physical equivalent solar aperture_11slides
TRANSCRIPT
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 1
A new experiment and modelling work to
jointly identify the building envelope’s
thermal parameters and a physical solar
aperture
Guillaume Lethé
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 2
Context • Energy performance gap of buildings noticed between expectation and measurements • Need for reliable characterisation techniques based on full-scale dynamic measurements
Background • Link between {dynamic - transient - static} methods • Advantages of the dynamic method • Which main variables of influence & the exfiltration's question
Used data set, and alternative modelling approaches • The experiment and the data set used for this study • The usual and a new modelling for the solar gains
Results, validation and comparison • Results • Validation and comparison
Conclusions
Contents
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 3
Context
Source: IEA ECBCS Annex 58 proposal, 2012
Source: Leeds Metropolitan Universiy, 2011
Source: BBRI, PERFECT research project, 2014
• Measured thermal performances of building envelopes significantly not as good as expected
• How to perform reliable measurements and identification of the Heat Loss Coefficient [W/K] ?
• Fully instrumented experimental building, for experimental design inter-comparison (5 different measurement protocols)
• One is a new short dynamic experiment, used here for in-depth data analysis (case-study)
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 4
Dynamic Analysis + finer models/estimation + generally applicable + must for prediction/control - requires stronger analysis skills
Dynamic, transient and static tests
Transient Analysis + faster and simpler (overnight) - sensitive to analysis method - no solar aperture identified - sensitive to weather conditions?
Static Analysis + slowest but very simple - only yields static parameters - sensitive to climate conditions
Other variables of influence • Wind conditions or measurement of the air change rate for exfiltration heat losses estimation • Composition/pattern of the solar radiation • Sky temperature, adjacent spaces and thermal bypasses
Measured exfiltrations
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 5
10 days co-heating + static analysis: impact of the exfiltrations is the same order of magnitude as impact of the solar radiation (based on daily average regression) 1 night experiment : impact of the analysis method (dynamic i.o. transient) is as important as the experiment itself
Initial findings
0 5 10 1540
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sun/dT [W/m²K]
hea
t/dT
[W
/K]
Heat Loss Coefficient, coheat 1&2
0 5 10 1550
60
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80
90
100
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120
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sun/dT [W/m²K]
hea
t/dT
[W
/K]
UA-value, coheat 1&2
HLC1
reg1
HLC2
reg2
UA1
reg1
UA2
reg2
199
162
142
137
HLC = αhQc − αcQh
αh∆Tc − αc∆Th
Ti
Te
Q
αh αc
Qh
Qc
∆Th ∆Tc
? ?
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 6
• Detached building on a small hill in an open meadow • Ventilation system sealed and all internal doors opened • Basement and attic disconnected from the ground floor • Temperature in the basement very stable • Temparature in the attic higly correlated to the ambient
• Indoor space sequentially controlled by themperature then by heating power for a very short test • Adaptive power distribution for homogeneous temperature • Damping for smooth evolution of the controlled variables
• Multiple measurements of solar radiation • Exfiltrations measured continuously by tracer gases
Experiment and data set used
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 7
Usual and new modelling of the solar gains
• Usual modelling • The global vertical South solar radiation: qs,v,south [W/m²] • Identification of a solar aperture: Aw [m²] based on dynamic data (or daily-mean) • Blindly encapsulates all physical phenomena (shadowing, reflection on the ground,
type of the solar radiation and angle of incidence)
• New proposed model • The mean solar transmission coefficient of the envelope (mainly the glazed
components), under equivalent normal (beam) incidence: qs,eq,tot,⊥ [W/m²] • Identification of the total glazed surface of the whole building envelope, multiplied
by the normalized heat gain coefficient: gAeq,tot,⊥ [m²] • Deterministic dynamic modelling of the above physical phenomena
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 8
Usual and new modelling of the solar gains
• New proposed model requirements • geometrical properties of glazing, facade orientation, sun path, albedo, etc. • pre-processing of the measured solar radiation (horizontal global & diffuse), per facade • final weigthed sum of all facades, based on the glazed surface of each facade
Day with clear sky (beam radiation) Day with overcast sky
(diffuse radiation)
- Stable ratio only under diffuse radiation - Daily-mean ratio varies by 5-10% from day to day
• Comparison of usual (qs,v,south) and new pre-processed (qs,eq,tot,⊥) solar data input
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 9
• Both modelling are implemented in CTSM-R
Results of the identification process
Total glazing surface of the building : 23m² | Typical solar factors (g-value) of double glazing : 0.85 In the new approach the identified average g-value is 18.8/23 = 0.82 very consistent ! Additionnally, the new approach has two advantages: it is physically interpretable and weather & climate independant. Finally, the consistency between the identified UA-values shows that the usual approach is good enough if one only requires to know the UA-value (i.o. a model suited for building control)
• usual approach (for g-value) • UA-value : 143.25 ± 5.54 W/K • Solar Aperture : 5.4 ± 3.4 m² • Loglik : 174.8
• new approach (for g-value) • UA-value : 144.4 ± 25 W/K • Solar aperture : 18.8 ± 6.5 m² • Loglik : 198.8
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 10
• Comparison of the usual and the new modelling approaches
• auto-correlation of the residuals both approaches are acceptable • cross-correlation of the residuals the new approach is better • Relatively less uncertainty and physical sense of the solar aperture • Same estimate for the UA-value but with more uncertainty, probably due to the
preprocessing itself and the relatively high arbitrary chosen albedo
Validation & comparison of the results
Auto Ti
Cross Ta
Cross qs
Cross Qh
Auto Ti
Cross Ta
Cross qs
Cross Qh
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1st intl. SEEDS Conference 2015, Leeds Beckett University – G. Lethé – 11/02/2017 – Page 11
• Good test environment, experimental procedure and data analysis are all required to correctly identify a good thermal model of the building enveloppe
• Usual approach good enough if only the static UA-value is required (excl. prediction model) Advantages of the proposed test and analysis methodology: + short dynamic testing (5 days i.o. 10 days for typical PRBS, or 15 days for static tests) + heating power control provides more damped data & homogeneous temperatures + solar aperture with physical meaning, weather independent fit for prediction models Drawbacks - solar modelling more complex and requires better knowledge of the environment - or requires more pyranometers to be placed Alternatives • Fit daily curves for the solar apertures, based on beam & diffuse solar radiation • Concentrate measurements at night (prediction capability of the model is lost) Points of attention • The global uncertainty is driven by the bigger terms: e.g. exfiltration heat losses often
contributes a lot to the global losses and is wind dependent to be measured! • Effect of the sky temperature, Treatment of adjacent spaces, etc.
Conclusions