Modeling Energy Use in a Residential Building. A beginner s (incomplete) story

Transcription

1 Modeling Energy Use in a Residential Building A beginner s (incomplete) story

2 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.

3 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

4 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?

5 House west face (SketchUp version)

6 What to do next? Radical modification.. By Shaun Greiner - CAT D9T, CC BY-SA 2.0, curid= Or try to understand behaviour of the house and how best to improve it.

7 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

8 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.

9 House OpenStudio constructions

10 House OpenStudio thermal zones Zones = areas in thermal model treated as being at same temperature Beginner s mistake. Model is way too complex thermally.

11 OpenStudio GUI

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13 EnergyPlus input files - editing

14 Raw numbers from simulation

15 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

16 Theory of Cumulative Incompetence (TOIC) For any system of sufficient complexity there is a nonzero 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.

17 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

18 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 pretty comfortable year round Black: external air temperature Red: internal air temperature from model

19 Model outputs Extensive 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

20 Model outputs (2) Tables for solid and fenestration parts of the envelope facilitate checks of the materials and constructions.

21 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

22 Simple model. Really interesting for learning. comparisons of single and double glazing Investigate ventilation in summer

23 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? Annual gas usage gas usage (MJ) Year of winter (beginning c. 24 April)

24 Energy use depends on today's climate.. 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 2014 Average gas usage mean daily gas usage (MJ) mean monthly maximum (C)

25 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.

26 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

27 Thermochron data sample memory About 3 weeks data logging with four samples per hour.

28 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

29 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...)

30 Temperature sensor systems.. For hands-on hobbyist, build your own. Ladyada is your friend 2 cm

31 Temperature data Roof Kitchen Bedroom Crawl Space Lounge Outside Temperture C /08 22/08 23/08 24/08 25/08 26/ /08 28/08 29/08 30/08

32 Boundary temperatures Outside 30 Crawl Space Roof Temperature C /08 22/08 23/08 24/08 25/08 26/ /08 28/08 29/08 30/08

33 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.

34 storm window Two layers of Clear Comfort on wooden frame

35 Window treatments - measurements Ideally need a foggy day with constant outdoor temperature so that the heat flow through the window and treatment is stable.

36 Window treatments Record temperature differences as a function of time Work out heat loss from the room relative to a single-glazed window.

37 Monitor temperatures Thermochron data. Summer Originally looking at temperature behind fridge/freezer Investigate installation of vent in ceiling behind fridges

38 Winter behaviour

39 Tune the model Tune parameters so ranges and means of attic, subfloor and room temperatures And gas usage were in rough agreement with measurements.

40 Tune the model..?

41 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

42 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.

43 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 (?).