Modeling Energy Use in a Residential Building

ATA May 2016 Ardenwood

Modeling Energy Use in a Residential Building

A beginner’s (incomplete) story


What is ahead?

• Four broad topics– Why start trying to do energy modelling?

– What tools were used?

– How to have any faith in the numbers generated?• Measurement

– Was it useful?

• Not a neat package tied with a bow– Comments from the those in the audience with more experience

may be useful for others, not just me.


Why try modeling the house?

• Curiosity, fun, excuse to measure stuff ...• (Originally) Intended to put a fridge vent in my kitchen

– Inspired by Dennis Wrigley’s book and some electrical consumption data that pointed to the high energy use of my fridge and freezer in summer.

• Then recorded temperature data around the house for a number of months

• Then wanted to understand how to quantify the cost/benefit of any “modification” to the structure of the house.

• So, finally, wanted to be able to have a reliable model which would let me test the changes in energy use (and comfort) resulting from any modification


The House

• Could be used, like so many others, as a bad example for Sustainable House day– Brick-veneer

– colander ceiling

– turns its back on the sun in winter, but welcomes the western sun in summer

– Hallway could be used for wind tunnel

– Windows designed to keep the occupant in touch with nature

– “comfort” maintained by lots of gas heating in winter and reverse cycle air conditioning in summer (one end of house only)

• We have insulated the walls and improved some of the more egregious infiltration problems but what to do next?


House – west face (SketchUp version)


What to do next?

By Shaun Greiner - CAT D9T, CC BY-SA 2.0, https://commons.wikimedia.org/w/index.php?curid=5153994

Radical modification ..

Or try to understand behaviour of the house and how best to improve it.


What tools to use?• Use free and freely available software to try to produce reasonably

accurate models of the energy use of my house.

• The tools I chose were:

• SketchUp

– Easy-to-use drawing package for 3d objects.

• OpenStudio– A “plug-in” for Google SketchUp developed by NREL and an

application for refining and running models.– Use it to simplify entering the thermal properties of a building– Creates text files that are processed by EnergyPlus

• EnergyPlus– Fairly complex engine for modeling energy usage of built structures.– Freely available from DOE– Text input only– The simulation engine underneath DesignBuilder


Work flow ...• Use SketchUp to handle the creation and rendering of

the 3d model

• OpenStudio plugin then handles the way the surfaces and spaces in that model are interpreted as entities with physical properties.

• OpenStudio application used to refine all details.– Materials, constructions (assemblies of materials), connections

between constructions.

– Infiltration, ventilation, contact with ground.

– Internal loads (electricity and gas)

• OpenStudio produces a text file that defines everything about the thermal characteristics of the structure.– This is the input to EnergyPlus that does the energy modelling.


House – OpenStudio constructions


House – OpenStudio thermal zones

• Zones = areas in thermal model treated as being at same temperature– Beginner’s mistake. Model is way too complex thermally.


OpenStudio GUI



EnergyPlus input files - editing


Raw “numbers” from simulation


Model or random number generator?

• Models are a great way to generate numbers

• Need to validate the model against the particular house– The house “as built” may not match the house “as planned”

– The implementation of the model may be wrong

– User “incompetence” may cause additional errors.

• Measure temperature history in the house and compare with the model– Direct comparison requires current climate data

• Measure total energy usage and compare with model

• Beware of the Theory of Cumulative Incompetence


Theory of Cumulative Incompetence (TOIC)

• For any system of sufficient complexity there is a non-zero probability that the sum total of the effect of all errors made in implementing that system will approach zero.

• That is: you get the right answer for the wrong reasons.

• A slight variation: “With four parameters I can fit an elephant, and with five I can make him wiggle his trunk” attributed to Von Neumann

• The model has no predictive capability.


Simple model. Single large space• A test case on which to learn how to build models and

how to interpret the output from models.– Single zone

– Thick slab floor

– High thermal mass walls

– Large northern windows for solar gain in winter

– Small east and west windows for ventilation


Model 1. Single large room• Naïve model using Canberra climate

– External temperature, solar insolation, precipitation, wind speed and direction all based on multiple years of Canberra weather observations

– Single glaze– Constant ground temp

(18C below slab)

– No air leaks– No internal loads– No curtains– Nobody opens windows

– Room looks prettycomfortable year round

Black: external air temperatureRed: internal air temperature from model


Model outputsExtensive and sometimes confusing for the beginner

• For example: 189 unique output variables for the simple model• Many of the 189 will be available for each surface in the model

– Good sanity check is the summary performance data for the building which includes an overview of the physical structure

• For example, the window-to-wall ratio of the external envelope• The table shows these data for my house


Model outputs (2)

• Tables for solid and fenestration parts of the envelope facilitate checks of the materials and constructions.


Model 1 (revised)• Ground temperature calculated, infiltration added, simple

glazing model for all windows and glass doors– Room now getting a little too hot in summer

and it’s two coats colder on winter mornings (detail below right)

Black curve: outdoor temperature. Red curve: zone (room) mean


Simple model.

• Really interesting for learning.– comparisons of single and double glazing

– Investigate ventilation in summer


Still need to sanity check the output …Gas usage in the real house ...• Provides some sanity check but highly variable and how

much of the energy through the meter ends up inside the house?

20052006

20072008

20092010

20112012

20132014

2015

0

10000

20000

30000

40000

50000

60000

70000

Annual gas usage

Year of winter (beginning c. 24 April)

ga

s u

sag

e (

MJ)


Energy use depends on today's climate ..

10.0 15.0 20.0 25.0 30.0 35.00.0

50.0

100.0

150.0

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250.0

300.0

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2014 Average gas usage

mean monthly maximum (C)

me

an

da

ily g

as

usa

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(M

J)

• EnergyPlus model uses a “typical weather year” to calculate energy usage and house temperatures. Can't compare these results directly with a measurement taken today.

• Need actual data for the period of measurement in order to make direct comparison.

• Figure below illustrates the sensitivity of the real gas usage to the temperature


Add temperature measurements ?

• Reasonable accuracy and precision <0.5°C

• Reasonable resolution

• Logging– On the device or over some kind of network

• Cheap (need 5 -10) – for the hobby user.

• Easy to use– Physical placement

– Long battery life

– Data retrieval and analysis

• Robust

• Easy to implement at multiple, scattered, locations.


Temperature sensors

• Thermochrons– Self-contained

– Robust

– Long life

– Relatively cheap

– Data retrieval is fiddly• Use custom code that handles

data retrieval from multiple sensors

– Reasonable resolution and accuracy• 0.5C resolution

– 2000 sample memory– Require precision support system

• See example at right


Thermochron data ...

• 2000 sample memory– About 3 weeks data logging with four samples per hour.


Temperature Sensors

• Thermocouples– Compact

• Great for putting inside insulation around pipes on solar HW

– Relatively robust– Fast response– Huge temperature range

• Really (way) more than is necessary for this application

– Logging is more difficult to implement• Microcontrollers and interface ICs are good for this• Expensive to implement at multiple locations

– Not accurate without calibration


Temperature sensors

• Solid state (lots of options) LM35 series is fun.– Relatively robust

– Relatively compact

– Good resolution and accuracy• Accuracy 0.2C without calibration, good for differential measurement

– Logging more difficult to implement• Micro-controller with reasonable analog-to-digitial conversion• Expensive to implement at multiple locations

• Wait a little while for prices to come down on temperature motes … e.g. Wimoto and many others.– Or build your own (WiFi, BlueTooth, Bluetooth LE, Zigbee, ISM,

phone ...)


Temperature sensor systems ..

• For hands-on hobbyist, build your own.

• Ladyada is your friend

2 cm


Temperature data

21/08 22/08 23/08 24/08 25/08 26/08 27/08 28/08 29/08 30/08

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35RoofKitchenBedroomCrawl SpaceLoungeOutside

Tem

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Boundary temperatures ...

21/08 22/08 23/08 24/08 25/08 26/08 27/08 28/08 29/08 30/08

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35Outside

Crawl Space

Roof

Tem

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Full house -vs- sub-systems

• After a quick look at the whole-house problem it seemed a “better” idea to start on more modest problems.

• Rather than trying to measure and model the complete house it can be interesting just to look at sub-systems.– A fridge vent – Changing window treatments

• Use temperature measurements to work out whether modifications have made a significant change

• One example. Compare standard single-glazed window with pelmeted curtain, plastic double-glazing or blinds.


“storm window”

Two layers of “Clear Comfort” on wooden frame


Window treatments - measurements … • Ideally need a foggy day with constant outdoor

temperature so that the heat flow through the window and treatment is stable ….


Window treatments …

• Record temperature differences as a function of time

• Work out heat loss from the room relative to a single-glazed window.


Monitor temperatures

• Thermochron data. Summer• Originally looking at temperature behind fridge/freezer

– Investigate installation of vent in ceiling behind fridges


Winter behaviour


Tune the modelTune parameters so ranges and means of attic, subfloor and room temperaturesAnd gas usage were in rough agreement with measurements.


Tune the model..

?


Using the model ..

• Given all the caveats, must be cautious.

• Adding cavity wall insulation.– Reduced gas usage by 25% (but only one reference year)

– Model predicts ~29 -32%

• Upgrading ceiling insulation– Reduced gas usage a further 25%

– Model “predicts” 14%

– model does not include a fudge factor for downlights which were sealed up during insulation upgrade


Using the model ..• But can be really useful for qualitative exploration.

– e.g. what size, shape to make shade over west windows?• Blue is predicted lounge temperature without shade, black with

shade.


Time for tea and biscuits

With all the caveats is it worth trying to do this sort of modeling? (as opposed to professional models of known builds with current data)

• Excellent learning in many areas

• Increased focus on some failings of the house

• Improved understanding of heat flows

• Improved understanding of solutions

• Lots of fun with hardware and coding

• Possible for the positive version of TOCI to apply (?).

Documents

Modeling Energy Use in a Residential Building