Ben Larson 19 July2010 [email protected] 4056 9 th Avenue NE, Seattle, WA 98105 (206) 322-3753 Fax:...
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Transcript of Ben Larson 19 July2010 [email protected] 4056 9 th Avenue NE, Seattle, WA 98105 (206) 322-3753 Fax:...
Ben Larson19 July2010
[email protected] 9th Avenue NE, Seattle, WA 98105(206) 322-3753 Fax: (206) 325-7270
Today’s topic – energy use modeling for the residential sector.
▪ This covers the process used by Ecotope in recent work including:▪ WA Energy Code, ▪ Northwest Power Council 6th Power Plan ▪ OR Energy Code
Modeling goals: predict energy savings across the sector for one (or a group of) efficiency measure(s).
To model an entire sector, one needs to use minimum, average, and typical characteristics:
▪ Ex: Minimum – code ceiling insulation requirement▪ Ex: Average – # of hours lights are on per day▪ Ex: Typical – weather data
To make problem tractable, simplifying assumptions are needed (to be indicated throughout discussion)
Assemble prototypes to represent new construction building population Choose appropriate weather data
Determine base case characteristics (code levels) Compile sets of efficiency measures to examine
▪ Building Shell▪ Lighting▪ HVAC and Duct Systems▪ Domestic Hot Water (DHW)
Perform modeling simulations and calculations Use an annual energy simulation program (SEEM) with a
combination of engineering calculations Compare results to base case using a weighted
average to predict energy savings
1344ft2 – original bldg in 1st Power Plan from 1982. Single story over crawl space (or slab)
2688ft2 – added to mix in late ‘80s Like 1344, but over a conditioned basement
2200ft2 – added in early ‘90s to address more complex designs 1.5 story split level with garage and bonus room (over crawl)
5000ft2 – special case for 2009 to address large house size conditioned basement plus 2 stories above grade
Weighting % for WA determined by census data and baseline stock assessments to create a representative snapshot of building population. Covers multiple construction scenarios (basement, crawl, etc.) Window areas determined from baseline surveys
Prototype Weight
1344 15%
2200 75%
2688 9%
5000 1%
Typical Meteorological Year (TMY3) From NREL
Three representative sites for Oregon:
City HDD65 CDD65
Portland 4187 367
Redmond
6583 204
Medford 4530 601
OR 2008 Energy Code: Prescriptive requirements (Table N1101.1(1)) Which additional measure to use?
▪ Choice matters because not all additional measures save the same amount of energy. Leads to slightly different base case comparison targets
▪ High efficiency HVAC assumed most likely (i.e. typical)▪ With better market information, we could construct an energy
baseline using a weighted average of all the additional measures
House infiltration – not specified in 2008 code.
▪ Average new house is ~6.5ACH50 but 25% of all houses >9ACH50. Where to set infiltration base?
Miscellaneous electric load (MEL) levels
New (or more) additional efficiency measures to consider for code upgrade.
▪ Equipment efficiency improvements▪ Duct sealing or interior duct placement▪ High efficacy lighting▪ Building shell (windows, walls, ceilings, floors)▪ Water heater efficiency ▪ Building infiltration▪ Solar PV (generation not conservation)▪ Solar thermal for water heating (generation not
conservation)
SEEM – Simple Energy Enthalpy Model Developed in the Northwest specifically for the NW
▪ Models ducts losses, heat pump behavior, and ground contact more accurately than other available simulation tools
▪ Models heating & cooling load correctly (for our climate) Used in Northwest Power Plan Inputs calibrated to match billing data
SEEM predicts the hardest part of whole house energy use: heating and cooling energy
▪ Calibration is important in order to ensure accuracy Engineering calculations used for DHW, lighting,
ventilation, appliance, and MELs.▪ These calculations are also calibrated to match field data
Lighting energy use. The number and type of bulbs in a house comes from regional survey data (NEEA). Average values:
▪ 1 Incandescent ~65W▪ 1 CFL ~17W▪ On-time: 2 hours/day
Lighting use 2200ft2 house, 50% CFLs 1766kWh/yr = 1.1(W/ft2) x 2200(ft2) x 2 (hrs/day) x
365(days/yr) / 1000(kW/W)
% CFLs LPD (W/ft2)
0 1.75
50 1.1
75 0.8
90 0.6
DHW use based on 2.5 people per house using 22 gals/person/day Hot water consumption baseline has held fairly
constant in Ecotope studies from the 1980s to today
Presentations as ASHRAE summer meeting 2010 also reconfirmed base consumption
Hot water efficiency measures: Upgraded equipment Lower flow faucets and appliances OR Electric Tank Code Base: 0.87 EF uses 4020
kWh/yr
thrms/yr
kWh/yr
2006
Code
749 7945
2009
Code
613 6828
Typical modeled site-use energy consumption for a 2200ft2 house with gas furnace and gas DHW
MELs consist of appliances and plug loads (~4000kWh/yr) 2009 Code compliance met with upgraded furnace
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
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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
include 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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Under the hood Uses input.csv file & output.csv file
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 Example: ex1-nwcities.xls
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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 met 16
#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 ~2 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 17
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
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Examples: Puget Sound Energy study - produced Access
database with ~250,000 entries Power Council 6th Power Plan Residential Sector
~ 350,000 runs WA State Energy Code Update ~60,000 runs
Custom data processing tools written for each application Includes calculations for lighting, heat system
efficiency, hot water, fan energy, etc. Example: current OR Energy Code
Modeling