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Energy saving through integrated greenhouse climate control for heating, ventilation and carbon dioxide… Lee, Dal-Hoon 1993

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ENERGY SAVING THROUGH INTEGRATED GREENHOUSE CLIMATECONTROL FOR HEATING, VENTILATION ANDCARBON DIOXIDE ENRICHMENTbyDal—Hoon LeeB. Eng., Hanyang University, Seoul, Korea, 1971M. Eng., University of Alberta, Edmonton, 1979A THESIS SUBMITTED IN PARTIAL FULFILMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF APPLIED SCIENCEinFACULTY OF GRADUATE STUDIESDepartment of Bio—Resource EngineeringWe accept this thesis as conformingto the required standardTHE UNIVERSITY OF BRITISH COLUMBIADecember 1993© Dal H. Lee, 1993In presenting this thesis in partial fulfilment of the requirements for an advanceddegree at the University of British Columbia, I agree that the Library shall make itfreely available for reference and study. I further agree that permission for extensivecopying of this thesis for scholarly purposes may be granted by the head of mydepartment or by his or her representatives. It is understood that copying orpublication of this thesis for financial gain shall not be allowed without my writtenpermission.(Signature)________________________Department of 1o I2.5oLlC5The University of British ColumbiaVancouver, CanadaDate ;(4J -/i4--DE-6 (2/88)ABSTRACTA computer model was developed for predicting heating,ventilation and CO2 enrichment requirements for a standard tomatogreenhouse range located in the Fraser valley of British Columbia.Predicted and measured data were compared for typical cases ofoutside weather conditions.The mathematical model which is comprised of heat and massbalances for the greenhouse thermal environment and cropphotosynthesis has yielded reasonably accurate simulation resultscompared to observed values.Heating requirement was predicted to within 10-14% for threetypical cases of weather conditions, but deviated by 35% fromactual energy consumption data under one situation(Case #3).Predicted ventilation demand also followed closely the trend ofobserved vent openings data, except for Case #4 . Energy saving isachieved in different manners for the four cases.11TABLE OF CONTENTSPAGESECTION 2. LITERATURE REVIEW 42.1 Computer Modeling 42.2 Evironmental Factors and Plant Growth 82.2.1 Light or PAR 82.2.2 Temperature 92.2.3 Interaction of Temperature/Light Effect 122.2.4 IIu:midity 122.2.5 Carbon Dioxide (C02) 13SECTION 3. MATERIAL AND METHODS 173.1 Data Collection 173.2 Mathematical Modeling and Computer Simulations..213.2.1 Heat Balance Heating Requirement Ventilation Requirement 29iiiABSTRACTTABLE OF CONTENTSLIST OF TABLESLIST OF FIGURESACKNOWLEDGEMENTSECTION 1. INTRODUCTION1.1 General1.2 Objectivesiiiiivvivii1133.2.2 Mass Balances.313.2.2.1 Mass Balance for Moisture 313.2.2.2 Mass Balance for Carbon Dioxide.. 33SECTION 4. RESULTS AND DISCUSSION 394.1 Heating Requirement 394.2 Ventilation Requirement 434.3 Carbon Dioxide Requirement 474.4 Energy- Saving 49SECTION 5 • CONCLUSION AND RECOMMENDATIONS 845.1 Conclusions 845.2 Recommendatins 85REFERENCES 87APPENDIX A. Summary Table of Heating, Ventilation andCO2Requirements 94APPENDIX B. Monthly Energy Consumption Data 107ivLIST OF TABLES3.1 Data Collection 193.2 Outside Climate Conditions Considered 204.1 Simulation Results for Case 1 54a4.2 Simulation Results for Case 2 554.3 Simulation Results for Case 3 584.4 Simulation Results for Case 4 61VLIST OF FIGURES4. ic4. id4. le4. 2a4.2b4. 2c4.2d4. 2e4. 3a4.3b4. 3c4.3d4. 3e4.4a4.4b4. 4c4.4d4. 4e6667686970717273747576777879808182833.1 Energy Flux Schematics 18a3.2 The Dimensions of the Greenhouse 18b4.la Outside Climate Conditions for Case 1 644.lb Inside Climate Conditins for Case 1 65Heating Requirement for Case 1Ventilation Requirement for Case 1C02 Depletion and Supply for Case 1Outside Climate Conditions for Case 2Inside Climate Conditins for Case 2Heating Requirement for Case 2Ventilation Requirement for Case 2C02 Depletion and Supply for Case 2Outside Climate Conditions for Case 3Inside Climate Conditins for Case 3Heating Requirement for Case 3Ventilation Requirement for Case 3CO2 Depletion and Supply for Case 3Outside Climate Conditions for Case 4Inside Climate Conditins for Case 4Heating Requirement for Case 4Ventilation Requirement for Case 4C02 Depletion and Supply for Case 4viACKNOWLEDGEMENTThe author wishes to express his gratitude to Dr. Anthony A.K.Lau for his guidance and suppervision of this study. His ideas,supports, suggestions and experience in the field of greenhousemanagement ensured the success of this report.The author also wishes to thank Dr. K.L. Pinder and Dr. K.V.Lo for reviewing the initial manuscript, providing me with thenecessary advice and sitting on my Committee.Also my sincere gratitude to my wife, Hye—Kyoo Lee, for herconstructive criticism and inspiration during my M.A.Sc.vii1SECTION 1. INTRODUCTION1.1 GeneralGreenhouses are means to provide protected cultivation ofhorticultural crops to overcome adverse climate conditions. Throughproper climate control, plants are grown under optimalenvironmental conditions and hence greenhouse crop products canoffer the best possible quality and consistency to local consumers.The consistent quality assures a premium price in peak priceperiods when imported field product varies in quality andreliability of supply. Increasing exports to other parts of thecontinent and overseas have been realized in recent years. InCanada, the present farm gate value of greenhouse vegetable andflower production amounts to some 500 million dollars.High energy cost remains a major obstacle to a stronger growthof the industry, as energy related expenses in the multipleprocesses of heating, ventilation, lighting, carbon dioxideenrichment and irrigation account for about 20 to 30 percent of thetotal operating cost. Concern over potential instability in fossilfuel costs and their availability has resulted in anintensification of research efforts aiming at developing energyconservation techniques and alternate energy sources since theearly 1970’s. Although, at present, energy saving is not ofparticular concern to growers who often choose to maximize2production at all costs, any longterm solution to the problem shallconsider environmental protection that calls for reduced fossilfuel usage.Energy conservation can be achieved in a variety of waysincluding better design and maintenance of greenhouse heating &ventilating systems and improved control of greenhouse environmentusing computer—based environmental controllers. Computers have thecapacity to control the greenhouse environment to pre—selected setpoint values. Commercial greenhouse computers have made steadyprogress in producing the best possible aerial environment for thecrop while minimizing the risk of disease and infestation. Today’scultivation techniques such as hydroponics, carbon dioxideenrichment, supplemental lighting and irrigation, as well as energyconservation by means of thermal screens have been incorporated inthe control algorithms that consider some interactions among themajor greenhouse environment variables — temperature, humidity,light, and carbon dioxide, also, electrical conductivity and pH ofthe nutrient solution. Nevertheless, the use of the physiologicalprocesses of plant growth in the control algorithms is minimal(Bailey, 1985), and hence, optimal greenhouse yield cannot beachieved when energy saving is desired.This thesis isolates energy and carbon dioxide as the criticalfactors of production, and uses the computer modelling and systemssimulation approach for the analysis of commercial greenhouse3facilities. Computer modelling and simulation provides an effectivemeans to obtain quantitative information for system optimizationpurposes. The overall goal of this research study is to developalgorithms for optimizing energy use and crop yield.1.2 ObjectivesThe specific objectives are listed as follows:1. to predict energy consumption involved in the heating,ventilation and CO2 enrichment processes;2. to predict ventilation requirement;3. to estimate CO2 depletion due to crop photosynthesisand ventilation;4. to verify simulated results with actual data, and5. to recommend an integrated climate control algorithm forenergy conservation purposes.4SECTION 2. LITERATURE REVIEW2.1 Computer ModelingModeling and simulation of the climate control behavior ofgreenhouses can be regarded as the backbone in the development ofcontrol algorithms.Mathematical modelling of the thermal environment can beclassified as steady state (static modelling) or transient state(dynamic modelling). Static models can be used to estimate heatingand ventilation demands, for instance, while dynamic models aremore appriorate for accurately describing instantaneouscharacteristics (leaf, cover and air temperatures, humidity, CO2level) of the system accurately.The first comprehensive study to characterize the physics ofthe greenhouse environment was published by Businger (1963). Steadystate equations are used to calculate the energy fluxes occuring ina greenhouse, whereby the storage capacity of the system is assumednegligible relative to the daily energy input, and therefore thegreenhouse is considered to adjust immediately to changes in theexternal conditions. Air and cover temperature, as well as thevaper pressure of the greenhouse air are assumed to be inequilibrium conditions. Subsequently, on the basis of Businger’s5work, Walker et al. (1983) presented an energy balance forgreenhouse air as follows:q+q+qr+qf=qcd+qg+qv+qff+qt+qp (1.1)whereq8 = net solar input q = equipment heatq = heat of respiration qf = furnace heatcd = convective/conductive heat transferqg = heat to ground= ventilation heat loss q = infiltration heat loss= heat of photosynthesis q = thermal radiation to sky* All units are in [WJ or equivalent.Several terms represent a negligible energy flux. The heatsof respiration and photosynthesis are often ignored, amounting toless than 3% of the incident solar radiation. The heat flux downinto the ground is also very small compared to upward convective,conductive, and radiative losses (Horiguchi, 1979). The heat fromequipment such as lights and fans will be excluded from greenhousesthat use natural ventilation system and no supplemental lighting.Modelling of the greenhouse thermal environment has beenpresented by many other researchers with different degrees ofcomplexity (For example, Arinze et al., 1984; Bot, 1983; Kimball,1986) while others have attempted models relating growth of a crop6to the environment for interactive environmental control (Challaand van de Vooren, 1980, Takakura, 1982).Steady state models are adequate for sizing heating andventilation equipment for greenhouse operations, and to some extentprovide a basic level of climate control. Kimball (1973) pointedout that it is necessary to calculate accurately the heating andcooling requirements in order to evaluate various methods ofcontrolling temperature in greenhouses. A simulation model willcalculate the energy fluxes occurring in a greenhouse. The fluxesare formulated in terms of known weather and greenhouse parameters.Unknowns (temperatures and vapour pressures) can then be calculatedfrom the solution to a set of simultaneous energy balance equationsthat describe several components of the greenhouse thermalenvironment.Albright et al.(1985) presented a lumped model for insituthermal calibration of unventilated greenhouse. They introduced theconcept of a “thermal mass temperature” to be incorporated in asingle equation that comprised of four parameters, namely, heatcapacity, overallheat transfer coefficient, correction factor forradiative heat transfer and solar heating efficiency. Marsh andAlbright (1991a,b) extended their method to estimate the achievabletemperature inside a ventilated greenhouseEach of these models gave reasonably accurate prediction of7the greenhouse environmental conditions, suggesting that the modelsmay not be very sensitive to certain parameters, and thereforeunnecessarily complicated models are not warranted. In this regard,Van Bavel et al. (1985) made a comparison of simulation models forcalculating the greenhouse climate and its energy requirements forboth heating and cooling. Seven sets (days) of data that representvarious weather conditions in Lubbock (USA), Tokyo (Japan) andWageningen (The Netherlands) were used for detailed computations.They concluded that although the models differ with regard to heatand mass transfer parameters between the greenhouse air and thecrop, the control functions for heating and cooling, and the methodof estimating transpiration, the models produced essentially thesame results in air temperature, humidity, and heatingrequirements. However, significant differences were found betweenthe estimates of daily amounts of transpiration.Conventional climate control technology affect plant growth inan indirect manner by manipulating the aerial environment. Recentresearch works (Challa et al.1988; Dixon, 1987; Jones et al. 1991b)indicate that increasing efforts are being focused upon biosystemsimulation, which is essential for a better understanding of therelationship between the physical and the biological systems, andeventually the synthesis of improved climate control strategies.Control algorithms that link to online measurement of plantresponses directly, for instance, leaf temperature, leaf area,water potential, net photosynthetic rate and transpiration rate8were explored by Hashimoto et al. (1980), Hack (1989) and Yang etal. (1990).2.2 Environmental Factors and Plant GrowthConventionally, the greenhouse aerial environment isrepresented by spatial average values of climate variables, namelysolar radiation and light, temperature,humidity and CO2concentration, which are factors that affect the physiologicalprocesses and hence the growth and development of plants.The principle of limiting factors stated that the rate of aprocess is limited by the pace of the slowest factor (Mastalerz,1979). In general, all these major growth factors (light, CO2 andtemperature) have to be at their optimal values for maximum plantgrowth and development. There are exceptions, though, when onefactor is at an inadequate level, other factors could be maintainedat high levels to compensate for the deficiency.Plant growth is a collection of many processes with differentsensitivities to environmental factors which may interact with eachother. This section reviews these factors whereas the next sectionconcerns computer modeling. Knowledge of these two aspects arenesessary for executing the process of finding the most desirableor optimal climate control strategy.92.2.1 Light or PRGaastra (1959) found that the photosynthetic rate ofindividual tomato leaves approached a maximum when light or PAR(photosynthetically Active Radiation) reached above 120-150 W/ra2.Yet, the rate of canopy photosynthesis continued to increase beyond150 W/m2, since a crop canopy consists of layers of leaves, suchthat light transmitted through the upper leaves will be absorbed byleaves lower in the canopy.de Visser and Vesseur (1982) as cited by Cockshull concludedthat 1% less light would reduce greenhouse cucumber yield by about1*, and the yield reduction was more obvious in the early part ofthe year. A similar correlation was found for tomatoes.Another important index is light integral. It is related toflower initiation and development. For tomatoes, light integrals of0.9 MJ/m2.d permitted almost all flowers on a truss to develop toanthers whereas almost all flowers aborted at 0.35 MJ/m2.d. InVancouver, a tomato crop seeded in November will start to bearfruit in February when the light level is sufficient to meet thiscriterion.2 • 2 • 2. TemperatureThe temperature range over which plants can photosynthesize is10large. For C3 plants such as tomatoes and cucumbers,photorespiration activity increases with temperature andcounteracts the stimulating effect of temperature on growth. Thus,temperature regime is lower for C3 plants(15-25 °C) compared to C4plants (30-45 °C). For photosynthesis and therefore, dry weightgain, day temperature must be higher than night temperature, sothat dark respiration rate is minimized.The horticultural industry uses a temperature band fortemperature control, i.e. greenhouse temperature is maintainedbetween T (24°C day/18°C night) and T (20°C day/16°C night).Controlling the humidity to a precise level is more difficultbecause the sensors are not very accurate. Also an individualgrower’s experience dictate the desired humidity levels.Nevertheless, a similar band between RH., (e.g. 80% day, 90%night) and RH., (e.g. 65% day and night) can be created forhumidity control.The proper temperature is not only important forphotosynthesis, but it also exerts a strong influence on thebalance between vegetative (leaf, stem and shoot) and generative(flower and fruit) growth. At higher temperatures, the strongassimilate demand by the growing fruits come at the expense ofdelayed growth of newly set fruits and even flower abortion becauseof low assimilate surplus. After some time, the total sink strengthof the fruits becomes low and the plant can have strong vegetative11growth again. Healthy flowers will then develop resulting in theonset of a second cycle of strong fruit growth. This cyclic patternof generative growth and vegetative growth means plants probablytend to a functional balance between the two kinds of growth; fortomatoes, intermediate temperatures of 19°C to 21°C are required forthe most stable fruit growth.Greenhouse crops respond more to the 24—hour averagetemperature than to the specific daytime and nighttimetemperatures, depending on the amplitude of the temperaturefluctuations and the buffering capacity of the plant. Lacroix etal. (1993) reconfirmed that greenhouse temperature regimes could bemore flexible than those traditionally used. As long as thetemperature setting followed a sine wave that produced the same24h—average temperature, temperature setpoints might be manipulatedso as to reduce energy consumption by 3 to 15% without adverselyaffecting production (Miller et al., 1985; Aikman and Picken,1989). In other words, the setpoint can be lowered when heat lossis higher than average due, for example, to high wind conditions;it can also be increased when the heat loss factor is anticipatedto be relatively low. In this way we can shift some heating toperiods when it is less costly to heat the greenhouse.In terms of biological control of pests, cooler growingregimes for tomato crop would make it more difficult to controlinfestations of the greenhouse whitefly (Trialeurodes12vaporariorum), as cool night temperatures promote colonization bythe pest but not its parasite (Encarsia formosa).132.2.3. Interaction of temperature/light effectIf the greenhouse is maintained at a lower temperature, thecrop can easily grow too ‘heavy’, particularly when there issufficient light. The disadvantages of a heavy crop are that theyare more likely attacked by fungal diseases and they produce lowerquality fruits. Depending on the light level, one must find atemperature setting that enables maximum assimilation.Calvert (1964) studied the behavior of young tomato plants.His data showed that the relative growth rate at 15.6 °C will fallif the daily light integral drops from 2.0 to 1.5 MJ/m2.d but canbe restored to its original level if the 24h average temperature israised to 17.2 °C.2.2.4 HumidityRelative humidity level of 70-80% allows adequatetranspiration to take place. High humidity in excess of 90% canincrease the incidence of fungal diseases due to condensation ofwater vapor on the foliage whenever the leaf temperature is lowerthan the dewpoint temperature of the air. A more serious effect isa reduction in transpiration. Less transpiration will not only meanless ability for the plant to cool itself and subsequent leafdousage, will have implications for growth and development, fruitquality, occurrence of physiological disorders, and cause weaker14plants which become more sensitive to rapid changes in environment.For example, Calcium is less mobile in the leaves and young fruits,thus restricting cell division and ultimately the sink capacity ofthe fruit.Grange and Hand (1987) argued that the most useful term fordescribing the humidity of air inside greenhouses is not relativehumidity, but rather the vapor pressure deficit (vpd) which hasvalues usually ranging from 0 to 1 kPa. Low vpd values correspondto high relative humidity and vice versa. For tomatoes, Cockshull(1988) found that the young leaves have smaller area when the vpdis low (0.1—0.2 kPa).A proper humility level is essential for pollination. Pollenis less likely to be shed from the anthers under high humidityconditions, while humidity too low will cause pollen to tend not tostick to the stigma.Bakker (1988) found that final yield in terms of both fruitweight and number of fruits of tomatoes was reduced by highnighttime humidity. Fruit quality at harvest and shelf life of thefruits were also poored.2.2.5 Carbon Dioxide (C02)Nighttime respiration contributes CO2 to the greenhouse15atmosphere. At dawn, CO2 concentrations often exceed the normalatmospheric level of 340 ppm, but as light levels increase duringthe day, photosynthesis quickly consumes the excess and drives CO2to below 340 ppm. In multispan greenhouses, CO2 depletion is evenmore severe as less infiltration occurs. Growth could virtuallycease at levels of 50—100 ppm, if not compensated by increasedlight level and/or temperature.In winter time (January and February), the amount of CO2generated by the central hot water heating system is sufficient toelevate the CO2 concentration beyond 340 ppm. As the heating demanddecreases towards spring time, CO2 supply is also reduced, whileincreased light level lead to more photosynthesis and thus CO2consumption, CO2 can be depleted considerably below ambient,production will therefore be substantially below its potential. Itwas estimated that 350 kg/ha of dry matter and 7000 kg/ha (11%) ofloss in fruit production will occur because of CO2 depletion whileabout 40000 kg/ha more fruits or 1700 kg/ha more dry matter resultsfrom enrichment to 1000 ppm.CO2 enrichment of greenhouses is practised to improveproductivity and quality of greenhouse crops. The beneficialeffects of adding carbon dioxide to the greenhouse environment havebeen well documented. In short, tomato fruit size and number (moretrusses and more fruit per truss) are increased, and the harvestpeak is shifted forward. Earliness may be increased by several16days. Dry weights increased up to 30% in young tomato plantspropagated under low winter light conditions and C02 enrichment; itappears that increases in photosynthetic rate due to enhanced C02concentration gradient even under low light conditions aresufficient to sustain early flower development. Transport ofcarbohydrates to the developing fruit are increased at higher CO2concentrations.Threefold CO2 enrichment (i.e. enriched to 1000 ppm) isnormally recommended if practicable. Above 1500 ppm, theaccumulated starch can cause deformation of chloroplast structurewhich may limit photosynthetic capacity. In the absence ofventilation, it is customary to supply CO2 at a flow rate of 56kg/ha.h in order to attain an enrichment level of 1000 ppm in agreenhouse full of plants under moderate light and calm weatherconditions. By the end of April it becomes increasingly uneconomicto maintain a constant level of 1000 ppm CO2 in the daytime asventilation is frequently required to remove excess solar heatunder sunny and warm climatic conditions.According to Hicklenton (1988), as the frequency of airexchange increases due to more ventilation or when photosyntheticconsumption is greater, the CO2 injection rate should increasesubstantially, up to 170 kg/ha.h, to maintain the desiredconcentration. In terms of resource utilization, it required 1400m3 of natural gas to be combusted to prevent CO2 depletion while it17needs 16000 m3 of natural gas to raise the CO2 level to 1000 ppm.Maximum benefit will accrue if C02 enrichment is available betweensunrise and sunset (Challa and Schadenponk, 1986).Daytime greenhouse temperatures can be raised between 3 and 5°Cwhen CO2 is applied, so that ventilators remain closed for a longerperiod. Nevertheless, both processes of carbon dioxide uptake andtranspiration are diffusion processes. As mass diffusivity of watervapor in air is almost twice as large as that of carbon dioxide, CO2supplement has to give way to ventilation if vent openings are theonly means to control excessive humidity.18SECTION 3. MATERIALS JND METHODSThe study consists of two parts: data collection and computersimulations.3.1 Data CollectionActual data were collected from a commercial vegetablegreenhouse (Hazelmere Greenhouses) growing tomatoes in SouthSurrey, B.C. The greenhouse is of Venlo-style, multispan type; theentire greenhouse is comprised of many smaller houses having thesame dimensions. The dimensions of a greenhouse are shown in Figure3.1. There are 27 houses and the total floor area is 25,400 m2 forthe tomates. Table 3.1 shows the different types of outside climateand inside climate data, as well as data related to the heating andventilation systems. All the sensors were installed in 1990 byCanadian Climatrol Systems, the representative of ‘Priva ClimateControl ‘ based in the Netherlands, except for the outside relativehumidity sensor which was set up in 1991 when this study wasinitiated. With the climate data storage protocol of the PRIVACV—250 climate control computer system, these data were collectedand stored at various time intervals, ranging from 5 minutes to twohours.These data were obtained under a wide range of outside climateconditions. Records compiled from such measurements were analyzed<Fig. 3.la Energy Flux Schematics>27 houses = 172.8 riO,8mm147L.lL2I—..—Section View<Fig. 3.lb The dimensions of a greenhouse>19Parameters monitored and/or controlled by the Priva CV—250 Climatecontrol computer system:Outside Climate:— Temperature- Wind speed— Solar radiation- Relative humidityInside Climate:— Temperature— CO2 Concentration- Relative humidity— Solar radiationHeating:— Heating water temperature— Boiler temperatureVentilation:— Windward vent openings— Leeward vent openingsTable 3.1 Data Collection20CASE SOLAR TEMPERATURE1. H H2. H L3. L H4. L LSolar;H : greater than 600 W/m2L : less than 300 W/m2Temperature;H : greater than 20 °CL : less than 10 °CTable 3.2 Outside Climate Conditions Considered21for achieving the research objectives.3.2 Mathematical Modelling and Computer SimulationsA transient state mathematic model that is comprised ofheat and mass balances, and having a time step of one hour will beused to predict energy consumption due to heating and ventilationand C02 enrichment. For the purpose of computer modeling, hourlydata were retrieved from the Priva Computer and stored on the harddisk of a P.C. Outside climate data constituted the boundaryconditions for the mathematical model whereas energy consumptionand vent openings data were used for model verification. Table 3.2shows the outside conditions considered for this research. Fourcases with different combinations of outside weather in terms ofsolar radiation (and thus PAR or light) and temperature wereselected among a months of data for the simulations,in order totest the flexibility of the computer model. Inputs for the modelare the physical characteristics of the crop, of the greenhouse andof the control system.Three types of climate control actions were considered in thecomputer model; they are temperature control, humidity control andCO2 control. Industrial climate computers have advanced controlstrategies that combine feedforward algorithms that anticipatechanges, and feedback (proportional & integral) algorithms for22making adjustments. Heat balance and psychrometric equations areused in the feedforward control algorithms for temperature control.However, equations that represent plant physiological processeshave not been applied to date, and are presented in this section.Temperature ControlWhen the inside air temperature (T1) is lower than the heatingsetpoint, furnace heating is required. When the inside airtemperature becomes higher than the ventilation setpoint, vents areopened.Humidity ControlWhen the inside relative humidity (W) is higher than therelative humidity setpoint, vents will be opened, provided that themoisture content of outside air (W0) is not greater than that ofinside air (Wi). In the event that the ventilation rate for humiditycontrol exceeds that required for temperature control, inside airtemperature could drop below the heating setpoint, thusnecessitating supplemental heating to restore the temperature toits setpoint value.CO2 ControlWhen the greenhouse CO2 level is lower than the ambient CO223level of 340 ppm, vents should be opened to bring the CO2 levelcloser to the ambient level if CO2 enrichment is not made. When highdosage of CO2 is required for enhancing photosynthesis, then ventopenings should be optimized to conserve valuable resources.[3.2.1) Heat BalanceThe heat balance equation enables us to determine the heatingor ventilation requirement of the greenhouse for temperaturecontrol. The heat balance equation can be derived from equation 1.1upon removal of insignificant terms, thusfld sens — — qjf ( 2 . 1)In words, the net amount of heat accumulated in the greenhouseis equal to the difference between heat gains and heat losses. Heattransfered to soil underneath the greenhouse floor is assumed to benegligible; this assumption is justified for a mature crop havingan extensive canopy that can effectively intercept most solarradiation. This assumption also implies minimal nighttime energyflux from the soil to the greenhouse. In this study, net heataccumulation is simulated directly in place of air temperature,which is compatible with the standard way of first solving fortemperature in a differential equation, and then computing net heataccumulation. In equation(2.l), sensible heat gain is defined asthe portion of absorbed solar radiation that has not been utilized24in transpiration for plants to cool themselves during the daytime,and is represented by= a*q801— — (2.2)where a is solar absorptivity of the plant canopy, X is thelatent heat of vaporization(2450 kj/kg), Np is transpiration rate,mp is the mass of plants, ç, is specific heat of plants(4200j/kg.°C) and T is plant(leaf) temperature, t is the time step andis chosen to be one hour in the simulation runs. Solar energyadmitted into the greenhouse, q801, is given by= ‘•* 10 * Af (2.3)where T is the effective transmissivity of greenhouse cover(for glass, usually 0.70 to O.75)[%), 10 is the outside solarradiation [Win2] and Af is the greenhouse floor area [m2].Effective transmissivity is defined as the amount of solarradiation received on an inside horizontal surface (at plant canopylevel) as a percent of that falling on an outside horizontalsurface of the same area. The effective transmissivity ofgreenhouse cover is different from its transmittance at the glazinglevel. The latter shows mainly the effects of the opticalproperties of glazing material, sky clearness and solar angle ofincidence. However, the former is further influenced by the25greenhouse geometric configuration and internal structures. Lau andStaley (1989) have made an in depth study of this parameter fordifferent types of greenhouse; results indicated that r varies from0.65 to 0.75 for most climate conditions.Transpiration provides both the motive force for water uptakeby the roots and a mechanism for cooling the leaf. Although thetranspiration rate of a greenhouse crop is governed by stomatalresistance (degree of closure of the stomata) which in turn dependson the environmental factors of light intensity, leaf temperature,ambient humidity or vapor pressure deficit, CO2 level, as well asleaf water potential, stomatal opening is most sensitive to lightor solar radiation. Literature review (Morris et al., 1956; Bakkerand van de Vooren, 1984; Stanghellini et al., 1992) indicated astrong correlation between solar radiation and transpiration forwell—watered greenhouse crops. For instance, Morris et al., (1957)reported that the ratio of transpiration (Mr) to solar radiation(I=r*I0) was found to vary with plant height. At a plant height of0.25 m, this ratio was 0.45 and it incresed from 0.60 at a plantheight of 0.70 m to 0.80 when the plants are 1.55 m tall. Beyondthis height, the ratio became constant.De Graaf and van den Ende (1981) observed that for smalltomato plants in winter, about 5% of the solar radiation wasconvered into latent heat via transpiration. For full—grown crops,this percentage was 37%. As solar intensity increased,26transpiration increased from 0.2 mm/day to 3-5 mm/day. Once thetomato plants had reached a height of 1.7 in at the end of 2 months,a further increase in height was not accompanied by increasedtranspiration, which agrees with results obtained by Morris et al.,(1957). Regression equations were obtained as follows:= 0.l6*0.00408*I + 0.30 h = 0.8 in= O•25*O•OO48Ipd + 0.50 h = 1.3 inlvii, = O.37*O.OO4O8*I + 0.61 h 1.7 in (2.4)where Mi, and‘pd are expressed in [rnm/d], and h is plantheight (i.e. stage of plant growth),‘pd had been converted fromJ/cm2.d to equivalent amount of latent heat using a conversionfactor of 0.00408. For instance, a full—grown tomato crop with aheight of 1.7 in will have a Mi, of 3.6 mm/d when‘pd is 2000 J/cm2.d.Therefore, the latent heat of vaporization required to convertliquid water to vapor form in order for transpiration to occur canbe a substantial part of the energy flux entering the greenhouse.Once daily transpiration is known, hourly transpiration rate isassumed to be proportional to the hourly solar radiation as apercentage of 1pd•More sophisticated transpiration models have been proposed byStanghellini and van Meurs (1992), which take into account themeasured or estimated leaf temperature, stomatal resistance,boundary layer resistance and leaf area index. Boundary layer27resistance (also called external resistance) accounts for sensibleheat transfer while stomatal resistance (also called internalresistance) represents latent heat flux due to transpiration. Heating requirementWhenever heat gains are less than heat losses (eqn. 2.1),becomes negative and an equivalent amount of heat shall be suppliedto the greenhouse to maintain the setpoint temperature. Thenighttime heating demand of a greenhouse, q, is used to size theboiler, and is computed as (ASAE, 1992) :q (2 . 5)since no solar heat input is available. The conduction heattransfer may be positive or negative depending on the relativemagnitudes of the inside (T1) and outside (T0) temperatures.= U * * (T1 — T0) (2.6)where,U: overall heat transfer coefficient [w/m2.°C)A5: surface area of the greenhouse [1112)T: inside greenhouse temperature [°C)T0: outside air temperature [°C)28Greenhouse heating systems are designed to maintain a giveninside temperature at a given outside temperature. The formerdepends on the crop grown and the latter depends on the location.The overall heat transfer coefficient (U—value) is usuallymade up of three components, the inside convective heat transfercoefficient, the conductance of the glazing material and theoutside convective heat transfer coefficient. Unlike buildingswhere the materials themselves contribute about 75% to 90% of thethermal resistance, greenhouse covers are thin so that thesurface/air interfaces and thus the convective heat transfercoefficients become the dominant factors for evaluating theU—value. Most of the time, mixed (forced and free) convection isthe prevailing mode on the outside of the greenhouse cover due inpart to the wind effect whereas free convection dominates the heattransfer mode at the inside surface. There are wide discrepanciesamong research findings (Takakura et al., 1985), some of which aredefinitely out of range, despite the dependence of these values onthe specific site and the greenhouse structure used in thedifferent studies. Papadakis et al (1992) have reviewed a numberof studies that pertained to this aspect, and recommendedcorrelations for these coefficients.Preliminary calculations of daily energy consumption asdemonstrated in Fig. 3.1 showed that the correlations recommended29by Papadakis et al., (1992) have not necessarily given rise to moreaccurate predictions of daily energy use than the results obtainedby adapting the standard U-values (ASAE, 1992). Hence, the standardU—values will, therefore, be used for all steady—state simulationsin this study.Infiltration is natural air movement due to leakage throughcracks or other small openings in the greenhouse structure.Therefore infiltration heat loss is always present regardless ofwhether or not ventilation is taking place. The following equationrepresents infiltration heat loss= 0.5 * V * N * (T1 — T0) (2.7)where, V : volume of the greenhouse [xn3)N : natural infiltration air exchange per hour [1/h)T1 : inside greenhouse temperature [°C)T0 : outside air temperature [°C)* N varies from 0.75/hr for a new Venlo—structure to3.0/hr for wooden frame or old greenhouse. Ventilation requirementAgain, referring to the heat balance equation (eqn. 2.1),whenever q is greater than zero, excess heat needs to be removedfrom the greenhouse by ventilation if the outside temperature is30less than the desired inside temperature, and if wind conditionspermit. The conventional control algorithm for natural ventilationof greenhouses with ridge ventilators is capable of minimizing thespatial distribution of temperature, limiting the frequency ofventilator operations in order to reduce wear and tear on themechanisms, and protecting ventilators from strong winds. However,no particular attention is paid to the conservation of resourcessuch as energy and CO2.The ventilation rate will be determined by the temperaturecontrol and the humidity control. Ventilation rate for temperaturecontrol (Q) is given byQ = /(p * cp * (T — T0)) (2.8)where, : net heat accumulation [W)p : air density [kg/m3]c, : specific heat capacity [J/kg. °C)T1 : greenhouse air (ventilation setpoint) temperature1°C)T0 : outside air temperature [°C)Q : ventilation rate for temperature control [m3/s)The number of air changes per hour, N, will then be calculatedfrom :31= Q * 3600/V . (2.9)where V is greenhouse volume [m3].This computed value of N will be compared to the nuiiber of airchanges involved in ventilation for humidity control.[3.2.2) Mass BalanceThe mass balance enables us to determine the ventilationrequirement for humidity control and to determine the amount of CO2needed to enrich the greenhouse atmosphere to desirable level.[] Mass Balance for MoistureVentilation for humidity control necessitates a mass balanceto be written about the moisture regime of the greenhouse. Equatingthe net moisture accumulation rate to ventilation rate will lead tothe following equation:Mfld =N — Md (2 . 10)where M is net moisture accumulation before ventilation [kg/s),is transpiration rate [kg/s), and M is moisture condensationrate [kg/s]. Similar to the heat balance, moisture accumulation is32simulated directly in place of air moisture content, as used instandard transient—state equations.In words, moisture accumulation before ventilation is thenet result of moisture production via crop transpiration andcondensation on the glass cover or leaves. Good greenhousemanagement will maintain an appropriate humidity level so as toavoid condensation on the leaves. Also, the steady—state modelassumes that the glass cover and the greenhouse air are atequilibrium, so that condensation on the cover is ignored. In thisstudy, computed values of crop transpiration rate (Mr) is used inplace of M in the moisture balance.Ventilation rate for humidity control is expressed asQh = !%/( p * (W1 — W0)) (2.11)where, M is transpiration rate [kg/s], W1 is inside greenhouse airmoisture content or humidity ratio [kg water/kg dry air), W0 isoutside air moisture content or humidity ratio [kg/kg), and Qh isventilatin rate for humidity control [m3/s).Similar to the case of ventilation for temperature control,the number of air changes per hour, Nh, is calculated asNb Qb * 3 6 0 0 / Vw34[ Mass Balance for Carbon Dioxide.The mass balance for CO2 involves CO2 input(gain), CO2 lossesand change of CO2 over time(one hour). CO2 losses arise from itsdepletion due to photosynthetic consumption and ventilation(including infiltration) loss. In general, filtered flue gases ofthe central hot water heating system are used for CO2 enrichment andtherefore CO2 supply is directly linked to energy supply (van Berkel,1986). This is also the method used at the Hazelmere Greenhouses.Equating the rate of change of CO2 with net accumulation(ordepletion) of CO2, we have the following equation:p *3*C./t = C — Cd (2.13)Cd = C ± (2.14)where C5 is CO2 supply(kg/ha.h), C is CO2 loss(or gain) due toventilation and infiltration (kg/ha.h), and C is CO2 consumptiondue to net photosynthsis(kg/ha.h), p is CO2 density(kg/m3), V isgreenhouse voluine(m3) and C1 is greenhouse CO2 concentration(ppm).First, let us look at CO2 demand. For CO2 consumption due tophotosynthesis, the classic model presented by Acock et al. (1978)and modified by Jones et al. (1991a) to account for the influenceof temperature is used, as it applies to the tomato crop during allstages of growth. Thus35Cpn=(PgR) * . (2.15)where,.f(T)*r*C. z*K*I+(1—m)*r*C.*f(T)1*ln 1K *K*I*eKL+(1-m)*t*Cf(T)(2.16)where, Pg : gross photosyntheric rate [mg/m2.sJR : Respiration rate [mg/m2.s)r : leaf conductance to CO2 transfer [mis)C1 : inside CO2 concentration [mg/rn3)K : canopy extinction coefficient [dimensionless)a : leaf light utilization efficiency [mg C02/j)I : PAR at top of canopy(= r*10*O.45) [w/m2]in : leaf transmission coefficient(usually 0.10)L : leaf area index [in2 leaves/rn2 floor area)f(T)=1_( TmajTT(2.17)36, is The temperature at which Pg is maximum, i. ewhen f(T)=1.O and T is The temperature below which f(T) and thusphotosynthesis is zero. Respiration is assumed to be 10% of grossphotosynthesis.Two scenarios are considered for the C term, which isexpressed as= N8*p*V* (C— C0) / Af (2. 18)where C0 is ambient CO2 concentration and N8 is ventilationsupply rate.The first scenario applies when CO2 is depleted below theoutside (ambient) 340 ppm level and is to be replenished byventilation to let inside air mix with outside air content. ThusC becomes negative and is effectively added to the CO2 supply.The minimum number of air changes per hour for CO2replenishment will be computed as* 3600/V (2.19)whereP*A‘ (C0—C1)*p(2.20)37This calculated value of the ventilation rate can then becompared with ventilation rates estimated by equations (2.9) and(2.12) in order to arrive at a ventilation rate that satisfied allthe requirements for temperature control, humidity control and CO2control.All the computed N-values shall be verified with the actual(supply) ventilation rate due to roof vent openings, as given bya regression equation that related wind speed and vent openingsto ventilation rate (Bot,1983),Q8 = a * Af * (7+1) V exp (—8.42*1O * (‘j+I))(2.21)where Q is the ventilation rate [m3/s), is ventilatoropening [%), I is infiltration expressed in equivalent units ofventilator opening [%], and v,, is the wind speed [m/s).Number of air changes per hour due to ventilation supply isgiven byN8 = Q8 * 3600/V(2.22)The second scenario pertains to CO2 enrichment beyond the38ambient 340 ppm level. Ventilation for temperature control orhumidity control will become a sink component of the mass balancefor CO2. Hence C becomes positive and is added to photosyntheticconsumption as CO2 demand.Finally, we consider CO2 supply. For carbon dioxide enrichmentusing flue gases, CO2 supply rate may be estimated from the heatsupply rate.Heat supply, qf[w), is computed from heat transfer equationsfor convection and radiation, thusqf = (h + hcf + hr)*Apw*(Tpw — T) (2.23)where h, hCf and hr are heat transfer coefficents due tonatural convection, forced convection and radiation, respectively[W/m2. °C), A, is total pipe surface area[m2) and is pipetemperature[°C), and hCf are obtained from empiricalcorrelations (Holman, 1991), emissivity of the pipe material is0.95.CO2 supply in [kg/ha.hJ is calculated from the stoichiometricrelation between natural gas(CH4) combustion and CO2 release, thus,(2.24)39C—___________S 16*38IifIt should be noted that heat supply to the greenhouse did notnecessarily come directly from the boiler; residual pipe heat maybe used for heating over a continuous period. Supply of CO2 can onlybe realized if heat is released from the boiler at a particularhour. Preliminary inspection of pipe temperature data indicatedthat heat release from the boiler was highly correlated to the riseof pipe temperature over the previous period. On the computersimulations, the quantity of CO2 supply will be calculated if thiscondition is satisfied. In the summer heat requirement is minimalwhile CO2 demand can be substantial, the hot water from the boilercan be diverted to a water storage tank for subsequent nighttimeuse. The more expensive way of CO2 supplementation via liquid CO2supply is not considered in this thesis.40SECTION 4. RESULTS AND DISCUSSIONFour days of varied outside climate conditions as depicted inFigs. 4.la to 4.4a were selected from the 1991 data and used in thesimulation runs. The climate factors considered were solarintensity and temperature. Measured inside climate conditions areillustrated in Figs. 4.lb to 4.4b. Results are presented withregard to heating requirement, ventilation requirement, as well asCO2 enrichment. The general behavior of the mathematical model willbe verified against the actual data.4.1. Heating RequirementFigs. 4.lc to Fig4.4c show the heating requirements of thefour cases.Case 1 (high solar radiation and high outside temperature):Diurnal outdoor temperatures varied from 8°C at night to 21°Cduring the daytime, while solar radiation follows a smooth pattern,peaking at 900 W/m2 on this summer day. The trend and magnitude ofthe inside temperature indicated that daytime temperature setpointsare light-dependent. As the heating setpoint temperature waschanged from the nighttime value of 19°C to its daytime value of22°C between 5 a.m. and 8 a.m., the rate of increase in temperaturewas 1.5°C/h, which fell within the recommended range of 1.0 to 1.5°C41per hour in order to allow the plant to adjust its temperaturegradually to the greenhouse temperature thereby avoidingcondensation on the leaves and fruits. Ventilation setpointtemperature increased from 22°C to 27°C when solar intensity wasraised from 240 W/m2 to 900 W/m2. This phenomenon also conformed toconventional greenhouse climate control strategy.Comparison is made between the calculated values of q withother researchers’ findings. With reference to egn. (2.2), g isa function of solar energy entering the greenhouse as well as croptranspiration. Discounting the amount of solar energy used fortranspiration and stored by the plant thermal mass, the remainingfraction of solar radiation that contributes to sensible heating ofthe greenhouse (computed as q8/q,1) was found to be 0.38±0.02 ascompared to values of 0.25 reported by Bailey and Seginer (1988)and 0.40 reported by Critten (1991). In other words, only 40% ofadmitted solar energy was retained as sensible heat in thegreenhouse.Heating demand, q , was calculated on an hourly basis as thedifference between sensible heat gain and sensible heat loss,nevertheless, the predicted q can only be verified with an actualenergy consumption record on a daily basis. The greenhousemanagement record indicated that total daily energy consumptionamounted to 146 GJ for both the tomato greenhouse range (2.54 ha)and the pepper greenhouse range (1.83 ha). Since the two greenhouse42ranges are identical in construction, the actual energy consumptionfor the tomato greenhouse will be 85 GJ (58% of 146 GJ); thesimulation model predicted a heating demand of 95 GJ fortemperature control, and a heating supply of 95 GJ based onconvective and radiative heat transfer from the hot water pipes tothe greenhouse air. Simulation results therefore differed from theactual data by 12%. On this day, the ventilation rate fortemperature control consistently exceeded that required forhumidity control, hence no supplemental heating was necessaryduring the daytime. Energy consumption was therefore attributedlargely to nighttime heating requirements, as is also evidencedfrom the measured pipe water temperature of less than 45°C duringthe daytime.Case 2 (high solar radiation and low outside temperature)This day is characterized by more diffuse sunlight whencompared to Case #1, although solar radiation climbed to a similarmaximum value of 850 W/m2 in the early afternoon. The greenhouserequired some heating in the morning hours. Again, pipe watertemperature was below 45 °C during the day. The outside airtemperature was 3 to 6 °C less than that encountered in Case #1,causing greater heat loss to the surroundings; the percentage ofadmitted solar energy retained as sensible heat was smaller(qsens/qsol = 0.22—0.30) accordingly. There was a 14% differencebetween the calculated heating demand of 96 GJ versus the actual43energy consumption of 112 GJ on this day, while a prediction of 116GJ based on heating supply equations was more accurate.Case 3 (low solar radiation and high outside temperature)The diurnal outside temperature fluctuated by less than 20%,whereas the inside air temperature followed a typical pattern of23°C day/16°C night temperature settings. For this day with lowsolar energy input, the sensible heat gain by air was reduced tonegative values, the heat balance of the greenhouse is thusgoverned by the greater thermal gradient between daytime indoor andoutdoor temperature, eventually leading to a higher heatingrequirement of the greenhouse during the daytime hours than duringthe nighttime.The simulated and actual energy consumption data differ by35%. The predicted value derived from the demand—side equations orsupply-side equations alike was about 110 GJ, while actual dailyenergy consumption was 167 GJ. The large discrepancy is likely dueto the excessive heat loss to the outside through wide ventilatoropenings (more than 60% leeward-side) at night, as shown in Table4.3, which is not accounted for in the heat demand equations. Thehigh outdoor temperature together with low wind speed means thetemperature of the glass is also relatively high, so that littlemoisture can condense out. The plants are now fully matured andcontinued to transpire at night, delivering some 10-20% of the44daily total transpiration capacity. As moisture accumulated in thegreenhouse and could not be removed by condensation, it wasnecessary to have adequate ventilation to maintain the insiderelative humidity level below ±90%, resulting in additional heatloss.Case 4 (low solar radiation and low outside temperature)The simulated heating demand is 236 GJ, and is in goodagreemnent (within 10%) with the actual energy consumption recordof 215 GJ, although the predicted heating supply of 173 GJ is offby 20%. This day as characterized by low solar energy input andlarge daytime heat loss to the ambient naturally implied thatenergy consumption would be the greatest of the four casesinvestigated; the results of the mathematical model accuratelyreflected this point.4.2 Ventilation RequirementThe ventilation requirement of each of the four cases isillustrated in Figs. 4.ld to 4.4d. Simulation results are presentedin terms of the number of air changes per hour, as related toventilation for temperature control, humidity control and CO2replenishment.The ventilation rates were computed from the heat and mass45balance equations, on the basis of the necessity to remove excesssolar heat (net heat accumulation) or excess moisture in thegreenhouse. Minimum ventilation rate required to restore the CO2level back to 340 ppm is also calculated when CO2 is depleted belowthis ambient level. The actual or supply ventilation rate was nextcomputed and all ventilation rates were converted to the number ofair changes per hour for comparison purposes.Case 1 (high solar radiation and high outside temperature):It was suggested that if a sunny day with high temperature isexpected, vents should be opened wide early in the morning, thegreenhouse temperature will then tend not to rise so much duringthe mid—day. Since a cooler plant transpires less than a warm one,a larger vent opening therefore would not necessarily lead to anincrease in transpiration. The additional venting is warranted evenif it means CO2 level cannot be maintained at an optimum level forphotosynthesis, as excessive plant temperatures are moredetrimental to plant growth than a temporary somewhat lower CO2level.Examination of the greenhouse climate conditions on this dayrevealed that the leeward vents were opened 20—30% in the morning.Carbon dioxide enrichment beyond 340 ppm was not apparent exceptfor the early morning hours when the boiler was activated toelevate the temperature from the nighttime setpoint to the daytime46setpoint. If the vents were opened wider, more CO2 would have beenlost through ventilation. In the middle portion of the day, COlevel was depleted considerably below 340 ppm; at one point, it wasnear the lower limit of 50-100 ppm, the CO2 compensation point. Thisis the moment when CO2 enrichment is most beneficial, thus, theboiler should be turned on in order to utilize the CO2 from the fluegases. Although the temperature data showed that no heating isneeded during the day, the hot water can be diverted to a waterstorage tank for later use.Ventilation rate for temperature control steadily increasedfrom 4.3/h to 27.9/h between 0900 and 1700 hours, whereasventilation rate for humidity control ranged from 6.5/h to 9.7/hduring the same time period. These ventilation rates fall withinthe range of values for average—sized greenhouses, of 0.00036 to0.04 m3/m2.s or 0.3 to 40 air changes per hour (Critten, 1991;Whittle and Lawrence, 1960). Upon checking with the actualventilation supply rate, it is seen that the ventilation strategyhad been governed by humidity control. Since vents were not openedadequately for temperature control, roof sprinklers have beeneffectively used on this hot summer dayCase 2 (high solar radiation and low outside temperature)The number of air changes per hour as plotted in Fig. 4.2dindicate that the computed ventilation rates for temperature47control and humidity control are in good agreement with actualventilation rate. In the morning, ventilators are opened to removeexcessive moisture, resulting in humidity levels below 80%. In theafternoon, ventilation is directed more towards temperaturecontrol, as humidity is allowed to build up somewhat. Ventilationrequirement for this day is not high, as all N—values are found tobe below 10 air changes per hour.Case 3 (low solar radiation and high outside temperature)Solar energy is the primary driving force behind temperaturerise. On this day with low solar intensity, ventilation demand fortemperature control is nil, rather, the greenhouse needs heatingfor the entire 24—hour period. However, ventilators were opened forhumidity control. In the mathematical model, transpiration occursonly during the day, resulting in no vent openings at nighttime.This assumption is in contradiction to actual data which showconsiderable nighttime vent openings. Nevertheless, predicteddaytime ventilation rate agrees reasonably well with actualventilation rate, except for 1500 hour when predicted Nh of 18.7/his more than doubles the actual N8 of 8.0/h.Case 4 (low solar radiation and low outside temperature)Vents were opened on this day for the sole purpose of humiditycontrol. The predicted ventilation rate for humidity control48consistently exceeds the actual ventilation supply rate; largediscrepancies exist during the daytime hours. These findings tendto reflect another shortcoming of the mathematical model fortranspiration, in that transpiration is correlated only with solarradiation, while other factors such as vapor pressure deficit andCO2 concentration are ignored. On this day, carbon dioxideenrichment is well executed, and it is possible that stomates areclosed somewhat under high ambient CO2 concentration, thus reducingtranspiration.494.3 Carbon Dioxide RequirementAs carbon dioxide is supplied from the flue gases of thecentral hot water heating system, it can be expected that CO2enrichment is possible only when the burner is switched on to meetthe heating demand of the greenhouse. Measured CO2 levels in eachof the four cases will be inspected to verify this criteria. CO2loss (photosynthetic consumption and/or ventilation loss) will bepresented along with CO2 gain (CO2 supply via burner flue gases) inFigs. 4.le to 4.4e for the four cases.Case 1 (high solar radiation and high outside temperature):This day with abundant solar radiation resulted in zeroheating demand during the day hours. The burner was therefore offunder these circumstances although the pipes were maintained at atemperature of ±40°C for humidity control most of the time. As aresult, CO2 levels were depleted below 340 ppm for an extendedperiod. Even though vents were opened to 50%, the amount of ambientCO2 introduced into the greenhouse apparently cannot satisfy thehigh photosynthetic consumption. As seen from Fig. 4.le, CO2 supplywas consistent with the trend of CO2 concentration. The maximum CO2level of 1100 ppm observed at dawn (0600 hour) coincided with apeak CO2 supply rate of 180 kg/ha.h.50Case 2 (high solar radiation and low outside temperature)As mentioned earlier, the greenhouse requires some heatingduring the morning hours, but no more heating is needed when solarenergy is seen to increase into the day. CO2 concentration was onlyraised to 830 ppm at 0600 hour, subsequently, it continued to fallbelow 340 ppm as the small amount of heating requirement is met byresidual heat in the pipes. Similar to case #1 then, as the burnerwas not on, no supply of CO2 should be realized. Yet, the computedCO2 supply values (Fig. 4.2e) were irregular and were obviouscontradictory to the measured CO2 concentration profile. Thisabnormality is likely due to the imposed logical condition on CO2supply which is linked with a rise in pipe temperature. Between0800 and 1800 hours, the pipe temperature profile was seen to havesome minor fluctuations of 1 to 2 °C, thus making the logicalcriterion ill-conditioned. Again, the extent of vent openings ofless than 30% could not sustain the CO2 level at 340 ppm during thedaytime hours when the greenhouse environment called forventilation.Case 3 (low solar radiation and high outside temperature)CO2 levels never reached beyond 400 ppm on this day even thoughthe greenhouse required heating most of the time. For instance,heating demand was estimated at 10.4 GJ/h at 0700 hour, but CO2level was only at 294 ppm at this hour. Heat and thus CO2 supply51could not be predicted on the basis of the the measured pipe watertemperatures which were probably erratic. However, inspection ofthe vent opening data could provide a hint of why CO2 levels werethis low. On this day, vents were opened quite wide (usually morethan 60%), leading to a ventilation air exchange rate of 6 to 12/h;the loss of CO2 through ventilators could be greater if the windspeed were high on this day. Photosynthetic consumption wasrelatively small due to low light levels. The possibility that fluegases were dumped rather than used for CO2 enrichment cannot beeliminated for this case.Case 4 (low solar radiation and low outside temperature)The greenhouse consumed 215 GJ of energy as compared to 167 GJfor case #3. Simulated CO2 supply rate is consistent with theobserved CO2 concentrations. In contrast to case #3, CO2 enrichmentwas very effective; evidently, the CO2 regime of the greenhouse washigh during this day, except for the noon hour. A majorcontributing factor is the small vent openings of less than 15%during the daytime so that loss of the enriched CO2 throughventilators was kept to a minimum.4.4 Energy SavingThe actual energy consumption record for the four cases (85,112, 167 and 215 GJ, respectively) did demonstrate a trend of52increased energy use as the outside weather conditions becameincreasingly severe. This section presents the implications of theclimate control actions on energy saving aspects.Case 1 (high solar radiation and high outside temperature):This day is characterized by excess solar input to thegreenhouse even after ventilation demand for humidity control. Thisexcess amount of solar energy was found to be 63 GJ and could bestored for nighttime use. During the daytime, CO2 concentrationswere allowed to deplete substantially below the normal 340 ppmlevel, in order to save energy but at the expense of photosynthesisand thus crop yield. It was estimated using the mass balanceequation for CO2 that 60 GJ of heat would have been required toenrich the greenhouse environment to 800 ppm.Case 2 (high solar radiation and low outside temperature)As discussed previously under the section ‘VentilationRequirement’, the ventilation rate for humidity control was greaterthan the ventilation rate for temperature control, therebynecessitating supplemental heat of 16.8 GJ to maintain the heatingsetpoint temperature. The ventilation rate should be consideredexcessive, as humidity was consistently driven below 85%. Atolerance of humidity level at 90% meant that vent openings couldbe reduced, so that less supplemental heat is required and energy53saving of 10.2 GJ (9% of the daily energy use) could be realized.Carbon dioxide levels on this day were lower than in case #1,even though there were hours with supplemental heating. Furthersimulations suggested that 71 GJ of heat will be required to bringabout a 800 ppm CO2 level in the greenhouse. Again the energy thussaved has to be weighed against potential reduction in crop yield.Case 3 (low solar radiation and high outside temperature)The daytime relative humidity profile (Fig. 4.3b) showed thathumidity levels were around 85% as a result of wide vent openings,ranging from 60% at 0900 hour to 80% at 1400 hour. At the sametime, the greenhouse space required continuous heating throughoutthe day. Yet, CO2 levels were never boosted to beyond 400 ppm dueto these large vent openings. Computations indicated that 28.5 GJof heat could be saved while CO2 concentrations would have beenraised to 650 ppm or more if vent openings had been restricted to20% or below.Case 4 (low solar radiation and low outside temperature)In contrast to case #3, this was a relatively calm day with alower wind speed. As the end of the growing season was approaching,a lot of leaves in the bottom layers had been removed; the croptranspired less and thus the greenhouse required less ventilation54for humidity control. The two factors combined to result in muchsmaller vent openings than case #3. Energy saving was realizedthrough avoiding excessive supply of heat and thus CO2 from theburner to offset the loss of CO2 associated with ventilation.Case1.Date:91252(Jun.18,91)HighSolarHighTemp.TABLE4.1SimulationResultsforCase1vwTinRHinWoWirn/sC%kg/kgkg/kgTwaterC02CppmTimeloutPARininsideIToutRHouthW/rn2W/m2J/cm2.hC%10.0008.8870.<0qfqnet>003/hGJfhGJ/hheatingventopeningswindwardleewardTout/lUqsensqsolqaccpqcdqifMpNtNh%03/h03/h03/h03/hGJ/hkg/smm/hr1/h1/h1.05.500. radiation[W0. solar intensity[J/cm2.h] intensity[W/m2} Insidehumidity[%J0.[%][C] outsidetemperature[C] pipetemperature[C][mis][kg/kgdryair][kg/kgdryair][kg/ha.h][ppm/h][ppm/h] [GJ/h] admittedintogreenhouse[GJ/h][GJ/h}[GJ/hJ0.00.949.[G3/h][GJ/hJ0. ofairchanges[1/h] VentilationSupplyRate[1/hJ0. Temperaturecontrol[1/h] 12,91)SolarTemp.TABLE4.2SimulationResultsforCase2.TimeloutPARininsideIhW/m2W/m2J/cm2.hToutRHoutvwC%rn/sTinRHinWoWiC%kg/kgkg/kgTwaterC02Cppm850.616880.115.9890.216.3870.417.5870.518.5760.419.8670.619.7671.819.7562.120.4592.420.5633.223.1633.124.3673.924.7724.624.9594.524.8724.524.1724.224.1723.223.1823.122.187218.4800.617.2830.316.5860.515.8880.316.285.10.00660.0136.4860.00670.009537.887.60.00680.009850.586.10.00650.010662.383.80.00640.011672.178.70.00530.011370.976.70.00510.011660.075.90.00540.011759.679.90.00500.013650.183.90.00550.016550.387.30.00580.01841.988.60.00630.019636.3850.00730.018635.483.60.00790.019737.283.40.00640.019236.885.90.00770.019838.584.20.00770.018535.384.60.00780.013432.982.90.00880.01349.677.10.00810.012256.878.60.0070.009460.383.90.00690.009661.687.10.00710.0162.984.20.00680.009561.8240.3296.3 300342.9456.1829.8505.7348.6227.3 22517192.392.974.396.374.7 97 94.3114.2183.6198.3225.9261.8300HighLow 100.009.8200.009.5300.009.7400.009.8500.009.56155.14.058.876321.317.0110815452.041.5810.99316106.785.3212.310317107.085.591311414139.7111.7813.712539181.9145.5314.613773260.9208.7115.514844284.9227.8815.615771260.2208.1715.516596201.2160.9215.117533179.9143.9115.118443149.5119.6115.419362122.297.7415.2209732.726.1912.9213110.58.3712.12220.70.5411.42300.0010.72400.0010.2SimulationResultsheatandmassbalancesventopeningswindwardleewardlout/lOqsens%%03/hheatingventingdemanddemandqnet<0qfqnet>.003/hGJJhGJ/hNtNh1/h1/hqsolqaccpqcdqifMp03/h03/hGJ/hGJ/hkg/smm/h03.—C02NcNsCventPnqco2qco2=800Suppy1/h1/hkgfha.hkg/ha.h03/h03/hkg/ha.hNotation: radiation[W0.[Jicm2.h][W/m2}[%]0.00.1150.[%]0.00.1671.[C]0.00.9396. outsidetemperature[C]0.02.9414.[C]2.92.7023.[mis]2.83.4023.[kg/kgdryair]2.12.7025.[kg/kgdryair]1.23.1021. CO2consumptionrate[kg/ha.h]1.45.1024.[ppm/h]1.26.4021.[ppm/h]1.55.5025.[GJ/h]1.03.7019.30.04.776.3qsol:solar heatadmittedintogreenhouse[03/h]1.33.4021.[03/h]1.12.9019.[03/h]1.23.3019.20.04.9106.3qaccp:heataccumulatedbyplants[03/h]0.83.908.90.04.4136.1qnet:heatingorventilationdemand[03/h]0.30.703.30.03.7131.5N:Number ofairchanges[1/h]0.00.300.20.03.6135.8Ns:Actual VentilationSupplyRate[1/h][1/h],91)LowSolarHighTemp.TABLE4.3SimulationResultsforCase3.TimeloutPARininsideIhW/m2W/m2J/cm2.hToutRHoutvwTinRHinWoWiC%ni/sC%kg/kgkglkgTwaterC02Cppm100.0016.8941.918.289.30.01150.011720.0177.9200.0016.5940.418.091.50.01120.011720.0185.6300.0016.6940.817.791.80.01130.011720.0194.3400.0016.6941.217.492.90.01130.011620.0185.9500.0016.5940.517.893.50.01120.012228.6195.3600.0016.4940.819.887.10.0110.012675.0203.2710.30.2716.4941.422.178.20.01100.01375.0293.6882.72.1616.4941.322.477.80.01100.013275.0390.09279.17.2916.3881.722.181.00.01020.013475.0387.0108930.024.0316.9881.,86.2116.9822.020.985.30.00990.013247.5424.22051.71.3515.9883.<0GJ/hkg/smm/hrGJ/hqfqnet>003/hGJIhNtNh1/h1/hheatingventingdemanddemand13.564.800.,81.559.42.7-0.41.9-‘ photosyntheticallyactive radiation[W0. intensity[J!cm2.hJ0. intensity[W/m2][%][%][C][C]0.03.515. pipetemperature[C]0.04.518.[rn/si0.[kg/kgdryair][kg/kgdryair][kg/ha.h][ppm/h]4.911.[ppm/h] [GJ/hJ4. admittedintogreenhouse[GJ/h][GJ/h][GJ/h]0.02.420.[GJ/h] heatingorventilationdemand[GJ/h] ofairchanges[1/h] VentilationSupplyRate[1/h] Temperaturecontrol[1/hi0.,91)LowTempt.LowSolarTPLE4.4SimulationResultsforCase4.TimeloutPARininsideITouthW/m2W/m2J/cm2.hCvwTinrn/sCTwaterC02CppmRHoutRHinWoWi%kg/kgkg/kg100.008.7840.117.784.00.00580.010736.3484200.008.8860.117.485.50.0060.010543.1494300.009.2880.117.587.60.00640.01143.5496400.009.8880.217.387.90.00650.010948.2500500.009.7900.‘ent openingswindwardleeward%qsensqsolqaccpqcdqifMp03/h03/hGJ/h03/hOJ/hkg/sHeatingVentingDemandDemandqnet<0qfqnet>0NtNhmm/hr03/h03/hGJJh1/h1/h05. photosyntheticallyactive radiation[W0. intensity[Jlcm2.h][W1m2J0. Insidehumidity[%j0.[%J0.[C] outsidetemperature[C] pipetemperature[C][mis][kg/kgdryair][kg/kgdryair][kg/ha.h]0.01.311. toventilation[ppm/h]0.01.3149.84.415.18.00.0Pn:Netphotosysntheticrate[ppm/h]0.01.3210.24.717.05.5177.0qsens:sensibleheatgainbyair [GJ/h]0.00.4101. admittedintogreenhouse[GJ/h]0.00.7108.[GJ/h}0.01.0112.[GJIhJ0.01.5113.[GJ/h]0.01.8122. heatingorventilationdemand[GJ/hJ0.01.689. ofairchanges[1/h]0.00.956. VentilationSupplyRate[1/h]0.00.849. Temperaturecontrol[1/h] C I —--Solar/i0,w/m2—a—Windspeed,m/s1Fig.4.la<Case1:OutsideCondition>.020.01750.015o.s C)0.0125S C ci 4-,p.010.0075o.0050.0025Time,h—I-—Temperature,C—*—RelativeHumity,%—>E---MoistureCont.kg/kg±C a Cl) C CtS I- I 0 E D I 0 a S C) F-—.—PipeTemp.C—I-—InsideTemp.C—B—MoistureCont.kg/kg—)E--Transpiration,kg/s—*--InsideR.F-L, %1Fig.4.lb<Case1:InsideCondition>C).‘ C).C a) 4-i C 0 0 a) I D 4-i Cl) 0Time,h-, (‘3 C a) IFig.4.lc<Case1:HeatingRequirement>——q(sol), GJ/h—H---q(sens),GJ/h—a--VentilationDemand——HeatingSupply—IE--HeatingDemandTime,h‘4cJ-c Cl) ci) C) C-c C-) IFig.41d<Case1:Ventilat’nReq’ment>——Temp.Control—I-—HumidityControl—*--C02Replenishm’t—B--Act’lVent’nSupplyTime,hSFig.4.1e<Case1:002Requirement>200-1200180-________________________________________________-1000Cl)140--8000C)160iI__1120-C-I-s12)C600100-C 0080-C’] 0C__________________________________________-400o a)___________________________U)40-.920-________S/\0-SI04812162024Time,h——C02Conc.,ppm—H-—Pn,kg/ha.h—1E—Cvent,kg/ha.h—6—Cs,kg/ha.hC I ——Solar/i0, w/m2 —B— Windspeed, rn/s—I-—OutsideTemp.C——MoistureCont,kg/kg—fE--OutsideR.H,%D)--C a) C 0 C-) ci) D Cl) 01Fig.4.2a<Case2:OutsideCondition>Time,hC 0 0 U) C I 0 S D I 0 a S ci) I———PipeTemp.C—H-—InsideTemp.C—a—MoistureCont.kg/kg—>E—Transpiration,kg/s—*--InsideR.H.%Fig.4.2b<Case2:InsideCondition>75 5c250.007512Time,h0 0) ci) IFig.4.2c<Case2:HeatingRequirement>—.--q(sol), GJ/h—H—-q(sens),GJ/h—a--Vent’nDemand,GJ/h—>E—HeatingSupply,GJ/h—E--HeatingDemand,GJ/hTime,hr C 0 C a) >1Fig.4.2d<Case2:Vent’nRequirement>—.—Temp.Control,1/h—I--—Humid.Control,1/h—*—C02Replenishm’t—El—Act’lVent’nSupplyTime,h-xFig.4.2e<Case2:C02Requirement>140-1000I I9001208002 a-a-c—-700 0C)________________________________________________600-____________________________4-,80C a)05000 C4-,__________________060-C)>-400cjC)100•J13000L._______040-ci___C’)___.920--200 -10004812162024Time,h——C02Conc. ppm—±—Pn, kg/ha.h---*---Cvent,kg/ha.h—B--Cs, kg/ha.hC)nr-Q4J C ‘3) C C C) ‘3)0.0075—a—Solar/i0,w/m2—B--Windspeed, rn/s—I-—OutsideTemp.C—?<--MoistureCont.kg/kg—-?iE—OutsideR.H., %1’Fig.4.3a<Case3:OutsideCondition>-C C I75Time,h—a t0 0 U) C (ts I- F 0 E I 0 ci E F-——PipeTemp.C—I---InsideTemp.C—8—Moisturecont.kg/kg—>E—Transpiration,kg/s—fE--InsideR.H., %1Fig.4.3b<Case3:InsideCondition>0)-I. C C) C 0 0 C) :3 4-’ C’) 0Time,h--C 0 c3)C ci) I—.--q(sol), GJ/h—9—VentilationDemand—I-—-q(sens),GJ/h——HeatingSupply—*—Heat’gDemand,GJ/hFig.4.3c<Case3:HeatingRequirement>Time,h—-c a) r) C-C 0 IFig.4.3d<Case3:Vent’nRequirement>——Temp.Control,1/h—±--Humid.Control,1/h—*--C02replenishment—6—Act’Ivent’nSupplyTime,h-Fig.4.3e<Case3:C02Requirement>80--70--400E6O-a 0300a 1 CC-)a)______________________________________________________040-C 8C ci)I.,r2OOc’._____\jwoc!30------i0 ci) C’)___________/\10010-I,I11JijL0- 04812162024Time,h—.—C02Conc.,ppm—±--Pn.,kg/ha.h—E---Cvent,kg/ha.h—B—Cs,kg/ha.h0 C I 0 t3 S D I 0 a S ci) I 0 1 Ct 0 Co——Solar Radiat’n,w/m2—I—OutsideTemp., C—a—Windspeed,mis—>E—MoistureCont.kgikg-*--OutsideR.H., %C)C)4-. C ci) 4- C 0 C) 0) I D 4-. C’) 011 1Fig.4.4a<Case4:OutsideCondition>12Time,h-S-$-n(pcrAC)C,) CDDC’)CDC) 000:3VTemp.orHumidityorTranspiration1! D0CD-‘—I DCD 0C)LiH3CD-c (!3 0) C 4-’ a) I—e—q(sol),GJ/h—±—q(sens),GJ/h—8---Vent’nDemand,GJ/h—?E—HeatingSuppty,GJ/h—*—HeatingDemand,GJ/hFig.4.4c<Case4:HeatingRequirement>Time,hFig.4.4d<Case4:Vent’nRequirement>1OCl) a) C Ct5.C C-)•-•--O—-H—-iH-R—i—iII—i r——o48121620Time,h——Temp.Control,1/h—I-—HumidityCont’l,l/h—IE—C02Replenishm’t—Eb-Act’lVent’nSupplyFig.4.4e<Case4:C02Requirement>220--1800200--1600160--1400E-c____________________________________a140--1200ct160-a 0 C_____1\\1000________________________________________________a)o120-C.)I-.0 C)•100-G)J/‘./ \80-___6000___c60—.mC,)40-IHcmm20-/400__________________________________________-2000-rnmmcImJmL04812224Time,h——C02Conc.,ppm-H--—Pn.kg/ha.h--*--Cvent,kg/ha.h—B---Cs,kg/ha.h84SECTION 5. CONCLUSIONS ND RECOMMENDATIONS5.1 ConclusionsThe mathematical model which comprised of heat and massbalances for the greenhouse thermal environment and cropphotosynthesis has yielded reasonably accurate simulation resultswhen compared to observed values. This model could be adopted asguidelines for an integrated climate control algorithm for energyconservation purposes.Heating requirement was predicted to within 10—14% for threetypical cases of weather conditions, but deviated by 35% fromactual energy consumption data under one situation (case #3).Predicted ventilation demand also followed closely the trend ofobserved vent openings data, except for case #4 when the modeloverpredicted ventilation rates for humidity control. Possiblecauses for the discrepancies between simulated and measured datawere explored, and the analyses have provided guidelines forimprovement in climate control actions. The model was able topredict carbon dioxide input from heating supply computations; ingeneral, the predicted supply of CO2 is compatible with the measuredCO2 concentration profiles, though predictions under thecircumstances of case #2 weather conditions were not realisticcompared to actual data.85Energy saving is achieved in different manners for the fourcases. In case #1, excess solar energy is available afterventilation and can be stored for nighttime use, thus saving fossilfuels. Ventilation requirements for temperature control andhumidity control are about the same for case #2 conditions, andenergy saving is realized if supplemental heat can be minimized byadopting a higher tolerance level for humidity. The greenhouseneeds heating throughout the daytime hours, yet CO2 depletion issevere due to excessive ventilation; simulation results indicatedthat energy saving is possible if vent openings were restricted to20% or below. For case #4, the heating, ventilation and CO2enrichment processes are well integrated; the model predicted noadditional energy saving.5 • 2 RecommendationsThe following recommendations are made for furtherinvestigations, with an aim to finetune and validate the computermodel before it can be adopted in climate control computers forimproved climate control actions.Plant tissue temperatures should be routinely measured alongwith greenhouse temperature so as to generate more precisepredictions for sensible heat gain and hence ventilation rate fortemperature control. The plant temperature can also be used in the86temperature function of the photosynthesis submodel.Transpiration rate should be measured, and used to calibratean improved transpiration submodel, which would account forenvironmental factors other than solar radiation alone. This willimprove predictions of ventilation rate for humidity control.Carbon dioxide input should be monitored with a flow meterretrofitted to the supply line, so that simulation results can beverified directly with the measured data.Finally, simulations shall be extended to include costs andbenefits assessment in order to search for an optimal CO2 controlstrategy with regard to energy saving versus crop yield. Thestrategy thus developed shall then be integrated into the heatingand ventilation control algorithms.87REFERENCESAcock, B., D.A. Charles-Edwards, D.J. Fitter, D.W. Hand, L.J.Ludwig, J. Warren-Wilson and A.C. Withers. 1978. The contributionof leaves from different levels within a tomato crop to canopy netphotosynthesis: an experimental examination of two canopy models.3. Exp. Bot. 29(111): 815—827.Aikiuan, D.P. and A.J. F. Picken. 1989. Wind-related temperaturesetting in glasshouses. J. Hort. Sci. 64(6): 649—654.Aibright, L.D., I. Seginer, L.S. Marsh and A. Oko. 1985. InSitu thermal calibration of unventilated greenhouses. J. Agric.Engng. Res. 31: 265—281.Aldrich,R.A.,Downs,R.S., 1983: The Effect of Environment onPlant Growth, in Ventilation of Agricultural Structures, Editedby M.A.Hellickson, ASAE Monograph #6, St.Joseph, Michigan, p.217Alscher, G. and H. Krug. 1989. On-line control of C02enricftnent in protected cultivation. Acta Hortic. 248: 321-327.Arinze,E.A.., G.J. Schoenau and R.W. Besant. 1984: A DynamicPerformance Simulation Model of an Energy Conserving Greenhousewith Thermal Storage. Trans. ASAE, 27(2): pp. 508—519ASHRAE, 1980: American Society of Heating, Refrigeration andAir-Conditioning Engineers Applications Handbook, Chapter 21.7Bailey, B.J. 1985. Microclimate, physical processes andgreenhouse technology. Acta Hort. 174: 35-42.Bailey, B.J. and I. Seginer. 1989. Optimum control ofgreenhouse heating. Acta Hortic. 245: 512-518.Bailey, J.C. 1985. A C02 control algorithm based on simulatedphotosynthesis and ventilation rate. Acta Hort. 174: 387-392.Bakker,J.C. 1985: C02 control algorithms based on simulatedphotosynthesis and ventilation rate. Acta Hortic. 174: pp.387-392Bakker, J.C. 1988. The effects of humidity on growth andproduction of glasshouse cucumbers, tomatoes and sweet peppers.Acta Hort. 229: 159—163.Bakker, J.C. and 3. van de Vooren. 1984. Water vaportransport from a greenhouse by ventilation. I: Effects ofclimate. Acta Hort. 148: 535—542.88Bauerle,W.L. , Short,T.H., 1978: Energy Conservation and PlantGrowth by Using Double Plastic on Glass Greenhouses, ACTA Hort.,#76,p.3O5Bello, R.L. 1982. Evapotranspiration in Greenhouses.Ph.D. Thesis. Geography Dept., McMaster University.Berkel, N. van. 1986. Co2 enrichment in the Netherlands. In:H.Z. Enoch and B.A. Kimball (eds.). Carbon dioxide enriclunent ofgreenhouse crops. Vol. 1. Status and CO2 sources. CRC Press Inc.,Boca Raton, FL. pp. 17-33.Blom, T.J., W.A. Strayer and F.J. Ingratta. 1984. Carbondioxide in Greenhouses. Horticultural Research Institute of OntarioFactsheet.4 pp.Bot, G.P.A. 1983: Greenhouse climate; from physical processesto a dynamic model. Ph.D. dissertation. Agric. Univ. wageningen,the NetherlandsBronson,R., 1983: Computer Simulation, Byte, March, p.95Businger,J.A.,1963: The Greenhouse Climate, in physics of thePlant Environment, 2nd Edition, W.R.Van Wijk, North HollandPublishing Co., Amsterdam, p.277Calvert, A. 1964. The effects of air temperature on growth ofyoung tomato plants in natural light conditions. J. Hort. Sci. 39:194—211.Challa, H. and A.H.C.M. Schapendonk. 1986. Dynamicoptimalization of C02 concentration in relation to climatecontrol in greenhouses. In: C02 enrichment of greenhouse crops,Vol I. Status and C02 sources. CRC Press Inc., Boca Raton, FL.Challa, H., G.P.A. Bot, E.M. Nederhoff and N.J. van de Braak.1988. Greenhouse climate control in the Nineties. Acta Hortic. 230:459—470.Challa,H.,Van de Vooren,J., 1980: A strategy for ClimateControl in Greenhouses in Early Winter Production, ACTAHort.,#106,p.l59Critten, D.L. 1991. Optimization of C02concentration in greenhouses: a modelling analysis for the lettucecrop. J. Agric. Eng. Res. 36: 261—271.Curtis, H. and N. Barnes. 1989. Biology.Worth Publ., NewYork.de Koning, A.N.M. 1990. Long-term temperature integration oftomato. Growth and development under alternating temperatureregimes. Scientia Hort. 45: 117—127.Dixon, M.A. 1987: Plant water potential gradients between stem89and fruits of tomato using simultaneous measurements. In; Pro.Int’l. Conf. Measurement of Soil and Plant Water Status. Utah StateUniv. July 6-10Gaastra, P. 1959. Photosynthesis of crop plants as influencedby light, carbon dioxide, temperature, and stomata diffusionresistance. Meded. Landb Hogesch. Wageningen 59(13): 1-68.Gary, C. 1988. A simple carbon balance model simulating theshort—term response of young vegetative tomato plants to light, CO2and temperature. Acta Hort. 229: 245- 250.Garzoli, K.V. and J. Blackwell. 1981. Thermal analysis ofAustralian grenhouses. Acta Hort. 115: 125—131.Gent, P.M. and H.Z. Enoch. 1983. Temperature dependence ofvegetative growth and dark respiration: a mathematical model. PlantPhysiol. 71: 562—567.Gijzen, H. and J.A. ten Cate. 1988. Prediction of the responseof greenhouse crop photosynthesis to environmental factors byintegration of physical and biochemical models. Acta Hort. 229:251—258.Grange, R.I. and D.W. Hand. 1987. A review of the effects ofatmospheric humidity on the growth of horticultural crops. J. Hort.Sci. 62: 125—134.Grange,R.I. ,Hurd,R.G. ,1983: Thermal Screens; EnvironmentalPlant Studies, Scientia Hort., Vol.19,No.3—4, April,p.201Hand, D.W. 1984. Crop responses to winter and summer C02enrichment. Acta Hort. 162: 45-63.Hand, D.W. 1988. Effects of humidity on greenhouse crops. ActaHort. 229: 143—158.Hashimoto, Y. 1980. Computer control of short term plantgrowth by monitoring leaf temperature. Acta Hort. 106: 139—146.Heij, G. and A.H.C.M. Schapendorik. 1984. C02 depletion ingreenhouses. Acta Hort. 148: 351-358.Heij, G. and P.J. de Lint. 1984. Prevailing C02 concentrationsin glasshouses. Acta Hort. 162: 93—99.Hicklenton, P.R. 1988. C02 enrichment in the greenhouse.Timber Press Growers Handbook Series Vol. 2. 58 pp.Horie,T., 1979: A Simulation Model of Cucumber Growth to FormBases for Managing the Plant Environment System, ACTA Hort.,90#87,p.215Houter, G., H. Gijzen, E.M. Nederhoff and P.C.M. Vermeulen.1989. Simulation of CO2 consumption in greenhouses. Acta Hort. 248:315— 320.Horiguchi,I., 1979: The variation of Heating Load Coefficientfor The Greenhouse, ACTA Hort.,#87,p.95Houter, G., H. Gijzen, E.M. Nederhoff and P.C.M. Vermeulen.1989: Simulation of CO2 Consumption in Greenhouse. Acta Hort. 248:pp. 315—320Jones, J.W. 1991. Crop growth, development, and productionmodeling. In: Proc. Sym. Automated Agriculture for the 21stcentury. Chicago, Ii. Dec. 16-17.Jones, J.W., E. Dayan and H. van Kuelen. 1988: Modeling tomatogrowth for greenhouse environment control. Amer. Soc. Agric. Eng.Winter Meeting, Chicago, Illinois.Jones, J.W., E. Dayan, L.H. Allen, H. van Keulen and H.Challa. 1991. A dynamic tomato growth and yield model (TOMGRO).Trans. ASAE 34(2): 663—672.Kimball, B.A. 1973. Simulation of the energy balance of agreenhouse. Agric. Meteorol. 11: 243-260.Kimball, BA. 1986: A modular energy balance program includingsubroutines for greenhouses and other latent heat devices. U.S.Depart. of Agric. Report #ARS-33, pp.360Kimball, B.A. and S.T. Mitchell. 1979. Tomato yields from C02enrichment in unventilated and conventionally ventilatedgreenhouses. J.Amer.Soc.Hort.Sci. 104(4) :515—520.Kozai, T., S. Sase and M. Nara. 1980. A modeling approach togreenhouse ventilation control. Acta Hort. 106: 125-136.Lau,A.K.P, 1988: Development of a Design Procedure forGreenhouse Solar Heating Systems, Ph.D. Thesis, U.B.C.p.77Lacroix, R., R. Kok and L. Gauthier. 1993. Simulation-baseddetermination of greenhouse temperature setpoints. Paper No.93—4043. ASAE/CSAE Meeting, Spokane, WA. June 20—23, 1993.Liebig,H.P., 1981: A Growth Model to Predict Yield andEconomical Figures of The Cucumber Crop, ACTA Hort.,#118,p.165Marsh, L.S. and L.D. Aibright. 1991. Economically optimum daytemperatures for greenhouse hydroponic lettuce production. Part I:91a computer model. Trans ASAE 34(2): 550—556.Mausa, B. 1992: Greenhouse crop specialist, Western greenhousecooperative association. Personal communication.Marsh, L.S. and L.D. Aibright. 1991. Economically optimum daytemperatures for greenhouse hydroponic lettuce production. Part II:Results and simulations. Trans ASAE 34(2): 557—562.Miller, W.B., R.W. Langhans and L.D. Albright. 1985. Plantgrowth under averaged day/night temperatures. Acta Hort. 174:313—320.Monteith, J.L. 1965. Light distribution and photosynthesis infield crops. Ann. Bot. IT.S. 29: 17—37.Monteith, J.L., B. Marshall, R.A. Saffell, D.Clark, J.N.Gallagher, P.J. Gregory, C.K. Ong, G.R. Squire and A. Terry. 1983.Environmental control of a glasshouse suite for crop physiology. J.Exp. Bot. 34: 309—321. (should get this article)Morris, L.G. 1963. Some recent advances in the control ofplant environment in glasshouses. Proc. Sym. Engng. Aspects ofEnvironmental Control for Plant Growth. CSIRO, Melbourne: 62-94.Morris, L.G., F.E. Meals and J.D. Postlethwaite. 1956: TheTranspiration of Glasshouse Crops and its Relationship to theIncoming Solar Radiation, J.Agric. Engng. Res. 1: pp. 111-122Nederhoff, E.M., H. Gizen and J. Vegter. 1989. A dynamicsimulation model for greenhouse cucumber: validation of thesubmodel for photosynthesis. Acta Hort. 248: 255-263.Nilsen, S., K. Hovland, C. Dons and S.P. Sletten. 1983. Effectof C02 enrichment on phtotosynthesis, growth and yield of tomato.Scientia Hort. 20: 1—14.Ohara, G. 1988. Improvement of the heating system control inprotected cultivation. Acta Hort. 229: 527-532.Otten, L., P.G. Muller, H. Tiessen, S. Khosla, F. Rey and H.A.Jackson. 1989. Energy saving hydroponic greenhouse pilot project:energy aspects. Can. Agric. Eng. 31: 147-152.Paez, A., H. Hellmers and B.R. Strain. 1984. Carbon dioxideenrichment and water stress interaction on growth of two tomatocultivars. J. Agric. Sci. Camb. 102: 687—693..Papadakis, G., A. Frangoudakis and S. Kyritsis. 1992. Mixed,forced and free convection heat transfer at the greenhouse cover.J. Agric. Eng. Res. 51(3): 191—206.92Penning de Vries, F.W.T. and H.H. van Laar. 1982. Simulationof growth processes and the model BACROS. In: Simulation of plantgrowth and crop production. F.W.T. Penning de Vries and H.H. vanLaar (eds.). Wageningen, The Netherlands. Chap. 3.3.Ryu, K.H., J.Y. Jin and S.H. Hong. 1993. Online Measurementand Control of Plant Growth. ASAE/CSAE Paper No. 933067.International summer meeting, Spokane, WA. June 20-23, 1993.Sase, S. and M. Nara. 1985. A control algorithm for naturalventilation based on wind tunnel testing.Schapendonk, A.H. and P. Gaastra. 1984. A simulation studyon C02 concentration in protected cultivation. Sci. Hortic.23:217—229.Schapendonk, A.H. and W. van Tilburg. 1984. The CO2 factor inmodeling photosynthesis and growth of greenhouse crops. Acta Hort.162: 83—92.Schiesser,W.E. ,1990: Differential Systems Simulator, Ver.2,Lehigh Univ., Bethlehem, Pa. 18015 U.S.A.Seginer, I., 1981: Economic Greenhouse Temperature, ACTA Hort.,#l15,p.439Seginer, I. and L.D. Albright. 1983. Greenhouse operation forbest aerial environment. Final research report. NARD Project I117—79.Seginer, I., G. Shina, L.D. Aibright and L.S. March. 1991.Optimal temperature setpoints for greenhouse lettuce. J. Agric.Eng. Res. 49: 209—226.Soribe, F.I. and R.B. Curry. 1973. Simulation of lettucegrowth in an air—supported plastic greenhouse. J. Agric. Eng. Res.18: 133—140.Spitters, C.J.T., H. van Keulen and D.W. van Kraalingen. 1988.A simple and universal crop growth simulator: SUCROS87. In:Rabbinge, R., S.A. Ward and H.H. van Laar (eds.). Simulation andsystems management in crop protection. Simulation Monographs No.32. PUDOC, Wageningen, The Netherlands. 420 pp.Stanghellini, C. and W. van Meurs. 1992. Environmental controlof greenhouse crop transpiration. J. Agric. Engng. Res. 51(4):297—311.Stokes,D.A. ,Tinley.G.H. ,l981: Cucumber; Thermal Screen andGrowing Media Investigations, ACTA Hort.,#1l8, p.13593Takakura, T., 1982: Optimization of Crop Production inProtected Cultivation, Proc, XXIst Int’l, Hort. Cong. 2:1048-1058.Takakura, T., K. Jurata and P. Honjo. 1985. Physical modelsand the greenhouse climate. Acta Hort. 174: 97-104.Takakura, T., K. Kurata and T. Honjo. 1985. Physical modelsand the greenhouse climate. Acta Hort. 174: 97-104.Tantau, H.J. 1985. Analysis and synthesis of climate controlalgorithms. Acta Hort. 174: 375—380.Ten Cate, U.A.J. 1985. Advances in greenhouse climate control.Acta Hort. 174: 361-363.van Bavel, C.H.M., T. Takakura and G.P.A. Bot. 1985. Globalcomparison of three greenhouse climate models. Acta Hort. 174:21—33.van Berkel, N. 1975. C02 from gas-fired heating boilers- itsdistribution and exchange rate. Neth. J. Agric. Sci. 23: 202-210.Verhaegh,A.P., 1981: The Influence of Insulation Techniques onCrop Production and Profitability in the Dutch GlasshouseIndustry, ACTA Hort.,#115, p.453Walker,J.N.;Aldrich,R.A.;Short,T.H., 1983: Quantity of AirFlow for Greenhouse Structures, in Hellickson, M.A., Ed.,Ventilation of Agricultural Structures, ASAE Monograph,#6,St.Joseph, Michigan,p. 257Walker,J.N. ;Duncan,G.A., 1978: Engineering Considerations ofEnergy Problems in Protected Cultivation, ACTA Hort.,#26,p.67Willits, D.H. and M.M. Peet. 1989: Predicting yield reponsesto different greenhouse C02 enrichment schemes: cucumbers andtomatoes. Agric. and For. Meteorol. 44: 275-293.Yang, X., T.H. Short, R.D. Fox and W.L. Bausle. 1990:Dynamic Modeling of the Microclimate of a Greenhouse Cucumberrow—crop. Trans. ASAE 33(5): 1701—1709.94APPENDIX A95<Case 1: Heating Requirement>Time Tin qsens qsol qnet<0 qfh C GJ/h GJ/h GJ/h GJ/h1 16.0 0.0 0.0 6.9 6.82 15.8 0.0 0.0 7.1 8.73 16.3 0.0 0.0 8.0 10.44 17.5 0.0 0.0 9.5 11.35 18.8 0.0 0.0 11.1 11.96 19.8 —1.6 1.4 13.6 13.17 20.8 1.0 8.0 9.6 10.78 21.1 6.0 16.7 2.1 9.69 22.6 6.8 25.2 0.0 7.210 24.6 10.4 37.1 0.0 4.811 25.4 17.7 49.0 0.0 3.912 26.7 19.7 56.6 0.0 2.513 26.7 24.1 60.8 0.0 1.514 27.4 22.7 61.1 0.0 1.415 27.2 23.3 58.7 0.0 1.416 27.5 21.3 55.3 0.0 0.517 26.7 18.0 45.3 0.0 1.018 20.9 2.7 6.9 4.5 2.319 21.0 1.0 3.2 6.5 5.020 18.7 1.5 3.8 3.9 0.321 16.7 0.7 1.8 2.8 0.622 16.2 0.0 0.1 3.1 1.523 16.1 0.0 0.0 3.4 2.024 16.0 0.0 0.1 3.2 2.3175.5 491.2 95.2 120.7Notation;Tinqsensqsolqnet<0qf: inside temperature [oC)sensible heat gain by air [GJ/h): solar heat admitted into greenhouse[GJ/h): heating demand [GJ/h): actual(furnace) heat supply [GJ/h]96Nc1/hNs1/h12345678910111213141516171819202122232416.015.816.317.518.819.820.821.122.624.625.426.726.727.427.227.526.720.921.018.716.716. . 781.283.784.586.585.<Case 1: Ventilation Requirement>Time Tin RHin qnet>0 Nt Nhh C GJ/h 1/h 1/hNotation;Tin : inside temperature [oC)RHin : inside humidity [%)qnet>0 : ventilation demand IGJ/h)Nt : ventilation rate for temp. control [1/h)Nh : ventilation rate for humidity control [1/h)NC : ventilation demand for C02 [1/h)Ns : actual ventilation supply rate [1/h)<Case 1: C02 Requirement>Time C02 Cvent Pn supplyh ppm kg/ha.h )cg/ha.hkg/ha.h1 373.5 2.4 0.0 0.02 377.8 2.7 0.0 0.03 391.5 3.7 0.0 0.04 398.5 4.2 0.0 0.05 547.0 14.8 0.0 0.06 1084.6 54.6 2.2 185.47 762.4 32.5 11.5 0.08 493.1 12.3 21.3 0.09 330.5 0.0 27.1 0.010 184.4 0.0 28.4 0.011 161.9 0.0 30.9 0.012 130.2 0.0 29.3 0.013 108.5 0.0 26.9 0.014 102.3 0.0 26.0 0.015 111.0 0.0 27.0 0.016 88.3 0.0 22.8 0.017 67.9 0.0 17.8 69.518 241.4 0.0 9.0 35.119 712.8 49.2 4.7 68.520 407.4 23.7 5.5 0.021 182.0 0.0 2.5 0.022 204.4 0.0 0.1 21.523 228.5 0.0 0.0 0.024 220.7 0.0 0.0 0.0380.0Notation;C02 : carbon dioxide concentration [ppm]Cvent : C02 loss due to ventilation [kg/ha.h]Pn : net photosynthetic rate [kg/ha.h]Supply : C02 supply [kg/ha.h)98inside temperature [oC)sensible heat gain by air [GJ/hJsolar heat admitted into greenhouse[GJ/h]heating demand [GJ/h): actual(furnace) heat supply [GJ/h)<Case 2: Heating Requirement>Time Tin qsens qsol qnet<0 qfh C GJ/h GJ/h GJ/h GJ/h1 16 0.0 0.0 6.0 3.02 15.9 0.0 0.0 6.2 3.33 16.3 0.0 0.0 6.4 5.54 17.5 0.0 0.0 7.4 7.55 18.5 0.0 0.0 8.7 9.46 19.8 —2.5 1.0 13.1 8.97 19.7 1.3 4.3 8.1 6.78 19.7 3.1 10.6 5.4 6.69 20.4 4.8 21.7 3.0 4.710 20.5 6.1 21.7 1.1 4.811 23.1 2.7 28.4 6.3 2.812 24.3 8.2 37.0 1.1 1.713 24.7 14.6 53.0 0.0 1.514 24.9 16.5 57.9 0.0 1.815 24.8 15.4 52.9 0.0 1.716 24.1 11.9 40.9 0.0 2.117 24.1 10.7 36.6 0.0 1.618 23.1 8.9 30.4 0.0 1.419 22.1 7.2 24.8 0.0 4.420 18.4 1.9 6.7 3.4 6.321 17.2 0.6 2.1 4.3 7.222 16.5 0.0 0.1 4.9 7.623 15.8 0.0 0.0 4.9 8.024 16.2 0.0 0.1 5.8 7.7111.6 430.1 95.7 116.4Notation;Tinqsensqsolqnet<0qf99<Case 2: Ventilation Requirement>Time Tin Ruin qnet>0 Nt Nh NC Nsh C GJ/h 1/h 1/h 1/h 1/h1 16 85.1 0.0 0.0 0.0 0.0 0.12 15.9 86 0.0 0.0 0.0 0.0 0.03 16.3 87.6 0.0 0.0 0.0 0.0 0.04 17.5 86.1 0.0 0.0 0.0 0.0 0.15 18.5 83.8 0.0 0.0 0.0 0.0 0.16 19.8 78.7 0.0 0.0 0.3 0.0 0.17 19.7 76.7 0.0 0.0 1.0 0.0 0.98 19.7 75.9 0.0 0.0 2.6 0.0 2.99 20.4 79.9 0.0 0.0 3.9 2.9 2.710 20.5 83.9 0.0 0.0 3.1 2.8 3.411 23.1 87.3 0.0 0.0 3.7 2.1 2.712 24.3 88.6 0.0 0.0 4.4 1.2 3.113 24.7 85 5.8 5.3 7.4 1.4 5.114 24.9 83.6 7.5 6.8 7.7 1.2 6.415 24.8 83.4 6.5 5.9 6.5 1.5 5.516 24.1 85.9 3.3 3.1 5.3 1.0 3.717 24.1 84.2 2.0 1.9 5.3 1.3 3.418 23.1 84.6 1.5 1.6 8.6 1.1 2.919 22.1 82.9 0.6 0.7 9.3 1.2 3.320 18.4 77.1 0.0 0.0 2.5 0.8 3.921 17.2 78.6 0.0 0.0 1.4 0.3 0.722 16.5 83.9 0.0 0.0 0.1 0.0 0.323 15.8 87.1 0.0 0.0 0.0 0.0 0.124 16.2 84.2 0.0 0.0 0.0 0.0 0.1Notation;Tin : inside temperature [CC)RUin : inside humidity [%)qnet>O : ventilation demand [GJ/h]Nt : ventilation rate for temp. control [1/h)Nh : ventilation rate for humidity control [1/h)NC : ventilation demand for C02 [1/h]Ns : actual ventilation supply rate [1/h)100carbon dioxide concentration [ppm]: C02 loss due to ventilation [kg/ha.h): net photosynthetic rate [kg/ha.h): C02 supply [kg/ha.h]<Case 2: C02 Requirement>Time C02 Cvent Pn Suppyh ppm kg/ha.hkg/ha.h kg/ha.h1 240.3 0 0.0 0.02 296.3 0 0.0 0.03 300 0 0.0 0.04 342.9 0 0.0 0.05 456.1 15 0.0 0.06 829.8 67 1.7 0.07 505.7 39 6.8 0.08 348.6 4 14.7 0.09 227.3 0 23.0 0.010 225 0 23.0 99.511 171 0 25.1 0.012 92.3 0 21.2 0.013 92.9 0 24.5 0.014 74.3 0 21.7 97.915 96.3 0 25.1 0.016 74.7 0 19.3 76.317 97 0 21.6 0.018 94.3 0 19.4 0.019 114.2 0 19.2 106.320 183.6 0 8.9 136.121 198.3 0 3.3 131.522 225.9 0 0.2 135.823 261.8 0 0.0 0.024 300 0 0.0 0.0783.4Notation;C02CventPnSupply101<Case 3: Heating Requirement>Time Tin qsens qsol qnet<O qfh C GJ/h GJ/h GJ/h GJ/h1 18.2 0.0 0.0 1.3 0.22 18.0 0.0 0.0 1.4 0.23 17.7 0.0 0.0 1.1 0.34 17.4 0.0 0.0 0.8 0.35 17.8 0.0 0.0 1.3 1.56 19.8 0.0 0.0 3.3 9.77 22.1 —4.9 0.1 10.4 9.38 22.4 —0.8 0.5 6.5 9.39 22.1 —0.4 1.9 6.0 9.310 22.2 —1.4 6.1 6.5 9.311 23.0 —3.2 7.3 8.7 9.212 24.0 —3.6 7.2 9.4 9.013 23.5 —1.5 7.4 7.1 9.114 23.1 —2.3 11.4 7.2 9.215 22.2 —2.2 10.7 5.7 9.316 22.7 —2.0 4.9 6.6 3.717 21.3 —0.7 3.4 4.2 2.118 20.8 —0.5 2.5 3.8 3.319 20.9 —0.5 1.6 4.4 4.220 19.1 —0.1 0.3 3.1 1.221 17.2 0.0 0.0 1.8 0.422 17.0 0.0 0.0 1.9 0.523 16.6 0.0 0.0 1.6 0.824 16.9 0.0 0.0 2.1 0.4—24.0 65.2 106.1 111.9Notation;Tinqsensqsolqnet<0qf: inside temperature [oC): sensible heat gain by air [GJ/h): solar heat admitted into greenhouse[GJ/hJheating demand [GJ/h)actual(furnace) heat supply [GJ/h)102<Case 3: Ventilation Requirement>NotationTin:RHinqnet>0Nt:Nh:NC:Ns:inside temperature [oC)inside humidity [%)ventilation demand [GJ/h)ventilation rate for temp. control [1/h)ventilation rate for humidity control [1/h)ventilation demand for C02 (1/h)actual ventilation supply rate [1/h)Time Tin REin qnet>0 Nt Nh NC Nsh C GJ/h 1/h 1/h 1/h 1/h1 18.2 89.3 0.0 0.0 0.0 0.0 6.42 18.0 91.5 0.0 0.0 0.0 0.0 1.83 17.7 91.8 0.0 0.0 0.0 0.0 3.54 17.4 92.9 0.0 0.0 0.0 0.0 6.35 17.8 93.5 0.0 0.0 0.0 0.0 1.26 19.8 87.1 0.0 0.0 0.0 0.0 1.97 22.1 78.2 0.0 0.0 0.1 0.0 3.88 22.4 77.8 0.0 0.0 0.8 0.0 3.59 22.1 81.0 0.0 0.0 1.9 0.0 4.510 22.2 83.3 0.0 0.0 6.2 0.0 3.611 23.0 84.8 0.0 0.0 7.0 7.0 6.312 24.0 84.9 0.0 0.0 6.1 7.8 6.313 23.5 84.4 0.0 0.0 5.7 13.5 6.914 23.1 83.3 0.0 0.0 11.5 4.9 11.115 22.2 82.3 0.0 0.0 18.7 2.7 8.016 22.7 82.3 0.0 0.0 5.4 4.5 8.517 21.3 84.1 0.0 0.0 5.0 4.3 4.818 20.8 87.3 0.0 0.0 2.4 0.0 1.519 20.9 85.3 0.0 0.0 1.5 0.0 2.420 19.1 84.6 0.0 0.0 0.6 0.1 12.221 17.2 86.9 0.0 0.0 0.0 0.0 7.022 17.0 87.0 0.0 0.0 0.0 0.0 5.123 16.6 89.9 0.0 0.0 0.0 0.0 4.524 16.9 90.7 0.0 0.0 0.0 0.0 3.8103<Case 3: C02 Requirement>: carbon dioxide concentration [ppm): C02 loss due to ventilation [kg/ha.h]: net photosynthetic rate [kgfha.h): C02 supply [kg!ha.h)Time C02 Cvent Pn Supplyh ppm kg/ha.hkg/ha.h kg/ha.h1 177.9 0.0 0.0 0.02 185.6 0.0 0.0 0.03 194.3 0.0 0.0 0.04 185.9 0.0 0.0 0.05 195.3 0.0 0.0 0.06 203.2 0.0 0.0 0.07 293.6 0.0 0.1 0.08 390.0 15.7 0.9 0.09 387.0 18.0 3.1 0.010 338.8 0.0 9.6 0.011 317.3 0.0 11.2 0.012 319.8 0.0 11.1 0.013 328.0 0.0 11.4 0.014 292.7 0.0 16.2 0.015 261.8 0.0 15.1 0.016 315.2 0.0 7.8 0.017 321.3 0.0 5.6 0.018 377.3 6.5 4.1 58.819 424.2 20.0 2.7 74.120 244.8 0.0 0.6 0.021 176.7 0.0 0.0 0.022 176.4 0.0 0.0 0.023 180.8 0.0 0.0 0.024 193.5 0.0 0.0 0.0Notation;C02CventPnSupply104: inside temperature [oC]: sensible heat gain by air [GJ/h): solar heat admitted into greenhouse[GJ/h): heating demand [GJ/h): actual(furnace) heat supply [GJ/h]<Case 4: Heating Requirement>Timeh123456789101112131415161718192021222324qsens qsol qnet<0 qfGJ/h GJ/h GJ/h GJ/h0.0 0.0 8.7 3.60.0 0.0 8.3 5.10.0 0.0 8.0 5.20.0 0.0 7.2 6.30.0 0.0 8.0 5.90.0 0.0 9.1 10.00.0 0.0 11.5 12.0—1.9 0.2 13.6 10.3—1.7 1.8 12.8 10.7—2.6 2.5 13.0 9.6—7.6 7.1 16.7 9.3—6.7 6.8 15.1 9.3—2.7 2.7 11.2 9.4—2.6 2.7 12.1 9.4—2.8 2.8 11.8 5.3—0.8 0.8 9.1 6.7—1.4 0.1 10.3 7.5—0.6 0.1 9.5 6.7—0.1 0.1 8.5 4.6—0.1 0.1 6.7 4.00.0 0.0 6.1 4.00.0 0.0 6.4 4.60.0 0.0 6.3 6.00.0 0.0 6.4 7.5—31.6 27.9 236.2 173.0TinC17.717.417.517.318.018.920.621.421.221.321.621.521.321.;Tinqsensqsolqnet<0qf105qnet>0GJ/hMt1/hNh1/hMc1/hMs1/hTime Tin RHinh C12345678910111213141516171819202122232417.717.417.517.318.018.920.621.421.221.321.621.521.321. 017.717.417.417.484. 085.587. 687.986.685.181.178.980.380.577.477.478. 179.582. 086.081.379.579.281.182 . 182.582.980.<Case 4: Ventilation Requirement>Notation;Tin : inside temperature [oC)Rim : inside humidity [%)qnet>0 : ventilation demand [GJ/h]Nt : ventilation rate for temp. control [1/h)Nh : ventilation rate for humidity control [1/h)Nc : ventilation demand for C02 [1/h)Ms : actual ventilation supply rate [1/h) dioxide concentration [ppm]: C02 loss due to ventilation [kg/ha.hJ: net photosynthetic rate [kg/ha.hJC02 supply [kg/ha.h]<Case 4: C02 Requirement>Time C02 Cvent Pn Supplyh ppm kg/ha.hkg/ha.h kg/ha.h1 484 10.5 0.0 0.02 494 11.2 0.0 0.03 496 11.5 0.0 0.04 500 12.2 0.0 0.05 507 12.2 0.0 0.06 527 13.4 0.0 0.07 537 14.3 0.0 0.08 888 41.1 0.3 0.09 1042 52.0 3.0 189.010 686 28.0 4.0 0.011 392 6.9 10.7 0.012 297 0.0 9.9 0.013 409 11.3 4.4 0.014 1268 149.8 4.4 0.015 1632 210.2 4.7 177.016 1336 101.3 1.4 0.017 1256 108.6 0.2 133.018 1143 112.1 0.2 0.019 994 113.3 0.2 0.020 965 122.8 0.1 0.021 838 89.6 0.0 0.022 766 56.7 0.0 0.023 734 49.2 0.0 0.024 705 54.0 0.0 0.0499.2Notation;C02CventPnSupplyaXTGNIdcTVLOTMAXNTERRtJT’TIBLESTATEMENTJUN,1991MAINTERRUPTIBLESTAENT)UG,1991MAINTEREJJPTIELESTATEMENTNOV,1991STATEMENTDATE:1991-09-05SmTEMEN’rDATE:1991-12-03DAYVOLUMEENERGYDAYVOLUMEENERGYDAYVOLUMEENERGY103m(G.3)103m(GJ)io33(cs)13.5138.013.7144.0112.5485.025.3207.023.5135.0210.4402.034.8187.033.3128.0312.1467.046.5252.042.182.0410.3398.053.6139.055.5215.0510.7413.065.5210.063.5136.0610.4400.076.6254.075.3204.078.1312.085.6215.085.5212.088.7336.095.2201.06.2239.099.6370.0/107.3281.0107.2276.0109.2354.0115.8224.0115.5208.0119.3359.0125.0193.0127.5283.01210.7411.0135.9228.0134.3162.01311.6447.0146.3243.0143.7139.01413.1503.0156.2239.0153.5132.01510.1388.0165.7218.0163.1116.01611.3436.0178.7333.0173.2120.01710.8416.0183.8146.0183.7139.0189.3258.0192.9110.0194.1154.01912.2470.0207.1273.0203.9147.02012.0463.0216.0234.0213.6136.02111.2432.0225.2202.0223.1117.02210.2394.0234.6177.0235.1192.02311.2432.0243.7143.0245.6211.02410.3396.0256.9267.0255.3200.0257.0270.0265.6217.0268.2309.0268.8339.0273.9151.0278.4317.0277.8300.0282.7105.0288.8333.02812.3473.0296.3243.0297.4284.02911.3436.0304.6178.0307.5288.03010.6409.0317.6295.0TOTAL160.86,208.0TOTAL313.112,071.0TOTAL158.96,053.0<MonthlyEnergyConsumptionData>


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