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SEEM Workshop. Ben Larson 31 October 2011. [email protected] 4056 9 th Avenue NE, Seattle, WA 98105 (206) 322-3753 Fax: (206) 325-7270. Agenda. Simulation models and history in the PNW Why the RTF uses SEEM SEEM capabilities overview Running SEEM Outputs Inputs with examples

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Seem workshop

SEEM Workshop

Ben Larson

31 October 2011

[email protected]

4056 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 overview

  • Running SEEM

  • Outputs

  • Inputs with examples

  • Example RTF measures

  • SEEM calibration

  • Future plans for SEEM

Modeling residential building performance

Modeling Residential Building Performance

SEEM an Introduction

Simulation models

Simulation Models

  • 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 challenging

Simulation history

Simulation History

  • 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



  • “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 cooling

  • Required side calculations to handle these effects and other loads

Correlation models

Correlation Models

  • 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)

Seem development

SEEM Development

  • 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

Seem credits

SEEM Credits

  • 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

Why the rtf uses seem

Why the RTF uses SEEM

  • 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

Seem what is it

Simple Energy Enthalpy Model

SEEM: What is it?

  • 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 analysis

Seem what can you do with it

SEEM: What can you do with it?

  • 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

Today s plan

Today’s Plan

  • 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

The basics

The Basics

  • 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)

The details 1

The Details (1)

  • 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

The details 2

The Details (2)

  • 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

Seem limitations

SEEM Limitations

  • 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

Using seem

Using SEEM

  • SEEM is a calculation engine

  • You are the model(er)

  • Output is only as good as the input

  • You are responsible for setting the proper baseline, assigning the correct inputs, and doing any simulation post-processing

Running seem

Running SEEM

  • 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

Seem outputs csv file

SEEM Outputs: .CSV File

Running seem comparisons

Running SEEM – comparisons

  • 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

Seem inputs category summary

SEEM Inputs: Category Summary

  • 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

Inputs run

Inputs: Run

  • 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

Inputs weather files

Inputs: Weather Files

  • 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:


Inputs occupancy tstat

Inputs: Occupancy - TStat

  • 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)

Inputs occupancy internal gains

Inputs: Occupancy – Internal Gains

  • #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

  • Inputs internal gains example

    Inputs: Internal Gains Example

    • Example: ex3-gains.xls

    • Prototype: 2200 ft2

    • Envelope: NWBOP1

    • Equipment: Gas Furnace AFUE 90

    • Explore impact of lighting levels on gains and energy use in Spokane

      • Lighting levels: All incandescent, 50% CFLs, 75% CFLs, 90% CFLs

    Inputs equipment type

    Inputs: Equipment Type

    • 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

    Inputs equipment

    Inputs: Equipment

    • 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.

    Inputs equipment hp controls

    Inputs: Equipment – HP Controls

    • HPcntrl – heat pump control strategy

    • Tcntrl – temperature associated with strategy

    • NW Regional Control Strategies:

      • Base Case and PTCS

    Inputs ducts

    Inputs: Ducts

    • 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:

    Inputs duct leakage

    Inputs: Duct Leakage

    • 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

    Inputs envelope units

    Inputs: Envelope – Units

    • 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


    Inputs envelope 2

    Inputs: Envelope (2)

    • 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.

    Inputs envelope 3

    Inputs: Envelope (3)

    • 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

    Inputs foundation 1

    Inputs: Foundation (1)

    • 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

    Inputs foundation 2

    Inputs: Foundation (2)

    • 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:

    Inputs foundation 3

    Inputs: Foundation (3)

    • Crawl space or basement wall characteristics

      • HeightAG

      • RwallAG

      • HeightBG

      • RwallBG

    Inputs infiltration

    Inputs: Infiltration

    • 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:

        • [email protected] / 20 ~ 0.35 ACH natural

    • ACHAttic – 4.5, typical for vented attic

    • ACHCrawl – 4.5, typical for vented crawl

    Adam s components may 31 st 2011

    (Adam’s Components)

    May 31st , 2011

    SEEM Workshop



    • 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

    Example runs of rtf deemed measures

    Example Runs of RTF Deemed Measures

    • 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)

    Example ptcs duct sealing

    Example: PTCS Duct Sealing

    • Primary SEEM Variables

      • SDleak

        • Pre: 15%

        • Post: 10%

      • RDleak

        • Pre: 5%

        • Post: 3%

    Example heat pump upgrades

    Example: Heat Pump Upgrades

    • 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.

    Example attic and floor insulation

    Example: Attic and Floor Insulation

    • 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

    Seem calibration

    SEEM Calibration

    • 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.

    Seem calibration single family weatherization

    SEEM Calibration: Single Family Weatherization

    Future plans for seem

    Future plans for SEEM

    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

    Seem workshop


    Extras follow this slide

    Extras follow this slide

    Seem outputs

    SEEM Outputs

    • 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


    Seem outputs seem file

    SEEM Outputs: .SEEM File


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