Skip to main content

Low-Cost Systems for Agriculture Energy Management in Tunisia

  • Chapter
  • First Online:
Low Carbon Energy Supply

Part of the book series: Green Energy and Technology ((GREEN))

Abstract

Tunisia is one of the several countries where the agricultural greenhouses are used for maintaining the inside climate on its favorable environmental condition for production and plant growth. The agricultural greenhouse presents a complicated procedure because of the strong perturbations and the important number of its input parameters, which have a great potential and capacity to influence the climate inside it. A Fuzzy Logic Controller (FLC) is developed in order to promote a suitable microclimate by acting on the appropriate actuators installed inside the greenhouse such as the ventilation, the heating system, the humidifying, and the dehumidifying systems with the appropriate rate. The dynamic modeling of the studied greenhouse is presented and experimentally validated in the Research and Technology Center of Energy (CRTEn) in Tunisia and it is simulated using MATLAB/Simulink environment. Agricultural greenhouse presents an important number of its inputs; which have a great potential and capacity to influence the variation of the output parameters such as the internal temperature and the relative humidity. For this purpose, a contribution to combine a small wind turbine system to a greenhouse in order to power the actuators allows reducing the cost of the agricultural production.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Abbreviations

C a :

Specific heat of air (J kg−1 K−1)

d a :

Air density (kg m−3)

H :

Relative humidity

h :

Heat transfer coefficient (W m−2 K−1)

I :

Solar radiation (W m−2)

LAI:

Leaf area index

l :

Characteristic length of the leaf canopy (m)

m :

Measured parameters

n :

Number of variables

N h :

Number of heaters

T :

Temperature (K)

r a :

Aerodynamic resistance (s m−1)

r s :

Stomatal resistance (s m−1)

RE:

Rate of air infiltration (m3 s−1)

S :

Surface area (m2)

P(T):

Water vapor pressure at temperature T (kPa)

Q :

Heat rate (W)

V :

Volume (m3)

V r :

Ventilation rate (m s−1)

W :

Wind velocity (m s−1)

Z :

Depth of the soil

\( \beta \) :

Pitch angle

\( \alpha \) :

Absorptivity for solar radiations

\( \alpha_{\text{t}} \) :

Absorptivity for thermal radiations

\( \varepsilon \) :

Emissivity

\( \gamma \) :

Psychometric constant (kPa K−1)

\( \lambda \) :

Thermal conductivity (W m−1 K−1)

\( \rho \) :

Reflectivity

\( \sigma \) :

Stefan–Boltzmann constant 5.670 × 10−8 W m−2 K−4

\( \tau \) :

Transmissivity

av:

Average

c:

Cover

ca:

Canopy

i:

Inside

o:

Outside

s:

Soil

sky:

Sky

inf:

Infiltration

ventilation:

Ventilation

heating:

Heating

A:

Absorbed heat

C:

Convective heat

Cd:

Conductive

L:

Latent heat

R:

Radiation heat

References

  • Abdel-Ghany AM, Kozai T (2006) Dynamic modeling of the environment in a naturally ventilated, fog-cooled greenhouse. Renew Energy 31(10):1521–1539

    Article  Google Scholar 

  • Atia DM, El-madany HT (2016) Analysis and design of greenhouse temperature control using adaptive neuro-fuzzy inference system. J Electr Syst Inf Technol

    Google Scholar 

  • Ben Ali R, Aridhi E, Mami A (2015) Dynamic model of an agricultural greenhouse using Matlab-Simulink environment, pp 346–350

    Google Scholar 

  • Bouadila S, Lazaar M, Skouri S, Kooli S, Farhat A (2014a) Assessment of the greenhouse climate with a new packed-bed solar air heater at night, in Tunisia. Renew Sustain Energy Rev 35:31–41

    Article  Google Scholar 

  • Bouadila S, Kooli S, Skouri S, Lazaar M, Farhat A (2014b) Improvement of the greenhouse climate using a solar air heater with latent storage energy. Energy 64:663–672

    Article  Google Scholar 

  • Boughanmi H, Lazaar M, Bouadila S, Farhat A (2015) Thermal performance of a conic basket heat exchanger coupled to a geothermal heat pump for greenhouse cooling under Tunisian climate. Energy Build 104:87–96

    Article  Google Scholar 

  • Boulard T, Wang S (2000) Greenhouse crop transpiration simulation from external climate conditions. Agric For Meteorol 100(1):25–34

    Article  Google Scholar 

  • Cuce E, Harjunowibowo D, Cuce PM (2016) Renewable and sustainable energy saving strategies for greenhouse systems: a comprehensive review. Renew Sustain Energy Rev 64:34–59

    Article  Google Scholar 

  • Dahmouni AW, Ben Salah M, Askri F, Kerkeni C, Ben Nasrallah S (2010) Wind energy in the Gulf of Tunis, Tunisia. Renew Sustain Energy Rev 14(4):1303–1311

    Article  Google Scholar 

  • Dahmouni AW, Ben Salah M, Askri F, Kerkeni C, Ben Nasrallah S (2011) Assessment of wind energy potential and optimal electricity generation in Borj-Cedria, Tunisia. Renew Sustain Energy Rev 15(1):815–820

    Article  Google Scholar 

  • Díaz-Méndez R, Rasheed A, Peillón M, Perdigones A, Sánchez R, Tarquis AM, García-Fernández JL (2014) Wind pumps for irrigating greenhouse crops: comparison in different socio-economical frameworks. Biosyst Eng 128:21–28

    Article  Google Scholar 

  • Duffie J, Beckman W (1991) Solar engineering of thermal processes, 2nd edn. Wiley, New York, USA

    Google Scholar 

  • Fatnassi H, Boulard T, Bouirden L (2013) Development, validation and use of a dynamic model for simulate the climate conditions in a large scale greenhouse equipped with insect-proof nets. Comput Electron Agric 98:54–61

    Article  Google Scholar 

  • Fitz-Rodríguez E, Kubota C, Giacomelli GA, Tignor ME, Wilson SB, McMahon M (2010) Dynamic modeling and simulation of greenhouse environments under several scenarios: a web-based application. Comput Electron Agric 70(1):105–116

    Article  Google Scholar 

  • Fourati F (2014) Multiple neural control of a greenhouse. Neurocomputing 139:138–144

    Article  Google Scholar 

  • Grisales LT, Lemus CG (2014) Overall description of wind power systems 10(19):99–126

    Google Scholar 

  • Hasni A, Taibi R, Draoui B, Boulard T (2011) Optimization of greenhouse climate model parameters using particle swarm optimization and genetic algorithms. Energy Proc 6:371–380

    Article  Google Scholar 

  • Hassan GE, Salah AH, Fath H, Elhelw M, Hassan A, Saqr KM (2016) Optimum operational performance of a new stand-alone agricultural greenhouse with integrated-TPV solar panels. Sol Energy 136:303–316

    Article  Google Scholar 

  • Holman JP (1993) Experimental methods for engineers/J. P. Holman. Version details—Trove, 6th edn

    Google Scholar 

  • I. Renewable and E. Agency (2015) Renewable energy in the water, energy & food nexus. no. January, 2015

    Google Scholar 

  • Joudi KA, Farhan AA (2015) A dynamic model and an experimental study for the internal air and soil temperatures in an innovative greenhouse. Energy Convers Manage 91:76–82

    Article  Google Scholar 

  • Khoshnevisan B, Rafiee S, Omid M, Mousazadeh H, Clark S (2014) Environmental impact assessment of tomato and cucumber cultivation in greenhouses using life cycle assessment and adaptive neuro-fuzzy inference system. J Clean Prod 73:183–192

    Article  Google Scholar 

  • Kıyan M, Bingöl E, Melikoğlu M, Albostan A (2013) Modelling and simulation of a hybrid solar heating system for greenhouse applications using Matlab/Simulink. Energy Convers Manage 72:147–155

    Article  Google Scholar 

  • Kooli S, Bouadila S, Lazaar M, Farhat A (2015) The effect of nocturnal shutter on insulated greenhouse using a solar air heater with latent storage energy. Sol Energy 115:217–228

    Article  Google Scholar 

  • Kristjansdottir TF, Good CS, Inman MR, Schlanbusch RD, Andresen I (2016) Embodied greenhouse gas emissions from PV systems in Norwegian residential Zero Emission Pilot Buildings. Sol Energy 133:155–171

    Article  Google Scholar 

  • Lafont F, Balmat JF (2002) Optimized fuzzy control of a greenhouse. Fuzzy Sets Syst 128(1):47–59

    Article  MathSciNet  Google Scholar 

  • Lafont F, Balmat JF, Pessel N, Fliess M (2015) A model-free control strategy for an experimental greenhouse with an application to fault accommodation. Comput Electron Agric 110:139–149

    Article  Google Scholar 

  • Lazaar M, Bouadila S, Kooli S, Farhat A (2015) Comparative study of conventional and solar heating systems under tunnel Tunisian greenhouses: thermal performance and economic analysis. Sol Energy 120:620–635

    Article  Google Scholar 

  • Li C, Wang H, Miao H, Ye B (2017) The economic and social performance of integrated photovoltaic and agricultural greenhouses systems: case study in China. Appl Energy 190:204–212

    Article  Google Scholar 

  • Longo GA, Gasparella A (2015) Three years experimental comparative analysis of a desiccant based air conditioning system for a flower greenhouse: assessment of different desiccants. Appl Therm Eng 78:584–590

    Article  Google Scholar 

  • Maatallah T, El Alimi S, Dahmouni AW, Ben Nasrallah S (2013) Wind power assessment and evaluation of electricity generation in the Gulf of. Sustain Cities Soc 6:1–10

    Google Scholar 

  • Maher A, Kamel E, Enrico F, Atif I, Abdelkader M (2016) An intelligent system for the climate control and energy savings in agricultural greenhouses. Energy Effi 1–15

    Google Scholar 

  • Márquez-Vera MA, Ramos-Fernández JC, Cerecero-Natale LF, Lafont F, Balmat J-F, Esparza-Villanueva JI (2016) Temperature control in a MISO greenhouse by inverting its fuzzy model. Comput Electron Agric 124:168–174

    Article  Google Scholar 

  • Marucci A, Cappuccini A (2016) Dynamic photovoltaic greenhouse: energy efficiency in clear sky conditions. Appl Energy 170:362–376

    Article  Google Scholar 

  • Mesmoudi K, Soudani A, Zitouni B, Bournet PE, Serir L (2010) Experimental study of the energy balance of unheated greenhouse under hot and arid climates: Study for the night period of winter season. J Assoc Arab Univ Basic Appl Sci 9(1):27–37

    Google Scholar 

  • Ministère de l’Agriculture et des Ressources Hydrauliques (Hrsg.) (2006) Enquête sur les Structures des Exploitations Agricoles 2004–2005, pp 1–77

    Google Scholar 

  • Mohamed S, Hameed IA (2016) A GA-based adaptive neuro-fuzzy controller for greenhouse climate control system. Alexandria Eng J

    Google Scholar 

  • Nayak S, Tiwari GN (2010) Energy metrics of photovoltaic/thermal and earth air heat exchanger integrated greenhouse for different climatic conditions of India. Appl Energy 87(10):2984–2993

    Article  Google Scholar 

  • Nookuea W, Campana PE, Yan J (2016) Evaluation of solar PV and wind alternatives for self renewable energy supply: case study of shrimp cultivation. Energy Proc 88:462–469

    Article  Google Scholar 

  • Ozgener O (2010) Use of solar assisted geothermal heat pump and small wind turbine systems for heating agricultural and residential buildings. Energy 35(1):262–268

    Article  Google Scholar 

  • Pawlowski A, Beschi M, Guzmán JL, Visioli A, Berenguel M, Dormido (2016) Application of SSOD-PI and PI-SSOD event-based controllers to greenhouse climatic control. ISA Trans 65:525–536

    Article  Google Scholar 

  • Peillóna M, Sánchezb R, Tarquisc AM, García-Fernández JL (2013) The use of wind pumps for greenhouse microirrigation: a case study for tomato in Cuba. Agric Water Manage 120(1):107–114

    Article  Google Scholar 

  • Rasheed A, Lee JW, Lee HW (2016) Feasibility evaluation of the wind energy as an alternative energy source for the irrigation of greenhouse crops. Int J Renew Energy Res 6(4):1–25

    Google Scholar 

  • Revathi S, Sivakumaran N (2016) Fuzzy based temperature control of greenhouse. IFAC-PapersOnLine 49(1):549–554

    Article  Google Scholar 

  • Salgado P, Cunha JB (2005) Greenhouse climate hierarchical fuzzy modelling. Control Eng Pract 13(5):613–628

    Article  Google Scholar 

  • Taki M, Ajabshirchi Y, Ranjbar SF, Rohani A, Matloobi M (2016) Heat transfer and MLP neural network models to predict inside environment variables and energy lost in a semi-solar greenhouse. Energy Build 110:314–329

    Article  Google Scholar 

  • van Beveren PJM, Bontsema J, van Straten G, van Henten EJ (2015) Optimal control of greenhouse climate using minimal energy and grower defined bounds. Appl Energy 159:509–519

    Article  Google Scholar 

  • World Health Organization (WHO) (2014) http://apps.who.int/iris/bitstream/handle/10665/170620/WPR_RC065_10_Progress_Report_2014_en.pdf?sequence=2&ua=1

  • Zeng S, Hu H, Xu L, Li G (2012) Nonlinear adaptive PID control for greenhouse environment based on RBF network. Sensors (Basel) 12(5):5328–5348

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Salwa Bouadila .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Bouadila, S., Ben Ali, R. (2018). Low-Cost Systems for Agriculture Energy Management in Tunisia. In: Sharma, A., Shukla, A., Aye, L. (eds) Low Carbon Energy Supply. Green Energy and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-10-7326-7_5

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7326-7_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7325-0

  • Online ISBN: 978-981-10-7326-7

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics