course overview, goals and methods
TRANSCRIPT
CEE 243 - Predicting and Measuring Building Energy Use
Agenda: April 3, 2012
Introductions
Motivating problem
Course overview / roadmap
Today’s lecture: intro to HVAC systems
Thursday: class software tools introduction
Big Ideas
We (engineers) now can measure and predict (Y2E2) in detail;
This class teaches tools and methods you (students and energy
novices) can use to measure and predict energy in detail;
– Y2E2: some HVAC components & systems work well; others no
Energy use is a global problem/opportunity: Malmo, LEED, Y2E2,
Oberlin all have measured energy >> predicted
Clear evidence for lack in methods to design, build and operate
individual buildings with satisfactory energy performance, -- first step
toward global improvements
– ~10 students @ 1000 hours/quarter 10% of building
Buildings and grid lack shared control
2
Course Staff & Meeting Times
Instructor:
– John Kunz ([email protected])
– Y2E2, Room 293
Co-Instructor:
– James O’Donnell ([email protected])
Teaching Assistant:
– Robert Graebert ([email protected])
Meeting Times:
– Tuesdays: Lecture
– Thursdays: Hands-on lab session analyzing real data
CEE 243 April 3 3
Gentle introduction to energy data analysis
http://171.67.80.21/
Login name: y2e2 (all lower case)
Password: user (all lower case)
CEE 243 April 3 4
Reflective Positive:
What surprised or
encouraged you
positively?
Reflective Negative:
What surprised or
encouraged you
negatively?
Decisional:
Suggest next steps
Reflections +/∆ Analysis
5
Class goals, given 2009-11 results
Explore methods to retrieve, plot, analyze and interpret the
significance of monitored energy system performance over time,
using a theoretically founded method, based on design theory,
that describes and analyzes
• Functional intent of Y2E2 energy (HVAC) system,
components and spaces, e.g.,
• Air, steam and water supply & return systems; mixing
boxes; valves; registers; economizers; dampers; rooms
• Form or designed scope, given functions
• Behaviors (measured and assessed) given their functions
and forms and our class analysis methods
Relate design intent and predictions to measurements and
develop guidance for performance analysis on how to use these
methods in practice;
CEE 243 April 3 6
Assessed behaviors: • Assessed Status (●●●) • Explanation
Apply these methods to in-depth, time-based analysis of a
modern building (Stanford's Y2E2 building) for which detailed
energy use data and building engineer reports are available for
analysis;
Method:
Class goals, given 2009-11 results
CEE 243 April 3 7
CEE 243 data analysis
method
Functions of • Systems • Spaces • Components
Forms of • Systems • Spaces • Components
Measured behaviors: • Time-varying component
data
Workflow
Class goals, given 2009-11 results
Explore the building spaces systems in person with a guided
building visit background for
– Analysis of data status
– Manual energy audits
Relate
– Manually audited information with automatically monitored
data; independent measurements,
– Measured data with occupancy and occupant assessment of
comfort
CEE 243 April 3 8
Class goals, given 2009-11 results
Make assessments to the owner about effectiveness of
interventions to building and systems operations that have been
made during previous years, given your assessment of
– Analysis of data – this year and in past
– Manually audited data
CEE 243 April 3 9
Class goals, given 2009-11 results
Make recommendations to the owner about methods to
– model the building,
– collect actual energy performance data,
– analyze energy use,
– interpret intended, predicted and measured performance,
methods to validate predictions and methods to validate
engineering changes.
These recommendations have the potential to make a real-
world impact on the facility itself and, over time, on other many
buildings
CEE 243 April 3 10
Motivating Problems: Global Perspective
Related problems:
– Big and global: global warming
– Buildings contribute to global warming:
buildings generate 40% of human
related CO2 emissions
– Daily operations: Big and unnecessary
building energy operating cost
CEE 243 April 3 11
Atmospheric CO2 is rising
12
800,000 year CO2 history
CO
2 (PPM
)
Year Year
1769: James
Watt invents
steam engine
http://www.globalchange.gov/publications/reports/ scientific-assessments/us-impacts/full-report/global-climate-change
Source: Sustainable Energy — without the hot air: MacKay, 2008,
Huge societal changes are required to lower carbon footprint:
Predicted impact of global warming
13
Source: Sustainable Energy — without the hot air: MacKay, 2008, based on Baer and Mastrandrea (2006)
US: ~24 tCO2/ y per person
Motivating Problem: US Buildings
14
U.S. Department of Energy Buildings Energy Data Book, Sept. 2008
Motivating Problem: Our Industry
15
(Contributing) reasons for Inefficient Operation
– Virtual absence of validated actual performance
measurements re design-phase prediction data
– Lack of validated virtual testing tools & practices
– Poor Design
– Poor Construction
– Absence of Life Cycle Information Transfer
– Absence of standardized practices during operation
Our focus: Y2E2
• 4 story building with ~130,000 sf • Labs, offices, mechanical room, server room, conference
rooms, class rooms
• Bathrooms, electrical rooms, data and storage rooms
16
Key Y2E2 concepts
Atria: – support natural ventilation
– provide daylighting
Exposed concrete floors: – Increase thermal mass of the building
Manually and automatically openable windows – Support natural ventilation
Active beams – Provide efficient conditioned fresh air to spaces
District heating and cooling – from cogen plant
Small PV units on roof (1-2% of total electricity)
17
http://www.entropic.ie/presentations/Entropic%20Chilled%20Beams.pdf
Key Y2E2 concepts
Building Management System (BMS)
• ~2,370 HVAC system measurement points:
• 1,440 samples/point/day
• ~3.5M samples/day
18
Key Y2E2 concepts
Building Management System (BMS)
• ~2,370 HVAC system measurement points:
• 1,440 samples/point/day
• ~3.5M samples/day
BMS status viewer: Altitude system
– Shows current status; system diagrams
19
Key Y2E2 concepts
Building Management System (BMS)
• ~2,370 HVAC system measurement points:
• 1,440 samples/point/day
• ~3.5M samples/day
BMS status viewer: Altitude system
– Shows current status; system diagrams
SEE-IT BMS data viewer
20
Key Y2E2 concepts: Workflow analysis
21
Select
• System, space, components to analyze
• Analysis points
Synthe-size
• Functional intent of system and space
• Data context
Graph
• Select data to retrieve from BMS
• Select graph options
Check
• Check conformance of data to functional intent
• Classify as green/yellow/red status
Cause
• Identify candidate immediate cause
• Identify candidate root cause(s)
Docu-ment
• Report selected system and points
• Report status and candidate cause(s)
Key Y2E2 concepts: expert engineering knowledge of failures to follow functional intent
Chilled Water valve (CWV) leak through if:
– fan is running [normally runs 24/7 in Y2E2] and
– Chilled Water valve (=219) has been closed for 30 minutes
(adjustable) and
– Supply AirTemperature (=1110) < MixedAirTemperature
(=1106) - 2o) (or sensor just before fan coil)
22
Key Y2E2 concepts: expert engineering knowledge of failures to follow functional intent
Chilled Water valve (CWV) leak through if:
– fan is running [normally runs 24/7 in Y2E2] and
– Chilled Water valve (219) has been closed for 30 minutes
(adjustable) and
– Supply AirTemperature (SAT: 1110) < (MixedAirTemperature
1106-2o) (or sensor just before fan coil)
Simultaneous heating and cooling if
– Fan is on for more than 5 minutes, and
– Heating, indicated by outside air temperature (OAT) < (SAT-2o)
and
– Cooling, indicated by CWV open or
OAT > (SAT+2) and Hot water valve (HWV) open
Note
– Checklist format of rules
– Common failures are well-known
23
CEE-243 Overview / (Tentative) Roadmap
Week
1: Introduction to class
2: Altitude system demo; Y2E2 building tour - Tim Troxell;
Introduction to product hierarchie and Y2E2 HVAC systems
3: HVAC controls (sequence of operations) at Y2E2
4: Performance audits and data analysis methods
5: Data analysis methods, continued
5b: Initial student presentations
6: Relating BMS and energy audit data
7: Group working session
8: Energy monitoring and management practice, vision and the
gap between them
9: Energy simulation and real-world challenges
10: Final Student Presentations
24
Reading week-1
Y2E2 2009 Summary
Santa Clara County 2010 Summary
Y2E2 Designed Sequence of Operations
Tutorial
Class wiki
Note: all materials on the class web site:
– http://www.stanford.edu/class/cee243/
CEE 243 April 3 25
CEE-243 compared to…
CEE 176A (Energy efficient buildings)
– Background in considerations of building energy performance
– Primary focus on residential (single-family homes)
– 243: commercial buildings, actual measured performance data
CEE 156/256 (Building systems)
– Focus primarily on HVAC systems and system design
– Simulation used to design systems
– 243: simulation as a comparison to actual measured data
CEE 226E (Advanced topics in integrated, energy-
efficient building design)
– Focuses on real cutting-edge energy efficient-system designs
– 243: analyze already-built systems; find ways for improvement
CEE 243 April 3 26
CEE 243 April 3 27
Class organization
Website:
– www.stanford.edu/class/cee243
– Latest links to readings / lectures
Wiki
– Past years’ work
– Query submission
Meeting times:
– Tuesday 1:15-3:05
– Thursday 1:15-2:05
GLOBAL SITUATION – SOME DETAIL
CEE 243 April 3 28
CO2 rise has many causes, but no one single cause … or solution (2002)
29
Source: Steve Chu, LBNL, AAAS 2007 keynote
Buildings
No single group can fix problem … Per capita CO2 emissions - 2000
30 Copyright David JC MacKay 2009.
Global
average
2050
objective
Per capita CO2 emissions - historical Many of those responsible are no longer living …
Many who will be impacted are unborn …
31
Copyright David JC MacKay 2009.
Global
average
2050
objective
All nations have a difficult challenge
32
Source: Steve Chu, LBNL, AAAS 2007 keynote
Each of us has insignificant impact, but we must all act to have impact: My personal part …
33
2840 watts = 24.8
Mwh/yr
15.4 M-tons
CO2/year
x
Huge societal change is required to lower carbon footprint:
Looming Global-Scale Failures and Missing Institutions
34 SCIENCE VOL 325 11 SEPTEMBER 2009
“To address our common threats we need greater interaction among existing institutions, as well as new institutions, to help construct and maintain a global-scale social contract.”
Our (ethical and engineering) dilemma
“Half-life” of CO2 in the atmosphere (apparently) is about a
century
Dilemma: Since
– Institutions cannot fix problem
– No one change can fix problem
– Many responsible for today’s rise in atmospheric CO2
are no longer here; most who will be affected are not
yet born
– Each of us has insignificant impact, but we must all act
to have impact
– Let’s learn how to interpret the numbers we can get
35
CO
2 (PPM
)
Our dilemma
“Half-life” of CO2 in the atmosphere (apparently) is about a
century
Dilemma: Since
– Institutions cannot fix problem
– No one change can fix problem
– Many responsible for today’s rise in atmospheric CO2
are no longer here; most who will be affected are not
yet born
– Each of us has insignificant impact, but we must all act
to have impact
– Let’s learn how to interpret the numbers we can get
36
CO
2 (PPM
)
“Half-life” of CO2 in the atmosphere (apparently) is about a
century
Dilemma: Since
– Institutions cannot fix problem
– No one change can fix problem
– Many responsible for today’s rise in atmospheric CO2
are no longer here; most who will be affected are not
yet born
– Each of us has insignificant impact, but we must all act
to have impact
– Let’s learn how to interpret the numbers we can get
Our dilemma
37
CO
2 (PPM
)
“Half-life” of CO2 in the atmosphere (apparently) is about a
century
Dilemma: Since
– Institutions cannot fix problem
– No one change can fix problem
– Many responsible for today’s rise in atmospheric CO2
are no longer here; most who will be affected are not
yet born
– Each of us has insignificant impact, but we must all act
to have impact
– Let’s learn how to interpret the numbers we can get
Our dilemma
CO
2 (PPM
)
Buildings represent ~38% of Energy -- directly
Primary Energy (Quad BTUs) consumption by
sector
39
Source: US DOE
Lighting is the greatest energy user in commercial buildings
Primary Energy consumption (Quad BTUs)
40
Source: US DOE
Residential energy use can be improved
Residential energy scenarios (Quad BTUs)
41
Source: US DOE
Better building can save money!
42
Building Industry
We use lots of energy in our buildings …
We can control our use of water, electricity,
consumption and our acquisitions
43
Source: US Green Building Council
U.S. building sector (residential and commercial):
employs 8 million people; ~10% of US GDP;
~115 million households, 5 million commercial buildings;
energy consumption split ~50:50 commercial & residential
US: 72% of electricity, 55% of natural gas, 40% of primary
energy (> transportation or industry);
– per year, 40 quads of primary energy, 2.7 trillion
KW‐hr, 40% of CO2 emissions (2300 MMT; 7.5
MMTCO2 equivalent/person);
utility bill/year: ~$400B; construction volume ~$1,000B
By 2030, EIA estimates 16% growth in energy
consumption +200 GW electrical capacity
Arun Majumdar, UCB, Testimony Regarding Reducing Energy
Consumption in Buildings, US Senate Committee on Energy and
Natural Resources 44
An example: Malmo, Sweden
The best example of
sustainable development in
the world:
– Best design and analysis
methods (~2000)
– Best construction
methods
– Project provides some
good data on
performance vs.
predicted
But
Energy: 20 of 20 buildings used more than predicted
– Prefabrication needed for intended energy performance
Land: much greater density needed even for next project
– Development model did not last even a decade
Data granularity: so coarse that improvement difficult to plan
Human capital: people on project mostly lost to next phase
45
CEE 243 April 3 46
Malmo, Sweden: Actual energy much worse than Predicted
Source: Sustainable City of Tomorrow
CEE 243 April 3 47
Malmo, Sweden: Actual energy much worse than Predicted
Source: Sustainable City of Tomorrow
Malmo, Sweden: Why the discrepancies?
Overly optimistic calibration factors from
window vendors
Analysis program did not properly consider
thermal bridges
Stick construction leaks air; only
prefabrication of skin works
CEE 243 April 3 48
CEE 243 April 3 49
Motivating Problem: Oberlin College
“Performance is more compelling than design awards”
(Ivanovich 2005)
Big idea: Be careful -- predicted performance can be
different than actual
Oberlin College
CEE 243 April 3 50
CEE 243 April 3 51
Oberlin College
Source: John Scofield
Oberlin College
Energy consumption exceeds predicted
Source: John Scofield -
http://www.oberlin.edu/physics/Scofield/ASHRAEcomment.htm
CEE 243 April 3 52
CEE 243 April 3 53
Oberlin College
Energy Recovery Ventilation (ERV)
Source: John Scofield
Motivating Problem: LEED1 Astray?
The APS study concluded, however, that the nation’s
121 LEED buildings actually use 30% more energy
per square foot than the average for U.S. buildings.
– They used the median value for the LEED buildings and the
mean for others,” explains Richter. Using the mean for both
types significantly bumps up the ‘green’ buildings’ calculated
energy use.
1 Leadership in Environmental and Energy Design
http://www.businessweek.com/investing/green_business/archives/2008/09/
building_efficiency_leed_astray.html
54
Details of LEED buildings … Illinois
Regional Green Building Case Study Project: A post‐occupancy study of LEED projects in Illinois, Fall 2009 http://www.usgbc-chicago.org/wp-content/uploads/2009/08/Regional-Green-Building-Case-Study-Project-Year-1-Report.pdf
55
CEE 243 April 3 56
Building Efficiency: LEED Astray?
121 LEED buildings
(Turner and Frankel 2008)
Motivating Problem: Stanford Y2E2 It performs well, but << design objective
57
Predictions
(Tobias Maile)
based on initial
designer model
Y2E2 energy cost comparison (designer)
58
Scott Gould, Stanford Facilities CEE 243 April 3
Proposed Stanford Green Dorm
The best example of
sustainable development on
campus:
– Laudable objectives for
energy, resource use and
education
– Planned good data to
compare predicted and
performance
– Data collection methods
might transfer to next
projects
But
– Scale: Unknown methods to design for the much greater density needed to fit many units on campus, e.g., 2,300 for SU medical center
– Dorm fine for students, but what are lessons for families of professionals?
– Uncertain transfer of methods and people for next projects
– Data will probably not transfer
59 CEE 243 April 3
CIFE 2015 Sustainability objective: 25% better than 2002 – overtaken by events
US EISA 2007: by 2010, GSA must use 55% less
energy than average; by 2030 all new facilities net
zero energy
US Executive Order 13423: reduce facility energy use
per square foot by 30 percent by the end of FY 2015,
relative to 2003 baseline, i.e., metered annual energy
consumption ~55 KBTU/GSF
California 2006 law: reduce greenhouse gas
emissions to 1990 levels by 2020
60 CEE 243 April 3
Collective action can have impact: Energy/capita – US, California
61
Source: Steve Chu, LBNL, AAAS 2007 keynote CEE 243 April 3
Y2E2: 2009 Findings
Performance
Most points make sense:
ranges normal; peaks
explainable
Hot water supply temp 150oF
(design temp180oF)
Heat recovery valve position
cycles rapidly (2 of 3)
Radiant lab slab control
strategy ≠ design sequence
of operations
Night flushing not obviously
working as designed
Surprises
New second law of
thermodynamics: whole <<
sum of parts
Viscous water: Driving
pressure ~600psi
Space temp = 725oF
Missing data values
(outages?)
Some points labeled with
incorrect locations
Huge effort to analyze and
diagnose performance:
12 students * 10 weeks
looked at ~10% of building
CEE 243 April 3 62
2009 Y2E2 class findings at a glance
Some HVAC components and systems work well
Some components and systems do not work well
– Simple: many labeling and calibration errors
– Potentially significant: night flush; valve cycling behavior
– Confusing: ∑electric submeter kWhs << steam plant
Enormous effort to interpret data:
– 12 students @~100hours/quarter each to analyze ~10% of
Y2E2 ~2400 data points
– No effort at commissioning to “fix” problems
– More than a year to prepare data acquisition system to
enable this class
63
2009 Y2E2: Findings
Performance
Most points make sense:
ranges normal; peaks
explainable
Hot water supply temp 150oF
(design temp180oF)
Heat recovery valve position
cycles rapidly (2 of 3)
Radiant lab slab control
strategy ≠ design sequence
of operations
Night flushing not obviously
working as designed
Surprises
New second law of
thermodynamics: whole <<
sum of parts
Viscous water: Driving
pressure ~600psi
Space temp = 725oF
Missing data values
(outages?)
Some points labeled with
incorrect locations
Huge effort to analyze and
diagnose performance:
12 students * 10 weeks
looked at ~10% of building
CEE 243 June 3 64
Y2E2 data set
Stanford Y2E2 – 2,370 points
– 1 minute interval
– Not all setpoints are logged
– Submetering of light and plug loads at floor level
– Four representative offices with very detailed measurements
65
Examples of functioning systems in Y2E2
66 CEE 243 April 3
Example: Valve position and flow rate correlate - System works mostly during occupied hours
67
Work
week
Work
week
Work
week
Work
week
Example: Pumps show intended lead/lag operation Pump speeds > minimum speed of 25 Hz
68
MAINHOTWATERLOOP: April 1st, 2009 to April 29th, 2009
Minimum
Speed: 25 Hz
Example: Supply air temperature generally meets 65°F setpoint ±2 °F
69 CEE 243 April 3
Example: Hot water temperature difference (supply – return) correlates with outside air temperature
70
MAINHOTWATERLOOP: April 1st, 2009 to April 29th, 2009
A. As control valve opens, flow responds accordingly.
B. When the valve opens, the returning chilled water temperature drops, which means the system is functioning well.
C. During heat wave, chilled water flow rate increases greater variation in return temp
CEE 243 April 3 71
Y2E2 – missing data points
– Occupancy
– Electricity submeters by floor and per AHU zone
– Radiant slab hot water flow rate
– Tempered hot/cold water flow rates
– Manual window positions
– Main hot/cold water temperature setpoints
– Air handling unit setpoints
72 CEE 243 April 3
Identified data problems
Sensor calibration problems: 1. Hot water flow rate stays constant even though valve position
changes
2. Radiant slab valve position only 0 or 100% open (should change in 10, 5 or 1 % increments)
3. Current draw in representative offices shows integer values only
4. Sum of electrical submeters << total electricity consumption
Incorrect mapping of sensors: 5. Active beam hot water supply and return water temperature are
reversed and values are inconsistent with hot water system level temperatures
6. Chilled water valve position does not fully correlate with chilled water flow (valve position is from a different office, wrong label in BMS)
Data conversion/scaling problems: 7. Temperature values out of range (e.g., 725 °F)
8. Pressure values out of range (e.g., 600 psi)
9. Minimum flow rate is 1 GPM
10. Missing data points
73 CEE 243 April 3
Example: Radiant slab valve position only 0 or 100% open (should change in 10, 5 or 1 % increments)
74 CEE 243 April 3
4. Example: Measured (steam plant) >> sum of submeters
75 CEE 243 April 3
76
5. Active beam hot water supply and return water temperature are reversed, and values are inconsistent with hot water system level temperatures
1. Hot water flow rate stays constant even though valve position changes
6. Chilled water valve position does not fully correlate with chilled water flow (valve position is
from a different office, wrong label in BMS)
77
Some correlation No correlation
CEE 243 April 3
Identified control problems
78
Setpoint problems 11. Hot water loop temperature seems to be around 150 °F <>
Sequence of operations calls for 180 °F
Cycling problems 12. Heating coil valve cycles open and closed rapidly
13. Heat recovery bypass valve opens and closes rapidly during transitional periods
System behavior problems 14. Night purge on the 1st and 2nd floor seems to be on a regular
schedule rather than dependent on outside and inside temperatures
15. Night purge on 3rd floor seems random and does not follow control strategy
16. Radiant slab control valve position does not show step behavior as outlined in sequence of operations
17. Heat recovery cooling mode does not coincide with coil cooling mode at all times
18. Measured (heat plant) ~ ASHRAE standard >> Design objective
CEE 243 April 3
79
11. Hot water loop temperature is around 150 °F Sequence of operations calls for 180 °F
CEE 243 April 3
12. Heating coil valve cycles open and closed rapidly
80
CEE 243 April 3
12. Heating coil valve cycles open and closed rapidly (closer look)
81
0
10
20
30
40
50
60
70
4/3/2009 0:00 4/3/2009 2:24 4/3/2009 4:48 4/3/2009 7:12 4/3/2009 9:36 4/3/2009 12:00 4/3/2009 14:24 4/3/2009 16:48 4/3/2009 19:12 4/3/2009 21:36 4/4/2009 0:00
Te
mp
(F
) a
nd
Va
lve
Po
sit
ion
(%
)
Heat Coil Valve Position
Outdoor T
Setpoint T
CEE 243 April 3
Heat recovery bypass valve opens and closes rapidly during transitional periods
82 CEE 243 April 3
Night purge on the 1st and 2nd floor seems to be on a regular schedule rather than dependent on outside and inside temperatures
83 CEE 243 April 3
Night purge on 3rd floor seems random and does not follow control strategy
84 CEE 243 April 3
85
17. Heat recovery cooling mode does not coincide with coil cooling mode at all times
Cooling coil valve open, but heat recovery not in cooling mode
85
CEE 243 April 3
18. Measured good, but << design objective
86
Predictions
(Tobias Maile)
based on initial
Arup model
Scott Gould 8/19/09 CEE 243 April 3
Recommendations from building engineer Tim Troxell
87
Set point problems
Hot water loop
temperature seems to
be around 150 °F <>
Sequence of
operations calls for
180 °F
This is not a control
problem EM&CS
cascades HHW temp
based on OAT. Will map
HHW set points to BMS. Closed
Cycling problems
Heating coil valve
cycles open and
closed rapidly
Yes Yes
Tobias said this was an
AHU. This was a scaling
problem. Valve cycles 0-
2% Database was
showing 0-20% Closed Heat recovery
bypass valve opens
and closes rapidly
during transitional
periods
Yes Yes EM&CS has added a time delay between switchover 7-6-09.
Completed CEE 243 April 3
Recommendations from building engineer Tim Troxell
88
Slide 11 of 28 Identified data problems
Sensor calibration problems
Hot water flow rate
stays constant even
though valve position
changes
Yes Yes
This is from one of the
Representative offices.
Found mapping incorrect.
Graphic was looking at flow
for one room and valve
position for another.
Completed
Radiant slab valve
position only 0 or
100% open (should
change in 10,5 or 1 %
increments)
Yes
We did find problems with
radiant slab in April. ISS
modified programming. ISS
has trended and validated
sequence. Completed Current draw in
representative offices
shows integer values
only
Yes
This and others are numbers that need to be divided by 10 to get decimal points.
Closed Tobias modified database
Sum of electrical sub
meters << total
electricity consumption
Yes
This has been a problem,
We are woking with
Cupertino Electric and
Eaton Metering to resolve.
This is on the Issues list
CEE 243 April 3
Recommendations from building engineer Tim Troxell
89
Problem reported Was this In-Scope
Is this Researc
h Related
only
Should it be
Identified during
commissioning
Could this be
Identified by
continuous commission
ing program?
Comments Status
Slide 10 of 28 Y2E2 – missing data points
Occupancy Yes There is not a reliable measure of
building occupancy.
Could be funded by research
Electricity sub meters by floor
and per AHU Zone Yes
Sub meters are possible but each
panel would need LON metering this
would be expensive.
Could be funded by research
Radiant slab hot water flow
rate Yes
This was not requested. Could be
added approximately $6K.
Could be funded by research
Tempered hot/cold water flow
rates Yes
This was not requested. Could be
added approximately $6K each
Could be funded by research
Manual window positions Yes VE
Out NO
Window switches were value
engineered out of project. They are in
scope for Nano and HEC.
Could be funded by research
Main hot/cold water
temperature set points mapped
from EM&CS system
No Yes Additional EM&CS points requested
by Tobias will be mapped over.
Will be done when field server is updated.
Added to Issues list
Air handling unit set points No Yes Additional EM&CS points requested
by Tobias will be mapped over.
Will be done when field server is updated.
Added to Issues list
CEE 243 April 3
Y2E2 energy cost comparison (designer vs measured)
A (bad news): ~53% Gap: Actual - initial predicted
B (good news): ~37% Improvement: Actual - new
baseline
90
A
B
CEE 243 April 3
Y2E2 energy cost comparison (designer)
Post occupancy analysis findings by designer:
Consuming in absolute terms ~53% more energy cost
than the non-calibrated early design model
($319,000/yr vs. $491,000/yr)
- Consuming in relative terms ~54% more steam cost
than is predicted by the Calibrated Design model
($83,000 vs. $54,000 predicted)
- Consuming in relative terms approximately the same
electrical and chilled water energy cost as is predicted
by the Calibrated Design model ($408,000 vs.
$412,000 predicted)
91 CEE 243 April 3
Y2E2 energy cost comparison (designer)
Post occupancy conclusions by designer:
Since Y2E2 is exceeding savings estimates by
$50,000/yr, the financial analysis carried out during
design would show a better return on investment if
carried out today.
The relative performance appears to be in line with
the early model predictions and exceeds the 37%
energy reduction target established in the Basis of
Design.
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CEE 243 April 3 127
Recommendation: Predict and Measure …
Big Ideas
We (engineers) now can measure and predict (Y2E2) in detail;
This class teaches tools and methods you (students and energy
novices) can use to measure and predict energy in detail;
– Y2E2: some HVAC components & systems work well; others no
Energy use is a global problem/opportunity: Malmo, LEED, Y2E2,
Oberlin all have measured energy >> predicted
Clear evidence for lack in methods to design, build and operate
individual buildings with satisfactory energy performance, -- first step
toward global improvements
– ~10 students @ 1000 hours/quarter 10% of building
Buildings and grid lack shared control
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Reflective Positive:
What surprised or
encouraged you
positively?
Reflective Negative:
What surprised or
encouraged you
negatively?
Decisional:
Suggest next steps
Reflections +/∆ Analysis
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