control. Because LED light intensity can be controlled rapidly and precisely in real time, these lights can be controlled such that supplemental light is provided when it will be most efficiently used to drive photosynthesis. This approach to supplemental lighting control has the potential to reduce the electricity cost associated with greenhouse lighting while retaining the beneficial effects on crop growth, thereby decreasing the financial cost and improving the sustainability of greenhouse crop production. In this paper, an optimisation problem is formulated to minimise the total amount of electricity used by supplemental LED lights, subject to achieving a specified daily amount of photochemistry. An algorithm to solve the problem explicitly based on sufficient conditions for a global minimiser is developed. This method represents a computationally simple and broadly applicable means for minimising the amount of electricity required for supplemental lighting in greenhouses. •Electricity use of greenhouse lights can be reduced using dimmable LEDs.•An optimization problem is formulated to minimize electricity use for lighting.•The problem is solved using a quick and computationally-simple algorithm.•Lettuce lighting requirements are simulated using typical meteorological year data.•Annual electricity costs can be reduced by an estimated 9.55% using this method.