2 Why Care About Building Energy Performance? Aside from building energy increasing? Ignoring...
-
Upload
lucas-carter -
Category
Documents
-
view
218 -
download
2
Transcript of 2 Why Care About Building Energy Performance? Aside from building energy increasing? Ignoring...
2
Why Care About Building Energy Why Care About Building Energy Performance?Performance?
Aside from building energy increasing?
Ignoring performance ratings is choosing to fly fairly blind — staying at the “dumb” end of the “dumb and dumber” scale
Performance ratings are an evaluation, quickly, and not an investigation
3
4
5
6
New Construction has been a problem for 50 New Construction has been a problem for 50 years, increasing carbon footprintyears, increasing carbon footprint
0
50
100
150
200
250
300 2003 CBECS
data with malls, kBtu/sq-ft-yr weighted means, higher source energy EUIs in newer buildings
CBECS data show same pattern with each survey year, life-cycle influences are shown
7
Basic Energy Benchmarking Basic Energy Benchmarking (Performance) Info(Performance) Info
Go to TC 7.6 website (shown on title slide previously)
Select Program Activities at bottom
Chicago 2006, Seminar 17, first presentation
Atlantic City 2002, Seminar 41, first two presentations
8
Current ASHRAE High-Performance Current ASHRAE High-Performance Protocol ProjectProtocol Project
“ASHRAE needs to provide guidance regarding the measurement and reporting of the performance of new and existing [commercial] buildings . . . .”
“ . . . to further the development of building energy performance standards.”
“Measuring and Reporting the On-site Performance of Buildings . . .”
9
ASHRAE STANDARD 105ASHRAE STANDARD 105 1984 to now 1984 to now
BSR / ANSI / ASHRAE Standard 105-1984 (RA99) covers measurement and expression of building energy performance at a basic level, with suggested optional extensions
Standard 105-[2007?] is a major revision and has been submitted for publication. It extends the coverage of energy performance measurement and expression, and comparison of building energy performance against others
The nature and level of performance comparison requires some performance “standard” and requires or intrinsically offers some evaluation
10
Standards of ComparisonStandards of Comparison
1. Minimum prescriptions or best practice levels (Stds 90.1, 90.2, 189P, LEED)
2. Self-reference, e.g., past and future
3. Ad-hoc building populations
4. Representative populations, e.g., CBECS, RECS for USA and CEUS for CA
11
2007 Applications Handbook2007 Applications HandbookEnergy Comparisons using CBECSEnergy Comparisons using CBECS
Chapter 35, energy management, 3 tables on commercial buildings
Based on 2003 CBECS micro-data without malls
About 50 building types
Site energy use indexes for mean and percentiles 10, 25, 50, 75, and 90
Electricity and cost indexes at same detail
12
Commercial Buildings Energy Commercial Buildings Energy Consumption Survey, CBECSConsumption Survey, CBECS
Latest survey micro data available = 2003, next is 2007 (released in 2010?)
Publicly available government reports and data on EIA website
Nationally representative sample, with fairly complicated cluster sampling frame
Different versions have been available, ~5,000 records
Not including imputation flags, there are ~350 data parameters
Data seem to get better each time
13
CBECS and CEUS,CBECS and CEUS, some important differences some important differences
Item CBECS 2003 CEUS 2003
Survey approach Phone Site, skilled
Unit of interest One building, even if a campus
Site, including campuses
Characteristics detail Limited Very detailed
Floor area limits due to masking
< 1,000,000 sq ft for valid data
No limit, but not over 2M here
Fuel data limitations Propane data coarse Only gas and electric real
Simulated or regressed end uses
None Simulated
Fuel cost data Annual by fuel None
Fuel data intervals Annual only Monthly
14
Basic EUI StatisticsBasic EUI Statistics kBtu/sq-ft per yr kBtu/sq-ft per yr
Quantity, all weighted CBECS 2003
N = 4678
CEUS 2003
N = 2360
Mean 216 208
10th percentile 30.8 27.6
25th percentile 66.1 57.8
Median 134 115
75th percentile 244 204
90th percentile 449 521
15
Floor Area Distributions, Sq FtFloor Area Distributions, Sq Ft
Quantity, all weighted CBECS 2003
N = 4738
CEUS 2003
N = 2360
Mean 14,352 8,813
10th percentile 1500 832
25th percentile 2400 1200
Median 5000 2444
75th percentile 12000 5280
90th percentile 28000 14,960
16
Week Schedule, hr/week openWeek Schedule, hr/week open
Quantity, all weighted CBECS 2003
N = 4360
CEUS 2003
N = 2360
Mean 63.7 61.6
10th percentile 16 40
25th percentile 40 45
Median 50 50
75th percentile 75 70
90th percentile 168 98
17
Worker DensityWorker Density workers per 1,000 Sq-ft workers per 1,000 Sq-ft
Quantity, all weighted CBECS 2003
N = 4360
CEUS 2003
N = 2352
Mean 1.37 2.69
10th percentile 0.05 0.53
25th percentile 0.38 1.00
Median 0.86 1.88
75th percentile 1.74 3.51
90th percentile 3.13 5.00
18
Density of PCsDensity of PCs PCs per 1,000 Sq-ft PCs per 1,000 Sq-ft
Quantity, all weighted CBECS 2003
N = 4360
CEUS 2003
N = 2127
Mean 1.32 1.89
10th percentile 0.15 0.22
25th percentile 0.31 0.46
Median 0.69 1.00
75th percentile 1.68 2.50
90th percentile 3.25 4.63
19
Rough-cut, Incomplete Regression Rough-cut, Incomplete Regression Models, weightedModels, weighted
Parameter coefficient
>> intercepts not signif.
CBECS 2003
N = 4300
CEUS 2003
N = 2352
EUI change per hr/wk 1.9 4.1
EUI change w/ worker density
50 25.7
Lab, change in EUI from average
386 NS
Offices – 52 – 49
Clinics – 42 – 33
Restaurant 336 82.8
Fast Food 830 272
Average EUI 245 179
20
Not done fishing yetNot done fishing yet