IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i1p202-d473940.html
   My bibliography  Save this article

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

Author

Listed:
  • Gianluca Serale

    (Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy
    Andlinger Center for Energy and The Environment, Princeton University, Olden St., 86, Princeton, NJ 08540, USA)

  • 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)

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.

Suggested Citation

  • Gianluca Serale & Luca Gnoli & Emanuele Giraudo & Enrico Fabrizio, 2021. "A Supervisory Control Strategy for Improving Energy Efficiency of Artificial Lighting Systems in Greenhouses," Energies, MDPI, vol. 14(1), pages 1-19, January.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:1:p:202-:d:473940
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/1/202/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/1/202/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    2. Yongtao Shen & Ruihua Wei & Lihong Xu, 2018. "Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature," Energies, MDPI, vol. 11(1), pages 1-17, January.
    3. Gianluca Serale & Massimo Fiorentini & Alfonso Capozzoli & Daniele Bernardini & Alberto Bemporad, 2018. "Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities," Energies, MDPI, vol. 11(3), pages 1-35, March.
    4. Adnan Rasheed & Wook Ho Na & Jong Won Lee & Hyeon Tae Kim & Hyun Woo Lee, 2019. "Optimization of Greenhouse Thermal Screens for Maximized Energy Conservation," Energies, MDPI, vol. 12(19), pages 1-20, September.
    5. Jung, Wooyoung & Jazizadeh, Farrokh, 2019. "Human-in-the-loop HVAC operations: A quantitative review on occupancy, comfort, and energy-efficiency dimensions," Applied Energy, Elsevier, vol. 239(C), pages 1471-1508.
    6. Singh, Devesh & Basu, Chandrajit & Meinhardt-Wollweber, Merve & Roth, Bernhard, 2015. "LEDs for energy efficient greenhouse lighting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 139-147.
    7. Yan, Xing & Ozturk, Yusuf & Hu, Zechun & Song, Yonghua, 2018. "A review on price-driven residential demand response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 411-419.
    8. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    9. Golzar, Farzin & Heeren, Niko & Hellweg, Stefanie & Roshandel, Ramin, 2018. "A novel integrated framework to evaluate greenhouse energy demand and crop yield production," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 487-501.
    10. Barkat Rabbi & Zhong-Hua Chen & Subbu Sethuvenkatraman, 2019. "Protected Cropping in Warm Climates: A Review of Humidity Control and Cooling Methods," Energies, MDPI, vol. 12(14), pages 1-24, July.
    11. Chiara Bersani & Ahmed Ouammi & Roberto Sacile & Enrico Zero, 2020. "Model Predictive Control of Smart Greenhouses as the Path towards Near Zero Energy Consumption," Energies, MDPI, vol. 13(14), pages 1-17, July.
    12. Yano, Akira & Cossu, Marco, 2019. "Energy sustainable greenhouse crop cultivation using photovoltaic technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 116-137.
    13. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Chen, Wei-Han & Mattson, Neil S. & You, Fengqi, 2022. "Intelligent control and energy optimization in controlled environment agriculture via nonlinear model predictive control of semi-closed greenhouse," Applied Energy, Elsevier, vol. 320(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rabiu, Anis & Adesanya, Misbaudeen Aderemi & Na, Wook-Ho & Ogunlowo, Qazeem O. & Akpenpuun, Timothy D. & Kim, Hyeon Tae & Lee, Hyun-Woo, 2023. "Thermal performance and energy cost of Korean multispan greenhouse energy-saving screens," Energy, Elsevier, vol. 285(C).
    2. Premaratne Samaranayake & Chelsea Maier & Sachin Chavan & Weiguang Liang & Zhong-Hua Chen & David T. Tissue & Yi-Chen Lan, 2021. "Energy Minimisation in a Protected Cropping Facility Using Multi-Temperature Acquisition Points and Control of Ventilation Settings," Energies, MDPI, vol. 14(19), pages 1-18, September.
    3. Zhong, Shengyuan & Zhao, Jun & Li, Wenjia & Li, Hao & Deng, Shuai & Li, Yang & Hussain, Sajjad & Wang, Xiaoyuan & Zhu, Jiebei, 2021. "Quantitative analysis of information interaction in building energy systems based on mutual information," Energy, Elsevier, vol. 214(C).
    4. Schellenberg, C. & Lohan, J. & Dimache, L., 2020. "Comparison of metaheuristic optimisation methods for grid-edge technology that leverages heat pumps and thermal energy storage," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    5. Vahid-Ghavidel, Morteza & Shafie-khah, Miadreza & Javadi, Mohammad S. & Santos, Sérgio F. & Gough, Matthew & Quijano, Darwin A. & Catalao, Joao P.S., 2023. "Hybrid IGDT-stochastic self-scheduling of a distributed energy resources aggregator in a multi-energy system," Energy, Elsevier, vol. 265(C).
    6. Katzin, David & van Henten, Eldert J. & van Mourik, Simon, 2022. "Process-based greenhouse climate models: Genealogy, current status, and future directions," Agricultural Systems, Elsevier, vol. 198(C).
    7. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    8. Dranka, Géremi Gilson & Ferreira, Paula, 2019. "Review and assessment of the different categories of demand response potentials," Energy, Elsevier, vol. 179(C), pages 280-294.
    9. Xu, Jiuping & Liu, Tingting, 2020. "Technological paradigm-based approaches towards challenges and policy shifts for sustainable wind energy development," Energy Policy, Elsevier, vol. 142(C).
    10. Parajuli, Samvid & Narayan Bhattarai, Tek & Gorjian, Shiva & Vithanage, Meththika & Raj Paudel, Shukra, 2023. "Assessment of potential renewable energy alternatives for a typical greenhouse aquaponics in Himalayan Region of Nepal," Applied Energy, Elsevier, vol. 344(C).
    11. Bhagya Nathali Silva & Murad Khan & Kijun Han, 2020. "Futuristic Sustainable Energy Management in Smart Environments: A Review of Peak Load Shaving and Demand Response Strategies, Challenges, and Opportunities," Sustainability, MDPI, vol. 12(14), pages 1-23, July.
    12. Pereira, Diogo Santos & Marques, António Cardoso, 2020. "How should price-responsive electricity tariffs evolve? An analysis of the German net demand case," Utilities Policy, Elsevier, vol. 66(C).
    13. da Fonseca, André L.A. & Chvatal, Karin M.S. & Fernandes, Ricardo A.S., 2021. "Thermal comfort maintenance in demand response programs: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    14. Navid Rezaei & Abdollah Ahmadi & Mohammadhossein Deihimi, 2022. "A Comprehensive Review of Demand-Side Management Based on Analysis of Productivity: Techniques and Applications," Energies, MDPI, vol. 15(20), pages 1-28, October.
    15. Mingzhi Zhao & Ningbo Wang & Chun Chang & Xiaoming Hu & Yingjie Liu & Lei Liu & Jianan Wang, 2023. "Comparative Analysis of the Filling Mass of Vertical Heat Exchanger Tubes on the Thermal Environment of Arched Greenhouses," Energies, MDPI, vol. 16(13), pages 1-28, July.
    16. Alperen Yayla & Kübra Sultan Świerczewska & Mahmut Kaya & Bahadır Karaca & Yusuf Arayici & Yunus Emre Ayözen & Onur Behzat Tokdemir, 2022. "Artificial Intelligence (AI)-Based Occupant-Centric Heating Ventilation and Air Conditioning (HVAC) Control System for Multi-Zone Commercial Buildings," Sustainability, MDPI, vol. 14(23), pages 1-29, December.
    17. Morales-España, Germán & Martínez-Gordón, Rafael & Sijm, Jos, 2022. "Classifying and modelling demand response in power systems," Energy, Elsevier, vol. 242(C).
    18. Blaud, Pierre Clement & Haurant, Pierrick & Chevrel, Philippe & Claveau, Fabien & Mouraud, Anthony, 2023. "Multi-flow optimization of a greenhouse system: A hierarchical control approach," Applied Energy, Elsevier, vol. 351(C).
    19. Zhang, Menghang & Yan, Tingxiang & Wang, Wei & Jia, Xuexiu & Wang, Jin & Klemeš, Jiří Jaromír, 2022. "Energy-saving design and control strategy towards modern sustainable greenhouse: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 164(C).
    20. Costantino, Andrea & Comba, Lorenzo & Sicardi, Giacomo & Bariani, Mauro & Fabrizio, Enrico, 2021. "Energy performance and climate control in mechanically ventilated greenhouses: A dynamic modelling-based assessment and investigation," Applied Energy, Elsevier, vol. 288(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:1:p:202-:d:473940. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.