A Supervisory Control Strategy for Improving Energy Efficiency of Artificial Lighting Systems in Greenhouses

Gianluca Serale, Luca Gnoli, Emanuele Giraudo and Enrico Fabrizio
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Gianluca Serale: Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy
Luca Gnoli: Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy
Emanuele Giraudo: Freelance Innovation Consultant, 12100 Cuneo, Italy
Enrico Fabrizio: Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy

Energies, 2021, vol. 14, issue 1, 1-19

Abstract: Artificial lighting systems are used in commercial greenhouses to ensure year-round yields. Current Light Emitting Diode (LED) technologies improved the system efficiency. Nevertheless, having artificial lighting systems extended for hectares with power densities over 50 W / m 2 causes energy and power demand of greenhouses to be really significant. The present paper introduces an innovative supervisory and predictive control strategy to optimize the energy performance of the artificial lights of greenhouses. The controller has been implemented in a multi-span plastic greenhouse located in North Italy. The proposed control strategy has been tested on a greenhouse of 1 hectare with a lighting system with a nominal power density of 50 W m − 2 requiring an overall power supply of 1 M W for a period of 80 days. The results have been compared with the data coming from another greenhouse of 1 hectare in the same conditions implementing a state-of-the-art strategy for artificial lighting control. Results outlines that potential 19.4% cost savings are achievable. Moreover, the algorithm can be used to transform the greenhouse in a viable source of energy flexibility for grid reliability.

Keywords: greenhouse; artificial lighting system; natural lighting; energy flexibility; predictive control; optimization; demand side management; algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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