Ben Larson31 October 2011

ben@ecotope.com4056 9th Avenue NE, Seattle, WA 98105(206) 322-3753 Fax: (206) 325-7270

Simulation models and history in the PNW Why the RTF uses SEEM

SEEM capabilities overviewRunning SEEMOutputs Inputs with examplesExample RTF measuresSEEM calibrationFuture plans for SEEM

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Modeling Residential Building Performance

Models not predictive Mathematical tool to describe the

interaction components of the building Describe physical relationship between the

determinants of consumption Space conditioning especially heating Building heat loss and heat gain Impact of occupant behavior Thermostat controlled loads Climate

Simulations not meant to describe or predict occupant behavior Appliances and plug loads notoriously

challenging4

PNW has used building energy simulation tools for energy planning since the first power plan

Larry Palmiter came to the region to develop a state of the art residential heating/cooling and solar model, SUNCODE

Early in this process a planning tool was needed to run fast and describe residential heating with a minimum number of inputs: SUNDAY

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“Daily” simulation using the minimum information necessary

Allowed quick assessment of space heating measures and interactions that determine heating

Not designed to assess heating system delivery

Not able to correctly model coolingRequired side calculations to handle

these effects and other loads

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An even faster correlation program: WATTSUN

Allowed very quick correlation look-up Added calculations not in simulation Heating equipment efficiency Duct efficiency Other loads

REMRATE uses a similar approach (although the look-up tables were developed from SUNCODE to be used in individual homes)

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The region needed capabilities not in Sunday/Wattsun Cooling load estimates Simulation of heat pump and AC equipment Duct sealing and duct efficiency impacts Ventilation interactions

SEEM developed around a similar concept to SUNDAY Minimum inputs to get an accurate answer Simplified inputs that allow parameter studies Direct platform to integrate findings from field

work, lab testing, and calibration exercises No direct simulation of occupancy based loads

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Developed beginning in 2003 by Larry Palmiter Passed to Ben Larson in 2008. Updates in 2011 carried out by Michael Logsdon. Funded initially by NEEA and the NPCC Enhanced with a consortium of regional energy

offices led by Idaho (funded by USDOE) Enhanced with funding from BPA, NEEA and RTF Current version SEEM92 (.92) reflects all these

upgrades. Ongoing efforts to add capabilities:

Ventilation systems Scheduling of internal gains Better user template

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Allows direct simulation of heating and cooling measures Insulation and heat loss rate Building HVAC equipment

▪ Heat pump▪ A/C▪ Ducting sealing▪ Delivery efficiency

Parameterize measures for comparison in conservation supply curves

Direct calibration to empirical field data and lab testing

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Calculates annual building heating and cooling energy use Developed specifically for single family residential

buildings Single zone model (treats the conditioned space as one big

room) Also appropriate for small-scale multi-family construction

including townhouses and 3-5 story flats

Differentiating features: Empirically derived heat pump performance maps

▪ Multiple control strategy possibilities Full duct model include losses to and regain from buffer spaces Ground contact heat transfer based on ISO standard handles many

types of construction and insulation Input and output via CSV file allows for large parametric studies and

flexible analysis11

Simple Energy Enthalpy Model

Pairwise Comparisons Compare proposed building against a base case for

compliance purposes Single Building Studies (1 to 50 runs)

Examine multiple measures for best energy savings opportunities and cost effectiveness

Medium Scale Studies (50 to 1,000 runs) Writing TCOs for NW Energy Star program Regional window retrofit measure

Large Scale Studies (5,000 to 500,000 to 1M+) Power Council 6th Power Plan Residential Sector Generate and analyze runs with scripts

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Provide enough information to start modeling a generalized building population Suitable for comparing codes and

standards or determining savings values for a conservation program

Interpret SEEM output In-depth explanation of developing

simulation inputs

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Taking 66 inputs, SEEM calculates the building heating and cooling loads, including humidity effects, at hourly intervals to determine annual energy use.

SEEM accounts for: Weather conditions using TMY data (1500 unique sites

available)▪ Including solar gains and humidity

Internal heat and moisture gains Heat and moisture loss to buffer spaces through

conduction and duct leakage Heat loss to the exterior Heat Pump COP (Coefficient of Performance)

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SEEM accurately models both air temperature and mean radiant temperature

SEEM offers state of the art modeling of heat pumps and air-conditioners including thermostat setup penalty and heat pump controls Empirically derived performance maps for HP and A/C

included Multiple equipment control strategy possibilities

Complete psychrometrics implementation includes Water balance on all zones: attic, crawl, and conditioned

space User input for internal water gains Calculation of latent cooling load

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SEEM accounts for duct losses and their impact on all zones/buffer spaces

SEEM calculates ground heat transfer to estimate the overall 3-dimensional U-value. Slab-on-grade

▪ Full under slab insulation (interior insulation also modeled)▪ Perimeter insulation with user determined depth

Crawl spaces, Unheated and Heated basements▪ Allows different wall types for above and below grade

components Multi-level buildings are modeled with

independent input of conditioned floor area, volume, footprint area, ceiling area, and external (i.e. cantilevered or over garage) floor area

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Currently does not directly model ventilation interactions

Currently does not model occupancy schedule except Tstat setback

Interface does not have a menu of pre-determined, selectable inputs

Single zone model coupled w/ buffer spaces House energy uses such as lighting, DHW,

etc. require add’l engineering calculations Certain inputs, ex: Qgains, require add’l

engineering calculations

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SEEM is a calculation engineYou are the model(er)Output is only as good as the inputYou are responsible for setting the

proper baseline, assigning the correct inputs, and doing any simulation post-processing

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Under the hood - Uses input.csv file & output.csv text files

On top - Excel spreadsheet integration Contains input and output within one workbook Easy to edit parameters Flexible for analysis & fully customizable

▪ User can create additional calculations for DHW, lighting, etc

▪ Easy to integrate with graphs or other tables

aa_copy_me_seem92.xls▪ Excel workbook needs to know where SEEM is on your

computer▪ “Locate SEEM” button

Example: ex1-nwcities.xls 19

UATotal (Btu/hr F) calculated UA Total UA from house to outside and ground including air infiltration.

HDD65 (°D)° Heating Degree Days Base 65 Heating degree days base 65 for input climate

CDD65 (°D) Cooling Degree Days Base 65 Cooling degree days base 65 for input climate

Pressure (atm) Site pressure in std atmospheres Can be used to correct for altitude effects on mass flow

RoomHeatkWh (kWh) Annual house heating load Heat which must be delivered to house (conditioned zone)

EquipHeatkWh (kWh) Annual heating equipment output Heat supplied by equipment into the duct system. The number includes the effects of duct losses and fan heat. Includes all auxheat.

InHeatkWh (kWh) Annual heating equipment input Site energy required to produce equipheat. Includes the effects of equip. eff., duct losses, and fan energy. Includes all auxheat.

AuxHeatkWh (kWh) Annual electric strip heat Used for heat pumps when compressor not meeting load

FanHeatkWh (kWh) amount of energy used by the fan This heat is included in equipheat. The fanheat is equal to the fan input power.

FanHeathrs (hr) total fan run time in heating mode Equals the equipment runtime in heating mode.

RoomCoolkWh (kWh) annual house cooling load Cool which must be delivered to house (conditioned zone)

EquipCoolkWh (kWh) annual cooling equipment output Cool supplied by equipment into duct system. Includes the effects of duct losses and fan heat.

InCoolkWh (kWh) annual cooling equipment input Site energy required to produce equipcool. Includes effects of equip. eff., duct losses, and fan energy.

QLatentkWh (kWh) annual latent load in cooling mode Amount of input energy used in cooling mode to meet latent load

LatentPct % percent of cooling due to latent load  

AuxCoolkWh (1 or 0) auxiliary cooling #hrs cooling set point not met20

Determine energy differences between buildings Need a base case Need one (or multiple) proposed case

Prototype building Building dimensions generally stay the same –

measures such as insulation, duct leakage, equipment change between runs

Example: ex2-windows.xls 2200ft2 Prototype - current average U.S. house size Split level house w/ some second floor space above

garage Double Triple pane window comparison

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Run: label, weather, hourly output Occupancy: thermostat (temperature, time, &

setback), internal heat and moisture gains Equipment: type, size, control strategy Duct: location, leakage, insulation Envelope: areas, volumes, insulation, windows

(including orientation, shading, SHGC) Foundation: type, area, perimeter, insulation Infiltration: ACH for house, attic, and crawl

Definitions in seem92_csv_inout.xls

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Run Label – Descriptive name of particular simulation. Can be used to identify which measures are used in that run.

Weather Name – name of weather file. Ex: IDBoise3 or WASpokane3 uses the TMY3 weather data for those cities.

Hourly Out – flag to produce hourly output for hottest and coldest day in a “.SEEM” file for each run (useful for testing and verification)

OutputMonth and Output Day – user settable output day to be included in .SEEM file

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Entered as State-City-tmytype: ORPortland3 Linked to Weather data files

The NW regional weather zones used in many analyses are compiled from a percentage of PNW typical climates:

Location Climate DataHeating Zone Weight Data

Heating Zone 1 20% 50% 15% 15% 0% 100%Heating Zone 2 0% 0% 85% 10% 5% 100%Heating Zone 3 0% 0% 0% 0% 100% 100%

PNW Region 20% 40% 15% 20% 5% 100%Heating Degree Days Base 65 4187 4641 6716 5396 7828

Location Climate DataCooling Zone Weights

Cooling Zone 1 5% 80% 0% 0% 15% 100%Cooling Zone 2 35% 0% 55% 10% 0% 100%Cooling Zone 3 0% 0% 0% 100% 0% 100%

PNW Region 35% 25% 20% 15% 5% 100%Cooling Degree Days Base 65 367 128 341 756 127

Region

Portland Seattle Spokane Boise Kalispell Region

Portland Seattle Spokane Boise Kalispell

Theathi – occupied T set point Theatlo – unoccupied/setback set point Hrheathi – hour to start occ. mode Hrheatlo – hour to start unocc. mode Tcoollo, Tcoolhi, hrcoolhi, hrcoollo – similar to above but

for cooling Setback – 1 or 0 to use setback or not

▪ For electric forced air furnace and electric zonal resistance use 66F heating set point w/ no setback (RTF decision, November 2009)http://www.nwcouncil.org/energy/rtf/meetings/2009/11/Default.htm

Typical Thermostat Setup ValuesTheathi Theatlo hrheathi hrheatlo Setback

(F) (F) (hr) (hr) (1 or 0)70 64 6 22 1

Tcoollo Tcoolhi hrcoolhi hrcoollo (F) (F) (hr) (hr) 74 78 9 17

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#1 input to get right in modeling Qgains – internal heat gains (Btu/hr). Sources include:

▪ Lighting – can be a simple calc using LPD and assuming ~1.5 hrs per day annual use

▪ Appliances – depends on appliances in use▪ People – numbers in ASHRAE Fundamentals▪ Plug loads – largest unknown

Wgains – internal water gains (lbs/hr). Sources include:▪ People, pets, showers, cooking, aquariums, etc.

Effects indoor RH and latent cooling load Suggest 0 or 0.5 lbs/hr 26

Example: ex3-gains.xlsPrototype: 2200 ft2

Envelope: NWBOP1Equipment: Gas Furnace AFUE 90Explore impact of lighting levels on

gains and energy use in Spokane Lighting levels: All incandescent, 50%

CFLs, 75% CFLs, 90% CFLs

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Equiptype – furnace, heat pump, or furnace and A/C combination Internally, SEEM assumes an electric furnace

with COP of 1. To model a gas furnace with AFUE 80, divide inheatkwh output by 0.8.

Common values:▪ Current Codes: 7.7/13▪ EnergyStar: 8.5/13

To get a value not listed in the table, interpolated between independent runs

Furnace A/C Combinations:▪ FYKC, FHPA, FHCA, FYSA

Example: ex4-equip.xls

Heat Pump OptionsLabel HSPF SEERYKC 7.2 10

HPA3 8 13HCA3 7.9 13YSA 9 14.5

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Tons – size of heat pump or air conditioner Typical range: 2-4 tons

▪ If sized too small, more electric resistance auxiliary heat is used and cooling load may not be met.▪ hrsetptmissed output

▪ If sized too large, a part load cycling penalty is incurred Furnsize – elec furnace size in kW.

Input not critical as SEEM will by default provide “missing” heat at COP of 1.

CFMmult – air handler flow multiplier Used to model low or high flow and to correct for

air mass flow at altitude (see documentation) Suggest leaving at 1.

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HPcntrl – heat pump control strategy Tcntrl – temperature associated with strategy NW Regional Control Strategies:

Base Case and PTCSHeat Pump Baseline Control Strategy Matrix

Weight HPcntrl Tcntrl Description

0.4 0 30ARI standard control, if you aren't meeting setpoint within

3degF, turn on auxiliary electric

0.15 1 30Compressor lockout if outside temp is below temp (Tcntrl),

turn on electric only.

0.05 2 40Auxiliary heat lockout, compressor runs at reduced capacity

(Tout<Tcntrl)0.15 3 30 strip heat on with compressor if Tout<Tcntrl (30 deg)0.25 3 50 strip heat on with compressor if Tout<Tcntrl (50 deg)

Heat Pump PTCS Control Strategy MatrixWeight HPcntl Tcntrl Description

0.1 0 30ARI standard control, if you aren't meeting setpoint within

3degF, turn on auxiliary electric

0.9 2 40Auxiliary heat lockout, compressor runs at reduced capacity

(Tout<Tcntrl)30

Perfect – (1 or 0) no duct leakage or conduction losses

SDloc, RDloc – supply and return duct location: Attic, Crawl, In, Out

SDarea, RDarea – supply and return duct surface area in buffer spaces

SDRval, RDRval – true R-value of duct insulation. Round duct / flex duct nominal R-value is not true R-value:

Actual R-values of Round Duct R nominal 4.2 6 8 11

Nominal Duct Diameter (in)

Actual Duct Area (ft2 per

ft length)R actual

4 1.05 3.13 4.08 4.97 6.096 1.57 3.41 4.53 5.62 7.038 2.09 3.57 4.8 6.04 7.66

10 2.62 3.67 4.99 6.33 8.12 31

SDLF, RDLF – Supply and Return Duct Leakage Fraction (0-100%).

Typically model supplies in the crawl space and returns in the attic

Manufactured homes typically modeled with no return leaks

Houses with basements typically have reduced duct leakage

Example: ex5-ductlosses.xls

Typical Duct Leakage Values Supply ReturnNW Existing 15% 10%NW New Construction 12% 10%NW EnergyStar (sealed) 6% 3%

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Units: Perimeter, Area, Volume in: ft, ft2, ft3

Insulation inputs – overall air-to-air R-value (inverse of the U-value). ▪ Values for walls can often be looked up in code or spec

tables.▪ Super Good Cents Heat Loss Reference Manual▪ ASHRAE Fundamentals Handbook▪ IECC Code Tables

▪ Values for ceilings and floors aren’t as straight forward because SEEM directly calculates buffer space effects

▪ Values can be found in the “docs\” folder of the distribution

SEEM_insulation_lookup_tables.xls33

Afloorcond – house conditioned floor area Volume – house volume Afloorext – floor area over

unconditioned space Rfloorext

Aextwall – gross exterior wall area Rextwall

Aceiling – ceiling area exposed to attic. Sum of Afootprint and Afloorext Rceiling

ABSroof – roof solar absorptivity. Depends on color and cleanness. Suggest 0.85.

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AwinN, AwinE, AwinS, AwinW – window area for each cardinal direction

Uwindow – NFRC U-value for window Example: ex6-windows_5climate.xls

SHGC – NFRC solar heat gain coefficient value Shading – (o to 1) fractional value to account for

shading: External: trees, landscaping, adjacent buildings Internal: (delete)and curtains, blinds, furnishings 0.5 – 0.65 is reasonable. Suggest 0.54.

Adoor – total door area Rdoor

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Foundtype – crawl space, slab, unheated basement, heated basement

Afootprint – area of house at grade

Pfloor – perimeter of house at grade

Rfloor – wood floor insulation value between house and crawl space

Rslabins – R-value of insulation underlying entire slab (if slab fully insulated)

Rcarpet – R-value of interior floor finishes

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Edgetype – perimeter slab insulation Horizontal Vertical None

EdgeDepth – depth of edge insulation Typically: 2 ft, 4ft

Redgeins – R-value of edge insulation

SoilCond – site soil conductivity Typically 0.7-0.8 Btu / ftFhr but can

very greatly depending on site Suggest 0.75

Vertical Edge Insulation:

Horizontal Edge Insulation:

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Crawl space or basement wall characteristics HeightAG RwallAG HeightBG RwallBG

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ACHHouse – infiltration in natural air changes per hour Includes natural and fan forced ventilation ERVs can be modeled but adjustments need to be made to

infiltration rate based on equipment efficiency Approximate blower door test conversion:

▪ 7ACH@50Pa / 20 ~ 0.35 ACH natural

ACHAttic – 4.5, typical for vented attic ACHCrawl – 4.5, typical for vented crawl

House ACH ValuesTypical existing stock 0.45

Typical new construction 0.35Energy Star NWBOP1 0.35

WA Code 2010 Proposal 0.3Energy Star NWBOP2 0.2

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(Adam’s Components)

May 31st , 2011

Example Runs of RTF Deemed Measures Duct Savings Heat Pump Savings Insulation Others

SEEM Calibration Calibration methodology

▪ Compare modeling output to metered data RTF-approved calibrations

▪ SF Weatherization (Adam demonstration) Future Needs

▪ Manufactured Homes

In general, for each measure Each prototype has its own set of pre-determined “fully weatherized” SEEM

inputs Very few (one or two) SEEM inputs are changed to create a pre- and post- run Savings are calculated for all iterations of prototypes, climate zones, and

sometimes heating system types, and weighted appropriately. Depending on the number of measures, the number of SEEM runs can get huge (especially with heat pumps)

Standard Prototypes Single Family

▪ 1344 ft2 on crawlspace▪ 2200 ft2 on crawlspace▪ 2688 ft2 on basement

Manufactured Homes… Multifamily… Note: For some measures, the standard prototypes are adjusted or new ones

are created▪ Examples: Large house for GSHP’s, slab foundation for slab insulation measures.

Climate Zones Portland Seattle Spokane Boise Kalispell

See this link for all the details of the single family SEEM runs (big file)

Primary SEEM Variables SDleak

▪ Pre: 15%▪ Post: 10%

RDleak▪ Pre: 5%▪ Post: 3%

Primary SEEM Variable Equiptype$

▪ Pre: HPA3▪ Post: YSA

Since YSA = HSPF 9.0 / SEER 14.5 and measure requires HSPF 9.0 / SEER 14.0, a simple ratio of SEER’s is applied to cooling energy use.

Heat pump measures involve the weighting of 5 control strategies (SEEM variables: HPcntrl and Tcntrl), so there are 5-times as many heat pump runs as other measures.

R19 to R-38 Attic Insulation Primary SEEM Variable

▪ Rceiling▪ Pre: 19.6▪ Post: 35.0

R-19 to R-30 Floor Insulation Primary SEEM Variable

▪ Rfloor▪ Pre: 22.0▪ Post: 30.6

Goal: Calibrate model using input assumptions that match real-world billing data.

Calibration: Where disagreement between SEEM and Real-World, turn ONLY the “knobs” that apply.

Example: Single Family Weatherization SEEM Runs Calibration Billing Data from 3 studies. Result: Adjusting SEEM inputs for the heating temperature setpoints to the following

resulted in a reasonable match:▪ Heat Pumps and Gas FAF:

▪ 70 degrees daytime▪ 64 degree night setback▪ Justification: Allows modeling of a night time setback for heat pumps (strip heaters), also takes into

account similar economics of running Gas FAF and heat pumps

▪ Electric FAF and Zonal Electric:▪ 66 degrees day and night▪ Justification:

Zonal electric: takes into account zoning (lower average house temperature) Electric FAF: factors in occupant’s ability to turn on/off heating system

Example: GSHP SEEM Runs Calibration Billing/metered data from 1 study (Missoula) Result: A reasonable match was achieved without making adjustments to the SEEM

model.

AverageHeat Pumps and Gas FAF 70/64 4% 0% 2% -7% -8% -2%Electric FAF and Zonal 66/66 -6% 1% 12% 8% 4%

Each StudyResults: SEEM Model kWh/sqft differs from Studies by x%

Heating System TypeHeating

Setpoints

Billing Study LocationHeating System

Sample SizeData Source

(goal)SEEM Model

ResultData

SourceSEEM Runs

Residential New Construction Bil l ing Analysis Market Research Report

(RLW for NEEA, 2007)WA Gas FAF 114 13,979 14,927 948 7%

Used WA gas heated homes due to large sample size and abil ity to disaggregate

space and water heating use.5.7 5.9

Zonal 305 4,728 4,468 -260 -6% 3.0 2.9

Heat Pump 36 7,835 7,876 40 1% 3.4 3.4

Zonal 346 4,907 4,954 47 1% 3.1 3.2

Heat Pump 53 8,055 8,114 60 1% 3.0 3.0

Electric FAF 212 11,539 12,896 1,357 12% 4.9 5.5

Heat Pump 212 7,383 6,888 -495 -7% 3.2 2.9

Electric FAF 169 9,631 10,375 744 8% 5.0 5.4

Heat Pump 169 6,168 5,680 -488 -8% 3.2 2.9

Data Source

Portland

Seattle

TriCities

RTF/NEEA Heat Pump StudyAssumed houses are weatherized.

Wood heat?HP controls estimated.

NW WA

Amount of wood heat unknown.Super Good Cents

Metered Data Report

Space Heat Use (kWh/year)

Difference(kWh/yr & %)

positive = SEEM overestimates

use

NotesHeating kWh/sqft

Internal Gains Scheduling Ventilation Model

Air balance within zones Stack driven infiltration Scheduled mechanical ventilation Combined natural and mechanical ventilation

Water Heater Model Driven by need to understand HPWHs Focus on HPWH interaction with condition (& buffer) space Water use schedule Equipment models

Ductless Heat Pumps Interface Enhancements

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Screen output Scrolls by quickly and provides some error

feedback if problems encountered CSV file

Contains all of the runs Definitions in seem92_csv_inout.xls

“.SEEM” File Text file with hourly data for heating and cooling

design day and user selected day. One file per run. Definitions in seem92_hourly_file_description.doc

Hourly data dump Text file containing a years worth of hourly data

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