“Use of Branch and Bound Algorithms for Greenhouse Climate Control” 7th International Conference – Haicta 2015 George Dimokas * Laboratory of Agricultural Constructions & Environmental Control Constantinos Kittas Introduction Material & Methods Results Conclusions Discussion Subject * Lecturer at T.E.I. of Peloponnese

Introduction Subject Material & Methods Results Conclusions Discussion 7th International Conference – Haicta 2015

Introduction Subject Material & Methods Results Conclusions Discussion 7th International Conference – Haicta 2015 Aim of the project The development of a decision support system that optimize greenhouse climate management during winter period according producers criteria

Introduction Subject Material & Methods Results Conclusions Discussion 7th International Conference – Haicta 2015 Biological Simulator Climate Simulator Central Engine Optimization Method Growers Needs Strategy for G.C.M Weather Generator

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Bio-Simulator Cli-Simulator Optimization Biological Simulator

Use of Biological simulators Introduction Material & Methods Results Conclusions Discussion Subject Bio-Simulator Cli-Simulator Optimization A useful “tool” for the growers: Prediction of production quantity Prediction of harvesting period Contribution in strategic management on Prediction of production quality Inputs Climate 7th International Conference – Haicta 2015

Biological Simulators Introduction Material & Methods Results Conclusions Discussion Subject Tomgro Hortisim Tomsim Sucros Bacros Elcros 7th International Conference – Haicta 2015 Bio-Simulator Cli-Simulator Optimization

Cultivation Simulators Introduction Material & Methods Results Conclusions Discussion Subject Tomato Cucumber Lettuce RosesRadish 7th International Conference – Haicta 2015 Bio-Simulator Cli-Simulator Optimization

Biological Simulator Maintenance respiration Gross photosynthesis Confirm the weather data from Climate Model Organs development rate Hourly “Loop” Daily initialization Integration of hourly variables for daily temperature calculation Amount of carbohydrates for the pool Rate of development for each organ Calculation the percentage of the appearance Growth respiration Number of organs Demand for assimilates for each organ Age class for each organ Ratio source / sink Daily “Loop” Calibration TOMGRO Validation

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Bio-Simulator Cli-Simulator Optimization Climate Simulator

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Use of Climate simulator A useful “tool” for the growers: Prediction of greenhouse climate Crop management Contribution in strategic management on Decrease fungus problems Inputs Climate Bio-Simulator Cli-Simulator Optimization

Climate Simulators Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 G.C.M. Hortisim Van Henten Micgreen Hortitrans Horticern Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Simulator Construction SimGreC Water Mass Balance Air Energy Balance Crop Energy Balance Cover Energy Balance Soil Energy Balance Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Model Inputs SimGreC Outside Rel. Humidity Outside Air Temperature Outside Solar Radiation Outside Wind Speed Heating System Energy Percentage of Window open Start value Air Temp. Start value Cover Temp. Start value Crop Temp. Start value Soil Temp. Controlled inputsSystem Controllers Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Model Outputs SimGreC Crop TempCover Temp Air Temp Soil Temp Relative Humidity Transpiration Crop condensation Cover condensation PAR Parameters Values Convection Radiation Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Bio-Simulator Cli-Simulator Optimization Time TransplantEnd Today Duration of Prediction Data Use of Biophysical Simulator Future Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Contemporary Concerns Series display problems Large number of possible solutions Which is the best ??? Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Methodology for Decision Support Requires use of "tools" The search for possible solutions The use of algorithms "Branch & Bound" Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Researching the space of possible solutions S S1S1 S2S2 S3S3 S4S4 S1S1 S2S2 S3S3 S4S4 S 21 S 22 S 31 S 32 (Α) (Β) (Γ) S S1S1 S2S2 S3S3 S4S4 S 21 S 22 S 31 S 32 S1S1 S4S4 Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 When it will open Percentage of Window opening 1.T i : air temperature inside greenhouse 2.RH: air humidity inside greenhouse 3.pb 1 : parameter 4.pRT: humidity parameter 5.pc 1 : parameter Ventilation Strategy Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Heating Strategy When it will open Percentage of Heating system opening 1.T i : air temperature inside greenhouse 2.DTi: air temperature difference between inside greenhouse and outside ambient air 3.RH: air humidity inside greenhouse 4.pb 2 : parameter 5.pRT: humidity parameter 6.pc 2 : parameter Bio-Simulator Cli-Simulator Optimization

Introduction Material & Methods Results Conclusions Discussion Subject 7th International Conference – Haicta 2015 Value equation - Objective function Bio-Simulator Cli-Simulator Optimization where Σ(fuel consumption) is the total energy gives the heating system inside the greenhouse, while respectively Σ(Plants D.W.) is the resulting dry weight of plant The problem to be solved is to minimize the objective function J to a range of possible solutions, S Restriction Function Function above reject some subset of possible solutions by further exploring inside, to find the possible solution when the above condition is true, that the optimal minimal solution that offers the particular subset is greater than the largest value of another subset

Introduction Material & Methods Subject Results Conclusions Discussion Material & Methods 7th International Conference – Haicta 2015

Introduction Material & Methods Subject Results Conclusions Discussion 7th International Conference – Haicta 2015 Experimental period from 1/10/2007 until 15/2/2008 Cultivation: Tomato Farm of the University of Thessaly

Introduction Material & Methods Subject Results Conclusions Discussion 7th International Conference – Haicta 2015 Biological Measurements Development Biomass production Fruit production

Introduction Material & Methods Subject Results Conclusions Discussion 7th International Conference – Haicta 2015 Climate Measurements Air, Cover, Soil, Crop temperature Relative humidity Solar radiation Wind speed CO 2 concentration

Results Conclusions Discussion Material & Methods Introduction Subject 7th International Conference – Haicta 2015

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta st Simulation

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject Optimization method 7th International Conference – Haicta 2015 Percentage (%) of window opening (-), during the first simulated period

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of measured (–) and optimally calculated (-) values, for air temperature ( o C) during the first simulated period Optimization method vs measured values

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of measured (–) and optimally calculated (-) values, for cover temperature ( o C) during the first simulated period Optimization method vs measured values

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of calculated values according modified TOMGRO ( ▲ ) and the optimal values according B & B algorithms ( ■ ), D.W. of leaves & stems, during the first simulated period Optimization method vs modified TOMGRO

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of calculated values according modified TOMGRO ( ▲ ) and the optimal values according B & B algorithms ( ■ ), number of nodes T.D.W. of plant, during the first simulated period Optimization method vs modified TOMGRO

Conclusions Discussion Results Material & Methods Introduction Subject 7th International Conference – Haicta nd Simulation 1 st Simulation

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Percentage (%) of window (-) and heating system (–) opening during the second simulated period Optimization method

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of measured (–) and optimally calculated (-) values, for air temperature ( o C) during the second simulated period Optimization method vs measured values

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of measured (–) and optimally calculated (-) values, for cover temperature ( o C) during the second simulated period Optimization method vs measured values

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of calculated values according modified TOMGRO ( ▲ ) and the optimal values according B & B algorithms ( ■ ), D.W. of leaves & stems, during the second simulated period Optimization method vs modified TOMGRO

Conclusions Discussion 2 nd Simulation 1 st Simulation Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Variation of calculated values according modified TOMGRO ( ▲ ) and the optimal values according B & B algorithms ( ■ ), number of nodes T.D.W. of plant, during the second simulated period Optimization method vs modified TOMGRO

Conclusions Discussion Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015

Conclusions Discussion Results Material & Methods Introduction Subject Conclusions of 1 st Simulated Period 7th International Conference – Haicta 2015 More ventilation is lowering inside air temperature create more robust plants in the future leads to reduction of whole plant’s D.W.

Conclusions Discussion Results Material & Methods Introduction Subject 7th International Conference – Haicta 2015 Less heating system operation led to a reduction of production costs by 19.72% the reduction caused in plants growth and development can be balanced with an increase of air temperature inside the greenhouse to a period prior to the reduction simultaneously a reduction of 17.4% for the whole plant’s D.W. Conclusions of 2 nd Simulated Period

Conclusions Discussion Results Material & Methods Introduction Subject Discussion 7th International Conference – Haicta 2015

Conclusions Discussion Results Material & Methods Introduction Subject The optimization method Useful “tool’ for the growers to: Predict correct the production quantity Predict the harvesting period Contribute in strategic management Reduce energy requirements 7th International Conference – Haicta 2015

Conclusions Discussion Results Material & Methods Introduction Subject The results are part of the research project 03ED526 Within the framework of the “Reinforcement Program of Human Research Manpower” (PENED) and co-financed:  75% from E.U.-European Social Fund  25% from the Greek Ministry of Development- General Secretariat of Research and Technology  and from a private company «AGREK» Samantouros 7th International Conference – Haicta 2015

Conclusions Discussion Results Material & Methods Introduction Subject Thank you 7th International Conference – Haicta 2015