Engineering Reference - EnergyPlus Documentation

EnergyPlus Documentation

Engineering ReferenceThe Reference to EnergyPlus Calculations(in case you want or need to know)

COPYRIGHT (c) 1996-2015 THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS AND THE REGENTS OF THE UNIVERSITY OF CALIFORNIA THROUGH THE ERNEST ORLANDOLAWRENCE BERKELEY NATIONAL LABORATORY. ALL RIGHTS RESERVED. NO PART OF THIS MATERIAL MAY BE REPRODUCED OR TRANSMITTED IN ANY FORM OR BY ANY MEANSWITHOUT THE PRIOR WRITTEN PERMISSION OF THE UNIVERSITY OF ILLINOIS OR THE ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY. ENERGYPLUS IS A TRADEMARKOF THE US DEPARTMENT OF ENERGY.

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EnergyPlus Documentation Page 1 of 847

Table of contents

EnergyPlusTM DocumentationEngineering Reference

The Reference to EnergyPlus CalculationsOverview

Document OverviewGeneral Modeling OverviewSimulation ManagerWarmup Convergence

Integrated Solution ManagerBasis for the Zone and Air System Integration

Zone Sensible Heat Capacity MultiplierSummary of Predictor-Corrector ProcedureAir System ControlMoisture Predictor-Corrector

Moisture PredictionMoisture Correction

Carbon Dioxide Predictor-CorrectorCarbon Dioxide PredictionCarbon Dioxide Correction

Generic Contaminant Predictor-CorrectorGeneric Contaminant PredictionGeneric Contaminant Correction

Zone Air Mass Flow ConservationSummary of Time Marching Solution

Summary of Timestep Model FormulationZone Update MethodVariable TimestepSimultaneous Solution of Plant/System Water LoopReferences

Surface Heat Balance Manager / ProcessesConduction Through The Walls

Conduction Transfer Function ModuleCalculation of Conduction Transfer FunctionsConduction Transfer Function (CTF) Calculations in EnergyPlusConduction Transfer Function (CTF) Calculations Special Case: R-Value Only LayersReferences

Conduction Finite Difference Solution AlgorithmBasic Finite Difference Solution ApproachFinite Difference Node Arrangement in SurfacesConduction Finite Difference Variable Thermal ConductivityConduction Finite Difference Source Sink LayersReferences

Combined Heat and Moisture Transfer (HAMT) ModelOverviewHAMT NomenclatureHAMT Model DescriptionReferences

Effective Moisture Penetration Depth (EMPD) ModelOverviewEMPD Model DescriptionEMPD Value DeterminationEMPD NomenclatureReferences

Outside Surface Heat BalanceExternal Shortwave RadiationExternal Longwave RadiationReferencesAtmospheric VariationOutdoor/Exterior ConvectionExterior/External ConductionReferences

Inside Heat BalanceInternal Long-Wave Radiation ExchangeInternal Short-Wave RadiationInterior ConductionInterior Convection

Adiabatic Boundary ConditionsInfrared Radiation Transfer Material

Radiation Exchange BasicsRadiation Transfer Surface DetailsBehavior Checks

Transparent Insulation Material (TIM)IntroductionComparison of Opaque and Transparent InsulationTypes of Transparent Insulation MaterialsTIM- Basic Mathematical Model


Sample Test Run Cases: – ComparisonReferences

Surface Heat Balance With Moveable InsulationBasic Heat Balance CasesHeat Balance CasesFortran Algorithm ExamplesFortran Variable DescriptionsReferences

Ground Heat Transfer Calculations using C and F Factor ConstructionsGround Heat Transfer Calculations using Site:GroundDomain:SlabGround Heat Transfer Calculations using Site:GroundDomain:BasementExterior Naturally Vented Cavity

Baffle Heat BalanceCavity Heat BalanceUnderlying Heat Transfer SurfaceSolar and Shading CalculationsLocal Wind Speed CalculationsConvection CoefficientsRadiation CoefficientsReferences

Green Roof Model (EcoRoof)OverviewGreen Roof Model DescriptionLinearizationFinal EquationsGreen Roof NomenclatureReferences

Climate, Sky and Solar/Shading CalculationsClimate Calculations

EnergyPlus Design Day Temperature CalculationsSky Radiation ModelingEnergyPlus Sky Temperature CalculationEnergyPlus Design Day Solar Radiation CalculationsPerez Direct/Diffuse Splitting ModelWeather File Solar InterpolationReferences

Design Week SpecificationSky Radiance Model

Sky Diffuse Solar Radiation on a Tilted SurfaceShadowing of Sky Diffuse Solar RadiationShadowing of Sky Long-Wave Radiation

Shading ModuleShading and Sunlit Area CalculationsSolar PositionSurface GeometryShadow ProjectionHomogeneous CoordinatesPolygon Clipping AlgorithmsOverlapping ShadowsSolar GainsSolar DistributionDetails of the Interior Solar Distribution CalculationGround ReflectancesGround Reflectances (Snow)References

Solar Radiation Reflected from Exterior SurfacesDiffuse Reflection of Beam Solar and Sky Solar Radiation

Receiving pointsRaysSky Solar Radiation Diffusely Reflected from ObstructionsSky Solar Radiation Diffusely Reflected from the GroundBeam Solar Radiation Diffusely Reflected from ObstructionsBeam Solar Radiation Diffusely Reflected from the GroundBeam Solar Radiation Specularly Reflected from Obstructions

Daylighting and Window CalculationsDaylighting CalculationsDaylight Factor Calculation

OverviewInterior Illuminance ComponentsDaylight FactorsSky Luminance DistributionsDirect Normal Solar IlluminanceExterior Horizontal IlluminanceDirect Component of Interior Daylight IlluminanceInternally-Reflected Component of Interior Daylight IlluminanceTransmitted Flux from Sky and GroundTransmitted Flux from Direct SunLuminance of Shaded Window


Daylight Discomfort GlareTime-Step Daylighting Calculation

OverviewTime-Step Sky LuminanceInterior IlluminanceGlare IndexLighting Control System SimulationReferences

DElight Daylighting CalculationsDElight Daylight Factor Calculation Differences from EnergyPlus Detailed MethodsDElight Time-Step Interior Daylighting Calculation Differences from EnergyPlus Detailed MethodsReferences

Complex Fenestration Daylighting CalculationsInternal Average Reflected Illuminance From WindowLuminance from Exterior ElementsLuminous Flux and Direct Illuminance at Interior Side of the WindowHandling Exterior Obstructions

Daylighting DevicesTubular Daylighting DevicesDaylighting ShelvesWindow Light Well

Window Calculation ModuleOptical Properties of GlazingGlass Layer PropertiesGlass Optical Properties ConversionSimple Window ModelGlazing System PropertiesCalculation of Angular PropertiesCalculation of Hemispherical ValuesOptical Properties of Window Shading DevicesThermochromic WindowsScreen Properties and CalculationsComplex Fenestration Calculation Module

Window Heat Balance CalculationThe Glazing Heat Balance EquationsRoom-Side ConvectionSolving the Glazing Heat Balance EquationsEdge-Of-Glass EffectsApportioning of Absorbed Short-Wave Radiation in Shading Device LayersWindow Frame and Divider CalculationBeam Solar Reflection from Window Reveal SurfacesShading Device Thermal ModelHeat Balance Equations for Shading Device and Adjacent GlassSolving for Gap Airflow and TemperatureHeat Balance Equations for Between-Glass Shading DeviceAirflow WindowsEvacuated Glazing Unit (EGU)Thermal Performance of Deflected Insulated Glazing Unit (IGU)Equivalent Layer Fenestration Model

Air Heat Balance Manager / ProcessesConvection from SurfacesConvection from Internal SourcesInfiltration/Ventilation

InfiltrationInfiltration Design Flow RateInfiltration by Effective Leakage AreaInfiltration by Flow CoefficientVentilationVentilation Design Flow RateVentilation by Wind and Stack with Open AreaZone Air Balance Outdoor Airflow (ZoneAirBalance:OutdoorAir)Reference

Air ExchangeTemperature Difference Controlled Air ExchangeDensity Difference Controlled Air ExchangeReferences

Calculation of Zone Air TemperatureBuilding System Simulation System Manager / Processes

Air LoopsDefinition of Air LoopSimulation MethodComponent ModelsIteration SchemeDetermination of Air Mass Flow Rates

Air Loop SimulationPrimary Air System Simulation

Input dataInitialization Calculations


Central air system simulationOutdoor Air System

SimulationOutdoor Air Mixer

SimulationZone Equipment Simulation

Input dataInitialization CalculationsSimulation

Air Path ComponentsOverviewZone Supply Air PathZone SplitterZone Supply PlenumZone Return Air PathZone MixerZone Return Plenum

Plant Load ProfileCalculation Model

Plant/Condenser LoopsIntegration of System and PlantCurrent Primary System Modeling MethodologyPlant ManagerPlant Flow ResolverSummary of Load Distribution SchemesSummary of Plant Loop Demand Calculation SchemesPlant and Condenser Equipment Operation SchemesPlant Operation SchemesCondenser Operation SchemesPrimary-Secondary Loop SystemsHeat Recovery Loop SystemsPlant Pressure Drop Simulation

Steam Systems and Component ModelsSteam Loop AssumptionsSteam To Air Heat ExchangerCondensate PumpSteam Pipe

Loop, Equipment Sizing and other Design DataSizing ManagerHVAC Sizing Simulation ManagerZone Design Loads and Air Flow Rates

OverviewZone Design Data ArraysZone Design Load CalculationUpdating and Adjusting the Zone ResultsZone HVAC Scalable Sizing

System Design Loads and Air Flow RatesOverviewSystem Design Data ArraysSystem Design Flow Rate and Load Summation and Adjustment

Plant Loop SizingIntroductionHot and Chilled Water Loop SizingCondenser Loop Sizing

Coincident Plant Sizing using HVAC Sizing SimulationComponent Sizing

IntroductionFan SizingCoil:Cooling:WaterCoil:Cooling:Water:DetailedGeometry SizingCoil:Cooling:WaterToAirHeatPump:EquationFit SizingCoil:Cooling:WaterToAirHeatPump:VariableSpeedEquationFit SizingCoil:Heating:WaterToAirHeatPump:EquationFit SizingCoil:Heating:WaterToAirHeatPump:VariableSpeedEquationFit SizingCoil:Heating:Water SizingCoil:Heating:Steam SizingSizing of Gas and Electric Heating CoilsDX Coil SizingDX MultiSpeed Coil SizingCoil:Cooling:DX:VariableSpeed SizingCoil:Heating:DX:VariableSpeed SizingPump SizingElectric Chiller SizingPlant Heat Exchanger SizingHumidifier SizingCooling Tower SizingFluid Cooler SizingEvaporative Fluid cooler Sizing


Fan Coil Unit SizingWindow Air Conditioner SizingUnit Ventilator SizingPackaged Terminal Heat Pump SizingMultiSpeed Heat Pump SizingSingle Duct Terminal UnitsIndirect Evaporative Cooler SizingSecondary DX Coils SizingDesiccant Dehumidifier SizingEvaporative Cooler SizingHeat Recovery SizingLow Temperature Radiant System SizingUnitary System Sizing

Zone Outdoor Air Design DataDesign Outdoor Air CalculationReferences

Demand LimitingAlgorithm

Alternative Modeling ProcessesRoomAir ModelsUser Defined RoomAir TemperaturesOne-Node Displacement Ventilation RoomAir ModelThree-Node Displacement Ventilation RoomAir ModelUnder-Floor Air Distribution Interior Zone ModelUnder-Floor Air Distribution Exterior Zone ModelCross Ventilation Room Air Model

AirflowNetwork ModelOverviewModel DescriptionPressure and Airflow CalculationsNode Temperature CalculationsNode Humidity Ratio CalculationsSensible and Latent Load CalculationsImpacts of Supply Air Constant Volume Fan Control on Load: Cycling vs. ContinuousAirflow Calculation Procedure using A Supply Variable Air Volume FanIntegration of the AirflowNetwork ModelModel OutputOccupant Ventilation ControlReferences

Electric Load Center Distribution ManagerOverviewElectric Load Center GeneratorsInvertersElectrical StorageElectrical Storage – Kinetic Battery ModelElectric Load Center Transformers

Photovoltaic ArraysSimple ModelEquivalent One-Diode ModelSandia Photovoltaic Performance Model

GeneratorsInternal Cumbustion EngineTurbine GeneratorMicroturbine GeneratorMicro-CogeneratorFuel Cell CogeneratorCustom Fuel Supply for GeneratorsWind Turbine

Performance Curves and Lookup TablesPerformance Curves

Curves based on a single independent variableCurves based on two independent variablesCurves based on three independent variablesPressure drop curve

Performance TablesTables based on a single independent variableTables based on two independent variablesLookup Tables

Economics CalculationsComponent Costs

Line Item CostsAdjustmentsComparisons

Tariff ComputationConceptual Framework – Variables and HierarchyDefault Order of ComputationComputation Steps

Life-Cycle Cost Computations


ExpressAsCashFlowsComputePresentValueComputeTaxAndDepreciation

Special Modules/ReportingEnvironmental Impacts

Types of PollutantsCarbon EquivalentFossil Fuel Emissions FactorsOff-Site Electricity Generation EmissionsOther Energy-Related Pollutants and Sources of Other InformationReferences

Zone Component Loads SummaryEstimated Component Load Details

Operational FaultsIntroduction to Operational Faults ModelingSensor Faults with Air EconomizersThermostat/Humidistat OffsetHeating and Cooling Coil Fouling

Simulation Models – Encyclopedic ReferenceAir System Distribution Terminals

Constant Volume Single Duct Uncontrolled Air TerminalConstant Volume Single Duct Reheat Air TerminalVariable Air Volume Single Duct Reheat and No Reheat Air TerminalsVariable Air Volume Heating and Cooling Single Duct Reheat and NoReheat Air TerminalConstant Volume Single Duct Four Pipe Induction Air TerminalFan Powered Induction Series and Parallel Single Duct Reheat Air TerminalVariable Air Volume Fan Powered Single Duct Air TerminalCooled Beam Unit (AirTerminal:SingleDuct:ConstantVolume:CooledBeam)Constant Volume Dual Duct Air TerminalVariable Air Volume Dual Duct Air TerminalDual Duct Dedicated Outside Air Terminal with VAV Cooling

BoilersSimple Hot Water BoilerSteam Boiler

ChillersAbsorption ChillerIndirect Absorption ChillerCombustion Turbine ChillerChillerHeater:Absorption:DirectFiredChillerHeater:Absorption:DoubleEffectConstant COP ChillerHot Water Heat Recovery from ChillersElectric Chiller Model Based on Fluid Temperature DifferencesElectric Chiller Model Based on Condenser Entering TemperatureElectric Chiller Model Based on Condenser Leaving TemperatureEngine Driven Chiller

Ice Thermal StorageSimple Ice Storage ModelDetailed Ice Storage Model

CoilsChilled-Water-Based Air Cooling CoilChilled-Water-Based Detailed Geometry Air Cooling CoilHot-Water-Based Air Heating CoilSingle-Speed Electric DX Air Cooling CoilMulti-Speed Electric DX Air Cooling CoilTwo-Speed Electric DX Air Cooling CoilVariable Speed DX Cooling CoilElectric Air Heating CoilGas Air Heating CoilMulti-Stage Electric and Gas Air Heating CoilSingle-Speed Electric Heat Pump DX Air Heating CoilSingle-Speed DX Heating Coil Standard RatingsMulti-Speed Electric Heat Pump DX Air Heating CoilVariable Speed DX Heating CoilDesuperheater-Recovery-Based Air Heating CoilDesuperheater-Recovery-Based Water Heating CoilHeat Exchanger Assisted Air Cooling Coil SystemsSingle-Speed Electric Heat Pump DX Water Heating CoilWater Source Electric DX Air Cooling CoilWater Source Electric Heat Pump DX Air Heating CoilSteam-Based Air Heating CoilVariable Refrigerant Flow Cooling CoilVariable Refrigerant Flow Heating CoilVariable Speed Water to Air Heat Pump (Heating & Cooling)Packaged Thermal Storage Cooling Coil

HVAC ControllersControl Valve for Water-Based Air System CoilsOutdoor Air Damper Controller for Air Systems


Outdoor Air Damper Controller for Zone Energy Recovery VentilatorBaseboard Heaters

Hot Water Baseboard Heater with Only ConvectionElectric Baseboard Heater with Only ConvectionHot Water Baseboard Heater with Radiation and Convection

Electric Baseboard Heater with Radiation and ConvectionOverviewModel DescriptionSteam Baseboard Heater with Radiation and Convection

Cooling Towers and Evaporative Fluid CoolersOne, Two, and Variable Speed Cooling Towers and Evaporative Fluid CoolersVariable Speed Cooling Towers Empirical ModelsCooling Towers with Multiple CellsCooling Tower Makeup Water UsageOne and Two Speed Fluid Coolers

Demand Controlled VentilationVentilation Rate ProcedureIndoor Air Quality ProcedureProportional ControlReferences

Evaporative CoolersDirect Evaporative CoolerDry Coil Indirect Evaporative CoolerWet Coil Indirect Evaporative CoolerTwo Stage Direct/Indirect Evaporative CoolerIndirect Evaporative Cooler Special Research ModelDirect Evaporative Cooler Special Research Model

Air System FansOverviewModelReferences

Air System Compound Component GroupsUnitary SystemsForced-Air Furnace and Central Air ConditioningUnitary SystemsUnitary System with Changeover-Bypass-Variable Air VolumeUnitary Air-To-Air Heat PumpUnitary Multi-Speed Air-To-Air Heat PumpDX Cooling PackageDX Heating PackageDesiccant Dehumidifier PackageUnitary Water-To-Air Heat PumpWater To Water Heat PumpsEquation Fit Water To Water Heat Pump ModelParameter Estimation Water-To-Water Heat Pump Model

Variable Refrigerant Flow Heat PumpsVariable Refrigerant Flow Heat Pump ModelZone Terminal Unit List

Heat ExchangersAir System Air-To-Air Sensible and Latent Effectiveness Heat ExchangerAir System Air-To-Air Flat Plate Heat ExchangerAir System Air-To-Air Balanced Flow Desiccant Heat ExchangerPlant Loop Deep-Ground-To-Water Vertical U-Tube Field Heat ExchangerGroundHeatExchanger:SlinkyPlant Loop Pond-To-Water Heat ExchangerPlant Loop Surface-Ground-To-Water Heat ExchangerPlant Loop Fluid-to-Fluid Heat ExchangerReferences

Air System HumidifiersOverviewElectric and Gas Steam Humidifier

Zone Internal GainsSources and Types of GainsHeat Gain from LightsHeat Gain from PeopleHeat Gain from IT EquipmentHeat Gain from Baseboard HeatDistribution of Radiant GainsReferences

Indoor Swimming PoolEnergy Balance of Indoor Swimming PoolConvection from the pool water surfaceEvaporation from the pool water surfaceRadiation exchange with the pool water surfaceConduction through the bottom of the poolMakeup pool water supplyHeat Gain from PeopleHeat from auxiliary pool heater


Pool Heating to Control the Pool Water TemperaturePool/Surface Heat Balance Equation SummaryOther additional informationSwimming Pool Flow RateComfort and HealthAir Delivery Rates (Indoor Pool)References

PipesHeat Transfer Pipes (Objects: Pipe:Indoor & Pipe:Outdoor)Underground Pipe (Object: Pipe:Underground)PipingSystem:Underground Simulation

PumpsSummary of Pump RulesDynamic Pump Pressure HeadVariable Speed PumpPressure-based Flow for Variable Speed PumpsConstant Speed PumpPressure-based Flow for Constant Speed PumpsPump Heat Addition to the LoopPump Heat Addition to Surrounding ZoneHeadered PumpsCondensate Pumps

Ideal Loads Air SystemOverviewModelReferences

District CoolingDistrict HeatingCentralHeatPumpSystem

OverviewModel Description

ChillerHeaterPerformance:Electric:EIROverviewModel DescriptionReferences

Plant Temperature Source ComponentRadiant System Models

Low Temperature Radiant System ModelHigh Temperature Radiant Heater Model

Refrigeration EquipmentOverviewRefrigeration Compressor RacksRefrigerated CasesWalk-In Coolers and FreezersAir Chillers and Air Chiller SetsDetailed Refrigeration SystemsSecondary Refrigeration SystemsTranscritical CO2 Refrigeration SystemReferences

Setpoint ManagersOverviewScheduledOutdoor Air ResetSingle Zone Reheat Heating and CoolingSingle Zone Heating OnlySingle Zone Cooling OnlySingle Zone Minimum HumiditySingle Zone Maximum HumidityMixed AirOutdoor Air PretreatWarmest Zone Supply Air ResetColdest Zone Supply Air ResetReturn Air Bypass FlowWarmest Temp FlowMultizone Heating AverageMultizone Cooling AverageMultizone Minimum Humidity AverageMultizone Maximum Humidity AverageMultiZone Minimum Humidity Supply Air ResetMultiZone Maximum Humidity Supply Air ResetFollow Outdoor Air TemperatureFollow System Node TemperatureFollow Ground TemperatureCondenser Entering Water Temperature ResetIdeal Condenser Entering Water Temperature Reset

Solar CollectorsFlat-Plate Solar CollectorsIntegral-collector-storage (ICS) Solar Collector


References:Photovoltaic Thermal Flat-Plate Solar CollectorsUnglazed Transpired Solar Collectors

System Availability ManagersOverviewScheduledScheduled OnScheduled OffNight CycleNight VentilationDifferential ThermostatHigh Temperature Turn OffHigh Temperature Turn OnLow Temperature Turn OffLow Temperature Turn OnHybrid Ventilation ControlOptimum Start Controls

Occupant Thermal ComfortBackground on Thermal Comfort ModelsMathematical Models for Predicting Thermal ComfortFanger Comfort ModelPierce Two-Node ModelKSU Two-Node ModelAdaptive Comfort Model Based on European Standard EN15251-2007Dynamic Clothing ModelMean Radiant Temperature CalculationReferences

Trombe WallsPassive Trombe WallActive Trombe Wall

Water Thermal Tanks (includes Water Heaters)Mixed Water Thermal TankHeat Pump Water HeaterStratified Water Thermal TankWater Heating Sizing

Water SystemsWater Mains TemperaturesWater Use Equipment and ConnectionsUnconnected Water Use EquipmentZone Heat Gain from Water Use EquipmentConnected Water Use EquipmentWater Use Equipment CalculationsDrainwater Heat Recovery

Zone ControlsThermostatic Zone ControlZone ThermostatsOperative Temperature ControlTemperature And Humidity ControlHumidistatThermal Comfort Zone Control

Zone Equipment and Zone Forced Air UnitsAir Distribution Terminal UnitInlet Side Mixer Air Terminal UnitSupply Side Mixer Air Terminal UnitSimple Duct Leakage ModelFan Coil UnitWindow Air ConditionerPackaged Terminal Air ConditionerPackaged Terminal Heat PumpZone Single Speed Water-To-Air Heat PumpZone Air DX DehumidifierEnergy Recovery VentilatorZone Evaporative Cooler UnitUnit HeaterUnit VentilatorVariable Refrigerant Flow Terminal UnitVentilated SlabCoolTowerEarthtubeThermal Chimney ModelZone Outdoor Air UnitControlsZone Exhaust Fan


OverviewDocument OverviewThis document is organized to give you the best possible look into the EnergyPlus calculations. First, the concepts of modeling in EnergyPlus are presented. These includedescriptions of the zone heat balance process, air loop/plant loop processes as well as other important processes for the building simulation.

Discussions during the modeling process may reference specific “object names” as found in the Input/Output Reference document.

The remainder of the document focuses on individual models.

General Modeling OverviewThe EnergyPlus program is a collection of many program modules that work together to calculate the energy required for heating and cooling a building using a variety ofsystems and energy sources. It does this by simulating the building and associated energy systems when they are exposed to different environmental and operating conditions.The core of the simulation is a model of the building that is based on fundamental heat balance principles. Since it is relatively meaningless to state: “based on fundamentalheat balance principles”, the model will be described in greater detail in later sections of this document in concert with the FORTRAN code which is used to describe themodel. It turns out that the model itself is relatively simple compared with the data organization and control that is needed to simulate the great many combinations of systemtypes, primary energy plant arrangements, schedules, and environments. The next section shows this overall organization in schematic form. Later sections will expand on thedetails within the blocks of the schematic.

Figure 1. EnergyPlus Program Schematic

Simulation ManagerThe simulation manager of EnergyPlus is contained in a single module. The main subroutine is shown below. Flow within the entire program is managed using a series of flags.These paired flags, in order (from the highest to the lowest) are:

Table 1. Simulation Flags

BeginSimulationFlag EndSimulationFlag

BeginEnvironmentFlag EndEnvironmentFlag(one to many days)

BeginDayFlag EndDayFlag

BeginHourFlag EndHourFlag

BeginTimeStepFlag EndTimeStepFlag

There is also a WarmupFlag to signal that the program is in warmup state. The operation of these flags can be seen in the following subroutine. The advantage of using theflag system is that any subroutine throughout the code can determine the exact state of the simulation by checking the status of the flags.


SUBROUTINE ManageSimulation ! Main driver routine for this moduleBeginSimFlag = .TRUE. EndSimFlag = .FALSE. CALL OpenOutputFiles CALL GetProjectData CALL GetEnvironmentInfo ! Get the number and type of Environments DO Envrn = 1, NumOfEnvrn ! Begin environment loop ... BeginEnvrnFlag = .TRUE. EndEnvrnFlag = .FALSE. WarmupFlag = .TRUE. DayOfSim = 0 DO WHILE ((DayOfSim.LT.NumOfDayInEnvrn).OR.(WarmupFlag)) ! Begin day loop ... DayOfSim = DayOfSim + 1 BeginDayFlag = .TRUE. EndDayFlag = .FALSE. DO HourOfDay = 1, 24 ! Begin hour loop ... BeginHourFlag = .TRUE. EndHourFlag = .FALSE. DO TimeStep = 1, NumOfTimeStepInHour ! Begin time step (TINC) loop ... BeginTimeStepFlag = .TRUE. EndTimeStepFlag = .FALSE. ! Set the End\_\_Flag variables to true if necessary. Note that each flag builds on ! the previous level. EndDayFlag cannot be .true. unless EndHourFlag is also .true., etc. ! Note that the EndEnvrnFlag and the EndSimFlag cannot be set during warmup. ! Note also that BeginTimeStepFlag, EndTimeStepFlag, and the ! SubTimeStepFlags can/will be set/reset in the HVAC Manager. IF ((TimeStep.EQ.NumOfTimeStepInHour)) THEN EndHourFlag = .TRUE. IF (HourOfDay.EQ.24) THEN EndDayFlag = .TRUE. IF ((.NOT.WarmupFlag).AND.(DayOfSim.EQ.NumOfDayInEnvrn)) THEN EndEnvrnFlag = .TRUE. IF (Envrn.EQ.NumOfEnvrn) THEN EndSimFlag = .TRUE. END IF END IF END IF END IF CALL ManageWeather CALL ManageHeatBalance BeginHourFlag = .FALSE. BeginDayFlag = .FALSE. BeginEnvrnFlag = .FALSE. BeginSimFlag = .FALSE. END DO ! ... End time step (TINC) loop. END DO ! ... End hour loop. END DO ! ... End day loop. END DO ! ... End environment loop. CALL CloseOutputFiles RETURNEND SUBROUTINE ManageSimulation

Warmup ConvergenceSince everything in EnergyPlus is based on the foundation of the loads simulation, it stands to reason that any inaccuracies in the loads calculation will result in inaccuracies ofsimilar or larger magnitude in the HVAC calculations. In the presumably limited cases where convergence was not truly achieved before the actual simulation began, it isunknown how much error would be introduced into the results. While simulations that last longer (annual vs. design day) will hopefully have any initial condition problemsbalanced by the shear number of days in the simulation, shorter simulations—particularly those used for sizing—could result in relatively large errors. The simulation resultscould be unreliable and inaccurate when steady periodic conditions are not achieved. Therefore, it is important to properly determine when there is enough temperature andflux history terms to start an EnergyPlus simulation since this has a potential economic and energy impact on buildings that use EnergyPlus in design.

EnergyPlus determines warmup convergence in the following manner as shown in the Figure 2 below. The process of the convergence checks begins by tracking fourparameters such including the maximum zone air temperature, the minimum zone air temperature, the maximum heating load, and the maximum cooling load for individualzone. It is note that these convergence checks are only in effective in simulations with at least one zone since the criteria is solely based on the maximum and minimum valuesobtained from an individual zone. Differences in these parameters between two consecutive days are then compared with the convergence tolerance values at the end of theday during the warmup period. For example, the maximum and minimum air temperature and the percentage difference of zone load for each zone at 9:00AM during thesecond to last warmup is compared to the values at 9:00AM last warmup day as follows:

where Tmax,prev is the maximum zone temperature of previous day, Tmax is the maximum zone temperature of current day, Ttol is the value of temperature tolerance,

−

qh,prev is the maximum heating load of previous day, qh, is the maximum heating load of current day, qtol is the value of load tolerance, qc,prev is the maximum cooling loadof previous day, and qc, is the maximum cooling load of current day.

Note that a minimum load of 100W is used to establish a fraction for the maximum loads when they are less than the minimum. This is done to avoid a false negative indicationfor the percentage load difference that may appear when zonal loads are very small. The convergence checks are repeated until passed for all zones. EnergyPlus assumesthat the warmup period has been reached steady-periodic when these four parameters are within tolerance. Finally, temperature and load differences between the last twowarmup days for individual zone at each time step in the last warmup day are reported so that users can easily track whether or not the warmup period has converged. Theinput parameters and output related to the warmup period are discussed in the Input-Output Reference.

Figure 2. Flows of Warmup Convergence Checks

Integrated Solution ManagerEnergyPlus is an integrated simulation. This means that all three of the major parts, building, system, and plant, must be solved simultaneously. In programs with sequentialsimulation, such as BLAST or DOE-2, the building zones, air handling systems, and central plant equipment are simulated sequentially with no feedback from one to the other.The sequential solution begins with a zone heat balance that updates the zone conditions and determines the heating/cooling loads at all time steps. This information is fed tothe air handling simulation to determine the system response; but that response does not affect zone conditions. Similarly, the system information is passed to the plantsimulation without feedback. This simulation technique works well when the system response is a well-defined function of the air temperature of the conditioned space. For acooling situation, a typical supply and demand situation is shown schematically in the Figure 3. Here, the operating point is at the intersection of the supply and demand curves.


Figure 3. Sequential Simulation Supply/Demand Relationship.

However, in most situations the system capacity is dependent on outside conditions and/or other parameters of the conditioned space. The simple supply and demand situationabove becomes a more complex relationship and the system curve is not fixed. The solution should move up and down the demand curve. This doesn’t happen in sequentialsimulation methods and the lack of feedback from the system to the building can lead to nonphysical results. For example, if the system provides too much cooling to aconditioned space the excess is reported by the program as "overcooling". Other categories of unmatched loads exist and are similarly reported by the program. While this kindof reporting enables the affected system or plant components to be properly sized, the system designer would, in most cases, prefer to see the actual change in zonetemperature. The same mismatches can occur between the system and plant simulations when they are simulated sequentially.

To obtain a simulation that is physically realistic, the elements have to be linked in a simultaneous solution scheme. The entire integrated program can be represented as aseries of functional elements connected by fluid loops as shown in Figure “Schematic of Simultaneous Solution Scheme”. In EnergyPlus all the elements are integrated andcontrolled by the Integrated Solution Manager. The loops are divided into supply and demand sides, and the solution scheme generally relies on successive substitutioniteration to reconcile supply and demand using the Gauss-Seidell philosophy of continuous updating.

Figure 4. Schematic of Simultaneous Solution Scheme

In the sections which follow, the various individual functions of the integrated solution will be described.

Basis for the Zone and Air System IntegrationThe basis for the zone and air system integration is to formulate energy and moisture balances for the zone air and solve the resulting ordinary differential equations using apredictor-corrector approach. The formulation of the solution scheme starts with a heat balance on the zone air.

where:

= sum of the convective internal loads

= convective heat transfer from the zone surfaces

= heat transfer due to infiltration of outside air

= heat transfer due to interzone air mixing

= air systems output

energy stored in zone air

C = ρ C C

ρ = zone air density

C = zone air specific heat

C = sensible heat capacity multiplier (Detailed description is provided below)

If the air capacitance is neglected, the steady-state system output must be:

Air systems provide hot or cold air to the zones to meet heating or cooling loads. The system energy provided to the zone, Qsys, can thus be formulated from the differencebetween the supply air enthalpy and the enthalpy of the air leaving the zone as in Equation :

This equation assumes that the zone supply air mass flow rate is exactly equal to the sum of the air flow rates leaving the zone through the system return air plenum and beingexhausted directly from the zone. Both air streams exit the zone at the zone mean air temperature. The result of substituting Equation for Qsys in the heat balance Equation isshown in Equation :

The sum of zone loads and air system output now equals the change in energy stored in the zone. Typically, the capacitance Cz would be that of the zone air only. However,thermal masses assumed to be in equilibrium with the zone air could be included in this term.

= + ( − ) + ( − ) + ( − ) +CzdTzdt

∑i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAi Tsi Tz ∑i=1

Nzones

ṁiCp Tzi Tz ṁinfCp T∞ Tz Q̇sys (5)

∑i=1

Nsl

Q̇i

( − )∑i=1

Nsurfaces

hiAi Tsi Tz

( − )ṁinfCp T∞ Tz

( − )∑Nzonesi=1 ṁiCp Tzi Tz

Q̇sys

=CzdTz

dt

z air p T

air

p

T

− = + ( − ) + ( − ) + ( − )Q̇sys ∑i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAi Tsi Tz ∑i=1

Nzones

ṁiCp Tzi Tz ṁinfCp T∞ Tz (6)

= ( − )Q̇sys ṁsysCp Tsup Tz (7)

CzdTz

dt= + ( − ) + ( − )∑i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAi Tsi Tz ∑i=1

Nzones

ṁiCp Tzi Tz

+ ( − ) + ( − )ṁinfCp T∞ Tz ṁsysCp Tsup Tz

(8)


EnergyPlus provides three different solution algorithms to solve the zone air energy and moisture balance equations. These are defined in the Algorithm field in theZoneAirHeatBalanceAlgorithm object: 3rdOrderBackwardDifference, EulerMethod and AnalyticalSolution. The first two methods to solve Equation use the finite differenceapproximation while the third uses an analytical solution. A short description is given below.

In order to calculate the derivative term with respect to time, a finite difference approximation may be used, such as:

The use of numerical integration in a long time simulation is a cause for some concern due to the potential build-up of truncation error over many time steps. In this case, thefinite difference approximation is of low order that further aggravates the problem. However, the cyclic nature of building energy simulations should cause truncation errors tocancel over each daily cycle so that no net accumulation of error occurs, even over many days of simulation (Walton, 1990). The Euler formula, Equation , was employed inEquation to replace the derivative term. All the terms containing the zone mean air temperature were then grouped on the left hand side of the equation. Since the remainingterms are not known at the current time, they were lagged by one time step and collected on the right hand side. This manipulation resulted in Equation , the formula forupdating the zone mean air temperature:

One final rearrangement was to move the lagged temperature in the derivative approximation to the right side of the equation. The explicit appearance of the zone airtemperature was thus eliminated from one side of the equation. An energy balance equation that includes the effects of zone capacitance was then obtained by dividing bothsides by the coefficient of Tz:

Equation could be used to estimate zone air temperatures, and is defined as the EulerMethod, one of the three solution algorithms provided in theZoneAirHeatBalanceAlgorithm object. However, it can severely limit the time step size under some conditions. To improve on this, higher order expressions for the firstderivative, with corresponding higher-order truncation errors, were developed. The goal of this approach was to allow for the use of larger time steps in the simulation thanwould be possible using the first order Euler form, without experiencing instabilities. Approximations from second through fifth order were tried as reported by Taylor, et al.(1990) with the conclusion that the third order finite difference approximation, shown below, gave the best results:

When this form for the derivative is used, equation changes to:

and the zone temperature update equation becomes:

This is the form historically used in EnergyPlus and is the current default referred to as 3rdOrderBackwardDifference in the ZoneAirHeatBalanceAlgorithm object. Thisalgorithm requires zone air temperatures at three previous time steps and uses constant temperature coefficients. The assumption is that three previous time steps lengths arethe same.

The AnalyticalSolution algorithm is an integration approach. While the 3 order finite difference approximation provides stability without requiring a prohibitively small time step,the method still has truncation errors and requires a fixed time step length for the previous three simulation time steps. Therefore, different time step lengths for the previousthree simulation time steps may make the temperature coefficients invalid.

The AnalyticalSolution algorithm provides a possible way to obtain solutions without truncation errors and independent of time step length. In addition, the algorithm onlyrequires the zone air temperature for one previous time step, instead of three previous time steps as required by the 3rdOrderBackwardDifference algorithm. The integrated(analytical) solution for Eq. (4) may be expressed as follows:

Since the load on the zone drives the entire process, that load is used as a starting point to give a demand to the air system. Then a simulation of the air system provides the

= ( − ) + O(δt)dT

dt(δt)−1 Tzt Tzt−δt (9)

+ ( + + + ) =Cz −T tz T t−δtzdt T tz ∑i=1

Nsurfaces

hiAi ∑i=1

Nzones

ṁiCp ṁinfCp ṁsysCp

+ +∑i=1

Nsl

Q̇t

i ṁsysCpTt

supply ( + + )∑i=1

Nsurfaces

hiAiTsi ∑i=1

Nzones

ṁiCpTzi ṁinfCpT∞

t−δt (10)

=T tz

+ +∑i=1

Nsl

Q̇t

i ṁsysCpTt

supply ( + + + )Cz Tzδt ∑i=1

Nsurfaces

hiAiTsi ∑i=1

Nzones

ṁiCpTzi ṁinfCpT∞

t−δt

+ ( + + + )Czδt

∑i=1

Nsurfaces

hiAi ∑i=1

Nzones

ṁiCp ṁinfCp ṁsysCp

(11)

≈ ( − 3 + − ) +O(δ )dTzdt

∣∣∣t

(δt)−1116T tz T

t−δtz

32T t−2δtz

13T t−3δtz t

3 (12)

( − 3 + − ) = + ( − ) + ( − )Cz(δt)−1 11

6T tz T

t−δtz

32T t−2δtz

13T t−3δtz ∑

i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAi Tsi Tz ∑i=1

Nzones

ṁiCp Tzi Tz

+ ( − ) + ( − )ṁinfCp T∞ Tz ṁsysCp Tsup Tz

(13)

=T tz

+ + + + − ( ) (−3 + − )∑i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAiTsi ∑i=1

Nzones

ṁiCpTzi ṁinfCpT∞ ṁsysCpTsupplyCz

δtT t−δtz

32T t−2δtz

13T t−3δtz

( ) + A+ + + C116

Cz

δt∑i=1

Nsurfaces

hi ∑i=1

Nzones

ṁiCp ṁinfCp ṁsys

(14)

rd

= −T tz⎛⎝⎜⎜T

t−δtz

+ + + +∑i=1

NslQ̇i ∑

i=1

Nsurfaces

hiAiTsi ∑i=1

NzonesṁiCpTzi ṁinfCpT∞ ṁsysCpTsup

+ + +∑i=1

Nsurfaces

hiAi ∑i=1

NzonesṁiCp ṁinfCp ṁsysCp

⎞⎠⎟⎟

∗ exp − δt⎛⎝⎜⎜ + + +∑i=1

Nsurfaces

hiAi ∑i=1


Cz

⎞⎠⎟⎟

++ + + +∑

i=1

NslQ̇i ∑

i=1

Nsurfaces

hiAiTsi ∑i=1

NzonesṁiCpTzi ṁinfCpT∞ ṁsysCpTsup

+ + +∑i=1

Nsurfaces

hiAi ∑i=1


(15)


actual supply capability and the zone temperature is adjusted if necessary. This process in EnergyPlus is referred to as a Predictor/Corrector process. It is summarized below.

Code Reference: the ZoneTempPredictorCorrector module performs the calculations.

Zone Sensible Heat Capacity MultiplierIf the Zone Sensible Heat Capacity Multiplier = 1.0, this represents just the sensible heat capacitance of the air volume in the specified zone. If the value is not defined, it is setto 1.0. This multiplier can be greater than 1.0 if the zone air sensible heat capacity needs to be increased for stability of the simulation. This multiplier increases thecapacitance of the air volume by increasing the zone volume that is used in the zone predictor-corrector algorithm in the simulation. This can be done for numerical reasons,such as to increase the stability by decreasing the zone air temperature deviations at the time step level. Or it can be increased to try and account for the additional capacitancein the air loop not specified in the zone, i.e. dampers, diffusers, duct work, etc., to see the effect on the dynamics of the simulation. See the Input/Output Reference foradditional information (Object: ZoneCapacitanceMultiplier:ResearchSpecial).

In the source code below we see how the ZoneVolCapMultpSens increases the zone volume used for the air ratio at the time step in the air system. This multiplier is constantthroughout the simulation.

AIRRAT(ZoneNum) = Zone(ZoneNum)%Volume\***ZoneVolCapMultpSens**\* & PsyRhoAirFnPbTdbW(OutBaroPress,MAT(ZoneNum),ZoneAirHumRat(ZoneNum))\* & PsyCpAirFnWTdb(ZoneAirHumRat(ZoneNum),MAT(ZoneNum))/(TimeStepSys\*SecInHour)

Summary of Predictor-Corrector ProcedureThe predictor-corrector scheme can be summarized as follows:

Using equation , an estimate is made of the air system energy required to balance the equation with the zone air temperature equal to the setpoint temperature. - Withthat quantity as a demand, the air system is simulated to determine its actual supply capability at the time of the simulation. This will include a plant simulation ifnecessary. - The actual air system capability is used in equation to calculate the resulting zone temperature.

Air System ControlPreviously, the formulation of a new heat balance equation with an unsteady zone capacitance term was discussed Equation . In this equation the updated zone temperaturewas calculated by removing its explicit dependence from the right hand side and lagging, by one time step, the unknown terms on that side. However, the right hand side stillcontains implicit dependencies on the zone temperature through the air system control logic; the need for heating or cooling in the zones, is based on zone temperature. In realbuildings the control system consists of one or more sensing units in the zone, such as a wall thermostat that samples the air temperature and sends signals to a control unit.The controller looks at the difference between the actual zone temperature and the desired temperature to ascertain if heating or cooling is required and then sends appropriatesignals to the air system components to drive the zone temperature closer to the desired value.

Although many control systems use only the zone air temperature to control the air system, most modern energy management systems consider many other variables, such asoutside environment conditions. Simulating such controllers would seem to be relatively straightforward in a simulation especially since some of the more complex controlproblems, such as managing duct pressures and flow rates, are not always modeled. However, real controllers have an advantage because they can sample zone conditions,and thus update air system response, on a time scale much shorter than any characteristic time of the air system or zone. Thus the feedback between zone and air systemusually results in steady or, at worst, slowly oscillating zone conditions and air system operation unless the air system is grossly oversized. On the other hand, the numericalmodel is only able to sample zone conditions at discrete time intervals. In the interest of minimizing computation time, these intervals need to be as long as possible. Frequently,they are of the order of, or longer than, the characteristic times of the air system and zones, except in the case of small air system capacity in relation to zone capacitance. Thissituation has the potential for unstable feedback between the zone and air system, resulting in an oscillatory or diverging solution.

Prior to implementing the new heat balance method (3rdOrderBackwardDifference) in IBLAST, several air system control strategies were considered. The primary objectivewas selection of a control method that would be numerically stable over a reasonable range of conditions, realistic from the standpoint of looking and operating like an actualair system controller, and flexible enough to be applied to all current and projected systems. The method actually implemented in IBLAST, and later EnergyPlus, tookadvantage of the computational model's "knowledge" of how much energy enters or leaves the zone as a function of zone air temperature i.e., the zone load. The realcontroller, on the other hand, does not have this information. The net zone load is given by Equation :

This is Equation without the term due to the air system. In addition, Tz is now the desired zone temperature as defined by the control system setpoints that must be specifiedfor each zone. An assumption was made that if the air system has sufficient capacity (based on the desired zone air temperature) to meet the zone conditioning requirements(i.e. Qsys=Qload) at the desired zone air temperature then those requirements will be met. On the other hand, if the air system cannot provide enough conditioning to the zoneto maintain the desired temperature, then the air system provides its maximum output to the zone and the zone air temperature is allowed to "float." Equation was used tocalculate the air system output required to maintain the desired zone air temperature; the actual zone temperature update was accomplished using Equation . This method wascalled predictive system energy balance . It has many characteristics of a predictor-corrector method since the air system response is first approximated based on a predictedzone temperature and then the actual change in zone temperature is determined from that air system response. The predictive air system energy balance method required thatthe system controls on air mass flow rate, supply air temperature, etc., be formulated as a function of the zone air temperature. However, this was not a serious drawback. Thefirst example considered was a single zone draw through air system. Typically, such systems have a cooling coil and heating coil in series, and constant air volume flow rate.Single zone draw through systems run at maximum capacity when turned on; so the only way to regulate net air system output and keep the zone air temperature within thedesired range is to turn the air system on and off. A simplified schematic of this system type is shown in Figure 5. Simplified Single Zone Draw Through Air System.

Figure 5. Simplified Single Zone Draw Through Air System

The amount of heating or cooling provided by the air system in relation to the desired zone air temperature is given by:

= + ( − ) + ( − ) + ( − )Q̇load ∑i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAi Tsi Tz ∑i=1

Nzones

ṁiCp Tzi Tz ṁinfCp T∞ Tz (16)

= η ( − )Q̇sys ṁsysCp Tsup Tz, desired (17)


where h is the fraction of the time step that the air system is turned on and varies between 0 and 1. The supply air temperature is also implicitly limited by the effectiveness ofthe coils and the operating parameters of the central plant components. These interactions are discussed later.

A far more complex, though again simplified, air system is the variable air volume (VAV) system, shown in Figure 6. Simplified Variable Volume Air System. In VAV systems,the supply air temperature, as well as the supply air volume, are continuous functions of zone air temperature. As shown in Figure 7. Idealized Variable Volume SystemOperation., when the zone air temperature is between Tcl and Tcu, cooling is required and the air system varies the supply air flow rate while maintaining a constant supply airtemperature. When the zone air temperature is between Thl and Thu, heating is required and air is supplied at a constant minimum flow rate while the supply air temperature isvaried.

Figure 6. Simplified Variable Volume Air System.

The next figure (Idealized variable volume system operation) shows idealized behavior of a VAV system; in practice, the air flow rate and temperature are not exact linearfunctions of zone air temperature.

Figure 7. Idealized Variable Volume System Operation.

As long as a VAV system has sufficient capacity, the zone air temperatures can be expected to vary within the limits defining the range of operation of the air damper, whencooling, or the throttling range of the reheat coil, when the air system is heating. This means that the desired zone air temperature, used to predict the air system response, isvariable and must be calculated in order to determine the air system output. For the purposes of this calculation, the following definitions were found useful:

Equations and are derived, respectively, from the numerator and denominator of Equation but with the system related terms omitted. Also excluded from these expressions arethe effects of zone capacitance.

When a zone requires cooling, the VAV system is designed to provide air to that zone at a constant supply air temperature. The amount of cooling is matched to the load bydampers in the supply air duct that vary the air volume flow rate of being supplied to the zone. Assuming that the volume flow rate varies linearly with zone air temperature, thevolume flow rate of supply air normalized to the maximum flow rate, or supply air fraction, is given by:

Normally, the minimum supply air fraction hc,min must be greater than zero to ensure a supply of fresh air sufficient to eliminate contaminants from the zone.

Conversely, when heating is required in a zone, the VAV system becomes a constant volume flow rate system with a variable supply air temperature. The dampers are set toprovide air to the zone at the minimum supply air fraction. Throttling the hot water supply to the reheat coil, which effectively alters the coil’s heating capacity, modulates thesupply air temperature. Again, assuming the heat energy output varies linearly with zone air temperature and normalizing with respect to the maximum coil output gives thefollowing result:

Observe that when hh is equal to zero, the zone is supplied with air at the cooling coil outlet temperature at the minimum air fraction. Because the control strategies of the VAVsystem are different whether the air system is heating or cooling, two equations are necessary to describe the air system output in terms of hh and hc. These expressions areas shown in Equations and :

Equation is valid for zone air temperatures below Th,upper, while Equation is valid for all temperatures above this value. Equating the system output to the zone load, as givenby Equation , the definitions of hc and hh were then used to develop expressions for the predicted zone air temperature in the cases of heating and cooling:

= + + +Q̇0 ∑i=1

Nsl

Q̇i ∑i=1

Nsurfaces

hiAiTsi ∑i=1

Nzones

ṁiCpTzi ṁinfCpT∞ (18)

= + +Q̇slope ∑i=1

Nsurfaces

hiAi ∑i=1

Nzones

ṁiCp ṁinfCp (19)

= + (1 − )( ) ; ≤ ≤ 1.0ηc ηc, min ηc, min −Tz Tc, lower−Tc, upper Tc, lower ηc, min ηc (20)

= ( ) ; 0 ≤ ≤ 1.0ηh −Th, upper Tz−Th, upper Th, lower ηh (21)

= + ρ ( − )Q̇sys,h ηhQ̇h/c, max Cp V̇ min Tc/c Tz,pred,heat (22)

= ρ( ) ( − )Q̇sys,c Cp ηcV̇ max Tc/c Tz,pred,cool (23)

= + +Tz,pred,heatQ̇h/c,maxTh,upper

−Th,upper Th,lowerQ̇0

ρCp V̇ minTc/c

+ ρ +Q̇h/c,max

−Th,upper Th,lowerCp V̇ min Q̇slope

(24)

=Tz,pred,cool+B1 +B21 B2

− −−−−−−√2

(25)


where,

and,

Once the predicted zone air temperature has been calculated from Equations and , the air system response may be determined. When a zone requires cooling the systemsupply air temperature is constant at the cooling coil outlet temperature and the volume flow rate is given by:

where the supply air fraction hc is computed from Equation . When heating is required by the zone, the air system provides air at the minimum volume flow rate and at atemperature given by:

The reheat coil capacity fraction hh is determined by using Equation . Once Equation or , has been used, the supply air flow rate and temperature are known. These values arethen used in Equation to calculate the updated zone air temperature. The equations describing VAV system operation may be solved without iteration if the cooling coil outlettemperature is constant, i.e. if the coil has infinite capacity, and if the reheat coil capacity varies linearly with zone air temperature. This is not the case, either in practice or insimulations, when realistic coil models are used. Therefore, an iteration scheme was developed that solved these equations simultaneously with the coil performance models.

Moisture Predictor-CorrectorThe transient air mass balance equation for the change in the zone humidity ratio = sum of internal scheduled latent loads + infiltration + system + multizone airflows +convection to the zone surfaces may be expressed as follows:

where

C = humidity capacity multiplier (See the InputOutput Reference for additional information on the object ZoneCapacitanceMultiplier:ResearchSpecial)

In the same manner as described above for zone air temperature (ref. Basis for the Zone and Air System Integration), the solution algorithms provided in theZoneAirHeatBalanceAlgorithm object are also applied to zone air moisture calculations.

In order to calculate the derivative term with respect to time, the first order backward finite difference method, defined as the EulerMethod in the ZoneAirHeatBalanceAlgorithmobject, may be used:

The zone air humidity ratio update at the current time step using the EulerMethod may be expressed as follows:

To preserve the stability of the calculation of the zone humidity ratio, the third order differential approximation, derived by a Taylor Series and used in the calculation of the nexttime step’s zone air temperature, is also applied to the zone air humidity ratio calculations. This algorithm is the default choice and is defined as 3rdOrderBackwardDifference inthe ZoneAirHeatBalanceAlgorithm object.

The third order derivative derived from a Taylor Series expansion is defined as:

.

The coefficients of the approximated derivative are very close to the coefficients of the analogous Adams-Bashforth algorithm. Then the approximated derivative is substitutedinto the mass balance and the terms with the humidity ratio at past time steps are all put on the right hand side of the equation. This third order derivative zone humidity ratioupdate increases the number of previous time steps that are used in calculating the new zone humidity ratio, and decreases the dependence on the most recent. The higherorder derivative approximations have the potential to allow the use of larger time steps by smoothing transitions through sudden changes in zone operating conditions.

= + −B1 Tc/c Tc,lower−ηc,min C2C1

(26)

= 4 ( + ( − ))B2 C3C1

Tc/cηc,min

C1Tc,lower (27)

=C11 − ηc,min

−Tc,upper Tc,lower(28)

=C2Q̇slope

ρCp V̇ max

(29)

=C3Q̇0

ρCp V̇ max

(30)

=V̇ sup ply ηcV̇ max (31)

= +Tsup ply Tc/cηhQ̇h/c,max

ρCp V̇ min

(32)

= k + ( − ) + ( − )ρairVzCWdWz

dt∑i=1

Nsl

gmasssched load ∑i=1

Nsurfaces

Aihmiρairz Wsurfsi Wtz ∑

i=1

Nzones

ṁi Wzi Wtz

+ ( − ) + ( − )ṁinf W∞ W tz ṁsys Wsup W tz

(33)

W

= ( − ) +O(δt)dW

dt(δt)−1 W tz W t−δtz (34)

V ( − ) = k + ( − ) + ( − )ρair CW (δt)−1 W tz W

t−δtz ∑

i=1

Nsl


Nsurfaces

Aihmiρairz Wsurfsi Wtz ∑

i=1

Nzones

ṁi Wzi Wtz

+ ( − ) + ( − )ṁinf W∞ W tz ṁsys Wsup W tz

(35)

≈ +O(δ )dWzdt

∣∣∣t

( − 3 + − )116W tz W

t−δtz

32W t−2δtz

13W t−3δtz

δtt3 (36)

( ) + + + + = k +surfaces

i mi ai z i inf sys mas sched load

surfaces

i mi ai z surf i


This gives us the basic air mass balance equation that will be solved two different ways, one way for the predict step and one way for the correct step.

Since the third choice of solution algorithms uses an integration approach, defined as AnalyticalSolution in the ZoneAirHeatBalanceAlgorithm object, it does not require anyapproximations and has no truncation errors. The solutions in both prediction and correction are provided below in detail.

Moisture PredictionFor the moisture prediction case the equation is solved for the anticipated system response as shown below.

Since the program provides three solution algorithms, the moisture prediction from each solution algorithm is given below.

EulerMethodFor this solution algorithm, the air mass balance for the predicted air system load or response is:

ThirdOrderBackwardDifferenceFor this solution algorithm, the air mass balance for the predicted system load or response is given below:

Then, using the following substitutions, the air mass balance equation becomes:

AnalyticalSolutionFor this solution algorithm, the air mass balance for the predicted air system load or response is given below:

At the prediction point in the simulation, the system air mass flows are not known; therefore, the system response is approximated. The predicted air system moisture load isthen used in the system simulation to achieve the best results possible. The system simulation components that have moisture control will try to meet this predicted moistureload. For example, humidifiers will look for positive moisture loads and add moisture at the specified rate to achieve the relative humidity setpoint. Likewise, dehumidificationprocesses will try to remove moisture at the specified negative predicted moisture load to meet the relative humidity setpoint.

After the system simulation is completed the actual response from the air system is used in the moisture correction of step, which is shown next.

( ) + + + + = k +ρairVzCWδt

116W tz ∑

i=1

Nsurfaces

AihmiρairzWtz ∑

i=1

Nzones

ṁiWtz ṁinfW

tz ṁsysW

tz ∑

i=1

Nsl


Nsurfaces

AihmiρairzWsurfsi

+ + + − (−3 + − )∑i=1

Nzones

ṁiWzi ṁinfW∞ ṁsysWsupρairVzCW

δtW t−δtz

32W t−2δtz

12W t−3δtz

(37)

PredictedSystemLoad = ∗ ( − )ṁsys Wtz Wsup

MassFlow ∗ HumRat = =kgairseckgwaterkgair

kgwatersec

(38)

PredictedSystemLoad [k / sec] = ( − )gWater ρairVzCW (δt)−1 W tsetpoint W t−δtz−[ k + ( − ) + ( − ) + ( − )]∑

i=1

Nsl


Nsurfaces

Aihmiρairz Wsurfsi Wt

setpoint ∑i=1

Nzones

ṁi Wzi Wt

setpoint ṁinf W∞ Wt

setpoint(39)

PredictedSystemLoad [k / sec] = ( ( ) + + + ) −gWater ρairVzCWδt 116 ∑i=1

Nsurfaces

Aihmiρairz ∑i=1

Nzones

ṁi ṁinf Wtz

[ k + + + + (3 − + )]∑i=1

Nsl


Nsurfaces

AihmiρairzWsurfsi ∑i=1

Nzones

ṁiWzi ṁinfW∞ρairVzCW

δtW t−δtz

32W t−2δtz

13W t−3δtz

(40)

A = + +∑i=1

Nsurfaces

Aihmiρairz ∑i=1

Nzones

ṁi ṁinf (41)

B = k + + +∑i=1

Nsl


Nsurfaces


Nzones

ṁiWzi ṁinfW∞ (42)

C=ρairVzCW

δt(43)

PredictedSystemLoad [k / sec] = [ ∗C+A] ∗ −gWater 116 WSetPoint

[B+C ∗ (3 − + )]W t−δtz32W t−2δtz

13W t−3δtz

(44)

PredictedSystemLoad [k / sec] = [ + + ] ∗gWater ∑i=1

Nsurfaces

Aihmiρairz ∑i=1

Nzones

ṁiWzi ṁinf

− ∗ exp − δt ∗⎡⎣⎢⎢W tsetpoint W t−δtz

⎛⎝⎜⎜ + +∑i=1

Nsurfaces

Aihmiρairz ∑i=1

NzonesṁiWzi ṁinf

ρairVzCW

⎞⎠⎟⎟

⎤⎦⎥⎥

−1 − exp − δt⎡⎣⎢⎢

⎛⎝⎜⎜ + +∑i=1

Nsurfaces

Aihmiρairz ∑i=1

Nzonesṁi ṁinf

ρairVzCW

⎞⎠⎟⎟

⎤⎦⎥⎥

−1

( k + + )∑i=1

Nsl


Nsurfaces


Nzones

ṁiWzi ṁinfW∞

(45)


Moisture CorrectionFor the correct step the expanded air mass balance equation is solved for the final zone humidity ratio at the current time step. When the air system is operating, the mass flowfor the system outlet includes the infiltration mass flow rate, therefore the infiltration mass flow rate is not included as a separate term in the air mass balance equation. Butwhen the air system is off, the infiltration mass flow in is then exhausted out of the zone directly.

In the same manner as described above for predicting the moisture load to be met by the air system, the zone air moisture correction calculation will be described individuallyfor the three solution algorithms.

EulerMethod

ThirdOrderBackwardDifference

Using the same A, B, and C parameters from the prediction step modified with actual zone mass flows with the air system ON and OFF result in:

If (ZoneSupplyAirMassFlowRate > 0.0) Then

Else If (ZoneSupplyAirMassFlowRate

Carbon Dioxide Predictor-CorrectorThe transient air mass balance equation for the change in zone air carbon dioxide concentration may be expressed as follows:

where:

= sum of scheduled internal carbon dioxide loads. The zone air density is used to convert the volumetric rate of carbon dioxide generation from user input

into mass generation rate [kg/s].The coefficient of 10 is used to make the units of carbon dioxide as ppm.

= carbon dioxide transfer due to interzone air mixing [ppm-kg/s]

= carbon dioxide concentration in the zone air being transferred into this zone [ppm]

= carbon dioxide transfer due to infiltration and ventilation of outdoor air [ppm-kg/s]

= carbon dioxide concentration in outdoor air [ppm]

= carbon dioxide transfer due to system supply [ppm-kg/s]

= carbon dioxide concentration in the system supply airstream [ppm]

= air system supply mass flow rate [kg/s]

= carbon dioxide storage term in zone air [kg/s]

= zone air carbon dioxide concentration at the current time step [ppm]

= zone air density [kg/m ]

= zone volume [m ]

C = carbon dioxide capacity multiplier [dimensionless] (See the InputOutput Reference for additional information on the object ZoneCapacitanceMultiplier:ResearchSpecial)

In the same manner as described above for zone air temperature (ref. Basis for the Zone and Air System Integration), the solution algorithms provided in theZoneAirHeatBalanceAlgorithm object are also applied to the zone air carbon dioxide calculations.


The zone air carbon dioxide concentration update at the current time step using the EulerMethod may be expressed as follows:

To preserve the stability of the calculation of the zone carbon dioxide concentration, the third order differential approximation, derived by a Taylor Series and used in thecalculation of the next time step’s zone air temperature, is also applied to the zone air carbon dioxide calculations. This algorithm is the default choice and is defined asThirdOrderBackwardDifference in the ZoneAirHeatBalanceAlgorithm object.

The third order derivative derived from a Taylor Series expansion is defined as:

The coefficients of the approximated derivative are very close to the coefficients of the analogous Adams-Bashforth algorithm. Then the approximated derivative is substitutedinto the mass balance and the terms with the carbon dioxide concentration at past time steps are all put on the right-hand side of the equation. This third order derivative zonecarbon dioxide update increases the number of previous time steps that are used in calculating the new zone carbon dioxide concentration, and decreases the dependence onthe most recent. The higher order derivative approximations have the potential to allow the use of larger time steps by smoothing transitions through sudden changes in zoneoperating conditions.

This gives us the basic air mass balance equation that will be solved two different ways, one way for the predict step and one way for the correct step.


Carbon Dioxide PredictionFor the carbon dioxide concentration prediction case, the equation is solved for the anticipated system response as shown below.

Since the program provides three solution algorithms, the carbon dioxide prediction from each solution algorithm is given below.

EulerMethod

= k ∗ + ( − ) + ( − ) + ( − )ρairVzCCO2dCtzdt

∑i=1

Nsl

gmasssched load 1.06 ∑

i=1

Nzones

ṁi Czi Ctz ṁinf C∞ C

tz ṁsys Csup C

tz (56)

k∑i=1

Nsl

gmasssched load

6

( − )∑Nzonesi=1 ṁi Czi Ctz

Czi

( − )ṁinf C∞ Ctz

C∞

( − )ṁsys Csup Ctz

Csup

ṁsys

ρairVzdC tz

dt

Ctz

ρair 3

Vz 3

CO2

= ( − ) +O(δt)dCtzdt

(δt)−1 Ctz Ct−δtz (57)

( − ) = k ∗ + ( − ) + ( − ) + ( − )ρairVZCCO2(δt)−1 Ctz C

t−δtz ∑

i=1

Nsl

gmasssched load 106 ∑

i=1

Nzones

ṁi Czi Ctz ṁinf C∞ C

tz ṁsys Csup C

tz (58)

≈ +O(δ )dCtzdt

− 3 + −116Ctz C

t−δtz

32Ct−2δtz

13Ct−3δtz

δtt3 (59)

( ) + + + = k ∗ρairVzCCO2δt

116Ctz ∑

i=1

Nzones

ṁiCtz ṁinfC

tz ṁsysC

tz ∑

i=1

Nsl

gmasssched load 106

+ + + − (−3 + − )∑i=1

Nzones

ṁiCzi ṁinfC∞ ṁsysCsupρairVzCCO2

δtCt−δtz

32Ct−2δtz

13Ct−3δtz

(60)

PredictedSystemLoad = ( − )ṁsys Csup Ctz (61)


For this solution algorithm, the air mass balance for the predicted air system load or response is:



At the prediction point in the simulation, the system air mass flows are not known; therefore, the system response is approximated. The predicted air system carbon dioxideload is then used in the system simulation to achieve the best results possible. If a central HVAC system provides the outdoor flow rate from a Controller:MechanicalVentilationobject, the outdoor airflow rate may be approximated as:

where:

= supply outdoor airflow rate into the controlled zone [kg/s]

The above approximation is based on the assumption that the carbon dioxide concentration at the outdoor air (OA) mixer inlet is equal to the zone air outlet concentration level,and the carbon dioxide level at the zone supply air inlet is equal to the level at the outlet node of the OA mixer.

After the system simulation is completed the actual response from the air system is used in the carbon dioxide correction step, which is shown next.

Carbon Dioxide CorrectionFor the correct step the expanded air mass balance equation is solved for the final zone carbon dioxide concentration at the current time step. In the same manner asdescribed above for predicting the carbon dioxide load to be met by the air system, the zone air carbon dioxide correction calculation will be described individually for the threesolution algorithms.

EulerMethod


AnalyticalSolution

The above solutions are implemented in the Correct Zone Air Carbon Dioxide step in the Zone Contaminant Predictor Corrector module of EnergyPlus.

Generic Contaminant Predictor-Corrector

PredictedSystemLoad [kg/ sec] = ( − )ρairVZCCO2(δt)−1 Ctsetpoint Ct−δtz−[ k ∗ + ( − ) + ( − )]∑

i=1

Nsl


i=1

Nzones

ṁi Czi Ctsetpoint ṁinf C∞ C

tsetpoint

(62)

PredictedSystemLoad [kg/ sec] = [ ( ) + + ] ∗ρairVzCCO2δt

116

∑i=1

Nzones

ṁi ṁinf Ctsetpoint

−[ k ∗ + + + (3 − + )]∑i=1

Nsl


i=1

Nzones

ṁiCzi ṁinfC∞ρairVzCCO2

δtCt−δtz

32Ct−2δtz

13Ct−3δtz

(63)

PredictedSystemLoad [kg/ sec] = [ + ] ∗ − ∗ exp − δt ∗∑i=1

Nzones

ṁi ṁinf

⎡⎣⎢Ctsetpoint Ct−δtz

⎛⎝⎜

+∑i=1

Nzonesṁi ṁinf

ρairVZCCO2

⎞⎠⎟

⎤⎦⎥

− ( k ∗ + + )1 − exp − δt⎡⎣⎢⎛⎝⎜

+∑i=1

Nzonesṁi ṁinf

ρairVZCCO2

⎞⎠⎟

⎤⎦⎥

−1

∑i=1

Nsl


i=1

Nzones

ṁiCzi ṁinfC∞

(64)

PredictedSystemLoad = ( − ) ≈ ( − )ṁsys Csup Ctz ṁOA,z C∞ Ctsetpoint (65)

ṁOA,z

=Ctz

k ∗ + + + +∑i=1

Nsl


i=1

Nzones

ṁiCzi ṁinfC∞ ṁsysCsup ρairVZCCO2C t−δtz

δt

+ + +ρairVZCCO2δt

∑i=1

Nzones

ṁi ṁinf ṁsys

(66)

=Ctz

k ∗ + + + + (3 − + )∑i=1

Nsl


i=1

Nzones

ṁiCzi ṁinfC∞ ṁsysCsupρairVZCCO2

δtCt−δtz

32Ct−2δtz

13Ct−3δtz

( ) + + +ρairVZCCO2δt

116

∑i=1

Nzones

ṁi ṁinf ṁsys

(67)

= − ∗ exp − δt +Ctz⎡⎣⎢⎢C

t−δtz

k ∗ + + +∑i=1

Nslgmasssched load

106 ∑i=1

NzonesṁiCzi ṁinfC∞ ṁsysCsys

+ +∑i=1

Nzonesṁi ṁinf ṁsys

⎤⎦⎥⎥

⎛⎝⎜

+ +∑i=1


ρairVZCCO2

⎞⎠⎟

k ∗ + + +∑i=1

Nslgmasssched load

106 ∑i=1

NzonesṁiCzi ṁinfC∞ ṁsysCsys

+ +∑i=1


(68)


The transient air mass balance equation for the change in zone air generic contaminant concentration may be expressed as follows:

where:

= Sum of internal generic contaminant loads from sources in a zone or interior surfaces.

The zone air density is used to convert the volumetric rate of generic contaminant generation from user input into mass generation rate [kg/s].The coefficient of 10 is used tomake the units of generic contaminant as ppm.

= Sum of removal rate from sinks in a zone or interior surfaces [ppm-kg/s]

= Generic contaminant transfer due to interzone air mixing [ppm-kg/s]

= Generic contaminant concentration in the zone air being transferred into this zone [ppm]

= Generic contaminant transfer due to infiltration and ventilation of outdoor air [ppm-kg/s]

= Generic contaminant concentration in outdoor air [ppm]

= Generic contaminant transfer due to system supply [ppm-kg/s]

= Generic contaminant concentration in the system supply airstream [ppm]

= Air system supply mass flow rate [kg/s]

= Generic contaminant storage term in zone air [ppm-kg/s]

= Zone air generic contaminant concentration at the current time step [ppm]

= Zone air density [kg/m ]

= Zone volume [m ]

= Generic contaminant transport through diffusion between interior surfaces and zone air

= Generic contaminant generation or removal rate as a function of zone air generic contaminant level at the previous time step

Mfor = Generic contaminant capacity multiplier [dimensionless] (See the InputOutput Reference for additional information on the objectZoneCapacitanceMultiplier:ResearchSpecial)

In the same manner as described above for zone air temperature (ref. Basis for the Zone and Air System Integration), the solution algorithms provided in theZoneAirHeatBalanceAlgorithm object are also applied to the zone air carbon dioxide calculations.


The zone air generic contaminant concentration update at the current time step using the EulerMethod may be expressed as follows:

To preserve the stability of the calculation of the zone generic contaminant concentration, the third order differential approximation, derived by a Taylor Series and used in thecalculation of the next time step’s zone air temperature, is also applied to the zone air carbon dioxide calculations. This algorithm is the default choice and is defined asThirdOrderBackwardDifference in the ZoneAirHeatBalanceAlgorithm object.

The third order derivative resulting from a Taylor Series expansion is defined as:

The coefficients of the approximated derivative are very close to the coefficients of the analogous Adams-Bashforth algorithm. Then the approximated derivative is substitutedinto the mass balance, and the terms with the carbon dioxide concentration at past time steps are all put on the right-hand side of the equation. This third order derivative zonecarbon dioxide update increases the number of previous time steps that are used in calculating the new zone generic contaminant concentration and decreases thedependence on the most recent. The higher order derivative approximations have the potential to allow the use of larger time steps by smoothing transitions through suddenchanges in zone operating conditions.

= ∗ − + ( − ) + ( − )ρairVzMfor dCtf,z

dt∑i=1

Nsource

ρairGf,i 1.06 ρair ∑i

NsinkRf,iCf,z ∑

i=1

Nzones

ṁi Cf,z,i Ctf,z ṁinf Cf,∞ C

tf,z

+ ( − ) + ρ ( − ) + ( )ṁsys Cf,sup Ctf,z ∑j

hj AjCs,j

kjCf,z Sf C

t−δtf,z

(69)

∑i=1

Nsource

ρairGf,i

6

ρair ∑i

NsinkRf,iCf,z

( − )∑Nzonesi=1 ṁi Cf,z,i Ctf,zCf,z,i

( − )ṁinf Cf,∞ Ctf,zCf,∞

( − )ṁsys Cf,sup Ctf,zCf,sup

ṁsys

ρairVzdC tf,z

dt

Ctf,z

ρair 3

Vz 3

ρ ( − )∑j

hj AjCs,j

kjCf,z

( )Sf Ct−δtf,z

= ( − ) +O(δt)dCt

f,z

dt(δt)−1 Ct

f,z Ct−δtf,z (70)

( − ) = ∗ − + ( − )ρairVzMfor (δt)−1 Ctf,z Ct−δtf,z ∑i=1

Nsource


NsinkRf,iCf,z ∑

i=1

Nzones

ṁi Cf,z,i Ctf,z

+ ( − ) + ( − ) + ρ ( − ) +ṁinf Cf,∞ Ctf,z ṁsys Cf,sup Ctf,z ∑j

hj AjCs,j

kjCf,z Sf

(71)

≈ +O(δ )dCt

f,z

dt

− 3 + −116Ctf,z C

t−δtf,z

32Ct−2δtf,z

13Ct−3δtf,z

δtt3 (72)

( ) + + + + + ρairNsink

f,izones

i inf sys j jEnergyPlus Documentation Page 23 of 847

This gives us the basic air mass balance equation that will be solved in two different ways, one way for the predict step and one way for the correct step.


Generic Contaminant PredictionFor the generic contaminant concentration prediction case, the equation is solved for the anticipated system response as shown below.

Since the program provides three solution algorithms, the generic contaminant prediction from each solution algorithm is given below.

EulerMethodFor this solution algorithm, the air mass balance for the predicted air system load or response is:



At the prediction point in the simulation, the system air mass flows are not known; therefore, the system response is approximated. The predicted air system genericcontaminant load is then used in the system simulation to achieve the best results possible. If a central HVAC system provides the outdoor flow rate from aController:MechanicalVentilation object, the outdoor airflow rate may be approximated as:

where:

= Supply outdoor airflow rate into the controlled zone [kg/s]

The above approximation is based on the assumption that the generic contaminant concentration at the outdoor air (OA) mixer inlet is equal to the zone air outlet concentrationlevel, and the generic contaminant level at the zone supply air inlet is equal to the level at the outlet node of the OA mixer.

After the system simulation is completed, the actual response from the air system is used in the generic contaminant correction step, which is shown next.

Generic Contaminant Correction

( ) + + + + + ρρairVzMfor

δt

116Ctf,z ρair ∑

i

NsinkRf,iC

tf,z ∑

i=1

Nzones

ṁiCtf,z ṁinfC

tf,z ṁsysC

tf,z ∑

j

hj AjCtf,z

= ∗ + + + + ρ +∑i=1

Nsource

ρairGf,i 1.06 ∑i=1

Nzones

ṁiCf,z,i ṁinfCf,∞ ṁsysCf,sup ∑j

hj AjCs,j

kjSf

− (−3 + − )ρairVzMforδt

Ct−δtf,z

32Ct−2δtf,z

13Ct−3δtf,z

(73)

PredictedSystemLoad = ( − )ṁsys Cf,sup Ctf,z (74)

PredictedSystemLoad [kg/ sec] = ( − )ρairVzMfor (δt)−1 Csetpoint Ct−δtf,z−[ ∗ − + ( − ) + ]∑

i=1

Nsource


NsinkRf,iCsetpoint ∑

i=1

Nzones

ṁi Cf,z,i Csetpoint Sf

−[ ( − ) + ρ ( − )]ṁinf Cf,∞ Csetpoint ∑j

hj AjCs,j

kjCsetpoint

(75)

PredictedSystemLoad [kg/ sec] = ( ) − [ + + ]ρairVzMforδt

116Csetpoint ρair ∑

i

NsinkRf,iCsetpoint ∑

i=1

Nzones

ṁiCsetpoint ṁinfCsetpoint

−[ ρ + ∗ + + + ρ + ]∑j

hj AjCsetpoint ∑i=1

Nsource


Nzones

ṁiCf,z,i ṁinfCf,∞ ∑j

hj AjCs,j

kjSf

+ (−3 + − )ρairVzMforδt

Ct−δtf,z

32Ct−2δtf,z

13Ct−3δtf,z

(76)

PredictedSystemLoad [kg/ sec] = [ + + + ρ ] ∗∑i=1

Nzones

ṁi ṁinf ρair ∑i

Nsink

Rf,i ∑j

hj Aj

− ∗ exp − δt ∗⎡⎣⎢⎢C

tsetpoint C

t−δtz

⎛⎝⎜⎜

+ + + ρ∑i=1

Nzonesṁi ṁinf ρair ∑

i

NsinkRf,i ∑

j

hj Aj

ρairVZMFOR

⎞⎠⎟⎟

⎤⎦⎥⎥

−1 − exp − δt⎡⎣⎢⎢

⎛⎝⎜⎜

+ + + ρ∑i=1

Nzonesṁi ṁinf ρair ∑

i

NsinkRf,i ∑

j

hj Aj

ρairVZMFOR

⎞⎠⎟⎟

⎤⎦⎥⎥

−1

( ∗ + + + ρ + )∑i=1

Nsource


Nzones

ṁiCf,z,i ṁinfCf,∞ ∑j

hj AjCs,j

kjSf

(77)

PredictedSystemLoad = ( − ) ≈ ( − )ṁsys Cf,sup Ctf,z ṁOA,z Cf,∞ Ctsetpoint (78)

ṁOA,z


For the correct step, the expanded air mass balance equation is solved for the final zone generic contaminant concentration at the current time step. In the same manner asdescribed above for predicting the carbon dioxide load to be met by the air system, the zone air carbon dioxide correction calculation will be described individually for the threesolution algorithms.

EulerMethod


AnalyticalSolution

The above solutions are implemented in the Correct Zone Air Generic Contaminant step in the Zone Contaminant Predictor Corrector module of EnergyPlus.

Zone Air Mass Flow ConservationThe zone air mass flow conservation object is intended to trigger zone air mass flow balance calculations. This feature is available for zones defined in an air loop only andrequires that zone mixing objects is defined. If there are no zone mixing flows to adjacent zones, then the zone air mass flow is balanced by setting the Zone Mixing objectsmass flow rate to zero. If there are no zone exhaust fans defined and there are no zone mixing objects specified, then a zone in an air loop is always balanced. The zonesimple flow objects (ventilation, ZoneCrossMixing etc.) with exception of zone mixing and infiltration are assumed to be self-balanced hence are not included in the zone airmass flow conservation calculation. Infiltration objects air mass flow is included in the zone air mass flow balance of zones that serve only as a source zone of zone mixingobjects. And the infiltration mass flow rate used may be adjusted from the value calculated based on user inputs for zone air mass flow balance purpose. The zone air massflow conservation equation includes: supply air flow rates, return air flow rates, zone exhaust fan flow rates, zone mixing objects flow rates and infiltration object flow rates.However, infiltration objects air mass flow rate are used to balance source zones only. Infiltration air mass flow is included in the zone air mass flow conservation only when thesource zone supply air flow rate is not large enough to offset the source mass flow rate. A particular zone can be a source zone, receiving zone, or both depending on thenumber of ZoneMixing objects specified for that zone. Zone air mass flow balance calculation is performed when user specifies an optional object “ZoneAirMassFlowBalance”and set the input field “Adjust Zone Mixing For Zone Air Mass Flow Balance ” to “Yes” and zones have at least one ZoneMixing object defined. A zone may have multiplezone mixing objects connecting adjacent zones. Zone air mass flow balance calculation is two steps procedure. The modified return air mass flow rate calculation is given by:

where,

= zone return air mass flow rate, (kg/s)

= zone exhaust air mass flow rate from exhaust fans, (kg/s)

= zone mixing mass flow rate as a receiving zone, (kg/s)

= zone mixing mass flow rate as a source zone, (kg/s)

= zone supply air mass flow rate, (kg/s)

Figure 8 illustrates the zone mass flow components for an air loop system providing conditioned air to the two zones connected with a zone mixing object. Since Zone 1 is asource zone only, infiltration object is defined for zone 1 only. The zone mixing object air flow rate depends on the user specified values and the zone air mass flow balancerequirements. When required the zone mixing object flow rate is adjusted from the user specified value for balancing purpose.

=Ctf,z

∗ + + + + ρ + +∑i=1

NsourceρairGf,i 1.0

6 ∑i=1

NzonesṁiCf,z,i ṁinfCf,∞ ṁsysCf,sup ∑

j

hj AjCs,j

kjρairVZMFOR

Ct−δtf,z

δtSf

+ + + + + ρρairVzMfor (δt)−1 ρair ∑

i

NsinkRf,i ∑

i=1

Nzonesṁi ṁinf ṁsys ∑

j

hj Aj

(79)

=Ctf,z

∗ + + +∑i=1


6 ∑i=1

NzonesṁiCf,z,i ṁinfCf,∞ ṁsysCf,sup

+ ρ + (3 − + )+∑j

hj AjCs,j

kj

ρairVZMFOR

δtC t−δtf,z

32C t−2δtf,z

13C t−3δtf,z Sf

( )+ + + + + ρρairVzMfor (δt)−1 116 ρair ∑i

NsinkRf,i ∑

i=1

Nzonesṁi ṁinf ṁsys ∑

j

hj Aj

(80)

= − ∗Ctf,z

⎡⎣⎢⎢C

t−δtf,z

∗ + + + + ρ∑i=1


6 ∑i=1

NzonesṁiCf,z,i ṁinfCf,∞ ṁsysCf,sys ∑

j

hj AjCs,j

kj

+ + + + ρ∑i=1

Nzonesṁi ṁinf ṁsys ρair ∑

i

NsinkRf,i ∑

j

hj Aj

⎤⎦⎥⎥

exp − δt +⎡⎣⎢⎢

+ + + + ρ∑i=1


i

NsinkRf,i ∑

j

hj Aj

ρairVZMFOR

⎤⎦⎥⎥

∗ + + + + ρ +∑i=1


6 ∑i=1

NzonesṁiCf,z,i ṁinfCf,∞ ṁsysCf,sys ∑

j

hj AjCs,j

kjSf

+ + + + ρ∑i=1


i

NsinkRf,i ∑

j

hj Aj

(81)

=MAX(0.0, + − − )ṁR ṁS ṁXR ṁEX ṁXS (82)

ṁR

ṁEX

ṁXR

ṁXS

ṁS


Figure 8. Illustration of zone air mass flow balance components

Individual zone may be a source zone for multiple receiving zones, and at the same time the same source zone may receive mixing flows from multipl

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