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Model Predictive Control versus Traditional Relay Control in a High Energy Efficiency Greenhouse

Author

Listed:
  • Chiara Bersani

    (Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genova, Italy)

  • Marco Fossa

    (Department Mechanical, Energy, Management and Transportation Engineering, University of Genoa, 16145 Genova, Italy)

  • Antonella Priarone

    (Department Mechanical, Energy, Management and Transportation Engineering, University of Genoa, 16145 Genova, Italy)

  • Roberto Sacile

    (Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genova, Italy)

  • Enrico Zero

    (Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, 16145 Genova, Italy)

Abstract

The sustainable agriculture cultivation in greenhouses is constantly evolving thanks to new technologies and methodologies able to improve the crop yield and to solve the common concerns which occur in protected environments. In this paper, an MPC-based control system has been realized in order to control the indoor air temperature in a high efficiency greenhouse. The main objective is to determine the optimal control signals related to the water mass flow rate supplied by a heat pump. The MPC model allows a predefined temperature profile to be tracked with an energy saving approach. The MPC has been implemented as a multiobjective optimization model that takes into account the dynamic behavior of the greenhouse in terms of energy and mass balances. The energy supply is provided by a ground coupled heat pump (GCHP) and by the solar radiation while the energy losses related to heat transfers across the glazed envelope. The proposed MPC method was applied in a smart innovative greenhouse located in Italy, and its performances were compared with a traditional reactive control method in terms of deviation of the indoor temperature in respect to the desired one and in terms of electric power consumption. The results demonstrated that, for a time horizon of 20 h, in a greenhouse with dimensions 15.3 and 9.9 m and an average height of 4.5 m, the proposed MPC approach saved about 30% in electric power compared with a relay control, guaranteeing a consistent and reliable temperature profile in respect to the predefined tracked one.

Suggested Citation

  • Chiara Bersani & Marco Fossa & Antonella Priarone & Roberto Sacile & Enrico Zero, 2021. "Model Predictive Control versus Traditional Relay Control in a High Energy Efficiency Greenhouse," Energies, MDPI, vol. 14(11), pages 1-21, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3353-:d:570622
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    References listed on IDEAS

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    Cited by:

    1. Beatrice Faniyi & Zhenhua Luo, 2023. "A Physics-Based Modelling and Control of Greenhouse System Air Temperature Aided by IoT Technology," Energies, MDPI, vol. 16(6), pages 1-18, March.
    2. Gustavo Cevallos & Marco Herrera & Ramon Jaimez & Hanna Aboukheir & Oscar Camacho, 2022. "A Practical Hybrid Control Approach for a Greenhouse Microclimate: A Hardware-in-the-Loop Implementation," Agriculture, MDPI, vol. 12(11), pages 1-28, November.
    3. Aurora González-Vidal & José Mendoza-Bernal & Alfonso P. Ramallo & Miguel Ángel Zamora & Vicente Martínez & Antonio F. Skarmeta, 2022. "Smart Operation of Climatic Systems in a Greenhouse," Agriculture, MDPI, vol. 12(10), pages 1-18, October.
    4. Chiara Bersani & Carmelina Ruggiero & Roberto Sacile & Abdellatif Soussi & Enrico Zero, 2022. "Internet of Things Approaches for Monitoring and Control of Smart Greenhouses in Industry 4.0," Energies, MDPI, vol. 15(10), pages 1-30, May.

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