Hawaii Energy and Environmental Technologies (HEET) Initiative Office of Naval Research Grant Award Number N0014-11-1-0391 KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL Prepared by: MKThink Prepared for: University of Hawaii at Manoa, Hawaii Natural Energy Institute March 2015
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Hawaii Energy and
Environmental Technologies
(HEET) Initiative
Office of Naval Research
Grant Award Number N0014-11-1-0391
KAWAIKINI NEW CENTURY PUBLIC
CHARTER SCHOOL
Prepared by:
MKThink
Prepared for:
University of Hawaii at Manoa, Hawaii Natural Energy Institute
March 2015
March 2015
TASK 4.2 FINAL REPORTKAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
PREPARED BY:
MKThinkMark R. Miller, AIA LEEDAP
CEO, Director of Innovation Services
PREPARED UNDER CONTRACT TO:
Office of Naval ResearchDr. Richard CarlinDepartment Head, Code 33
PREPARED FOR:
Hawaii Natural Energy InstituteUniversity of Hawaii at ManoaDr. Rick RocheleauDirector
TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL2
04/01/15 | CONTRACT NO.N00014-11-1-0391 3TABLE OF CONTENTS
Performance Dashboard 4
1 Introduction 6
2 Study Details 8
3 Performance Category 1: Energy 20
4 Performance Category 2: Interior Environment 48
5 Performance Category 3: Daylighting 62
6 System Analysis 1: 24-Hour Load Profiles by Month 70
7 System Analysis 2: Cooling 100
8 System Analysis 3: Lighting 112
9 Conclusion 120
Acknowledgements 130
Table of Contents
4 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Performance Dashboard
RECOMMENDATION 1 - AIR SUPPLY CHECKRun a system check on E Frog AC distribution system to understand the significant difference in air supply distribution effectiveness. Consider monitoring user patterns as a check against building system use by: providing daily use schedules, system program settings, and/or install additional monitoring.
RECOMMENDATION 2 - AC/FAN/LOUVER CHECKStudy how AC and Fans/Louvers are interacting in order to move towards optimal use goals. Determine a way to distinguish between automatic and manual user selected use of Fans and AC. Determine an alternative method to monitor Louver use, so that it can be related more instantaneously to Fan/AC use.
RECOMMENDATION 3 - ADJUST TC ASSUMPTIONSAdjust evaluation techniques and assumptions for user thermal comfort: conduct surveys and/or potentially field validate assumptions through onsite observation.
RECOMMENDATION 4 - INVESTIGATE OCCUPANT BEHAVIOR RELATED TO ENERGY USEIncorporate class schedules to analysis to better tie energy demand patterns to occupant activities.
1: W-E PLATFORM COMPARISON - IS PERFORMANCE CONSISTENT ACROSS PLATFORMS?4 OF 9 PERFORMANCE MEASURES VARIED BY GREATER THAN 20% ACROSS PLATFORMSInterpretation 1: The majority of performance measures across the two platforms (5 of 9) showed less than 20% difference in annual results. However, selected systems did show moderate (20-50%) to significant (>50%)differences: Air Supply and distribution temperatures varied significantly (>50%) due to increases in distribution temperature in the E Frog during the last two quarters; Fan usage between the two buildings was moderately different (20-50%) without a corresponding difference in AC usage; and Thermal Comfort* conditions varied by 20% across the two platforms with the platform using the least fan energy having the higher thermal comfort - which suggests the PMV model and assumptions are not a good fit for the building type and/or user behavior.
2: MODEL COMPARISON - DO PLATFORMS PERFORM AS PREDICTED BY MODELS?BOTH PLATFORMS USED LESS ENERGY THAN ANTICIPATED (42-48% LESS), BUT ALSO LESS THAN OPTIMAL Interpretation 2: West and East Frogs both out-performed model predictions of total annual energy consumption. However, selected systems did not outperform their individual targets. Lighting systems were used more than the anticipated/optimal amount, but that appears to be affected by outdoor lighting being left on at night that may be related to security. Additionally, the AC systems were used more than optimal and often at air temperatures below the optimal “kick-in” temp of 82°F, especially in the E Platform.
3: STANDARD COMPARISON - DO PLATFORMS PERFORM BETTER THAN ESTABLISHED STANDARDS?3 OF 4 PERFORMANCE MEASURES WERE WITHIN STANDARD REC’S FOR AT LEAST ONE PLATFORMInterpretation 3: While 3 of 4 performance measures showed >90% adherence to standards in at least one platform, Thermal Comfort performance showed less than 50% adherence to standard recommendations. However, it appears that the relatively low performance may be a result of model assumptions for ASHRAE using clothing insulation and metabolic rates that, upon further investigation, tend to cause large variations in model fit. Adjusting those assumptions to fit user behavior as inferred through use of building systems may lead to a better calibration of the PMV calculation and to a higher percentage of PMV scores within the comfort range (see Appendix for details). Lighting use and illuminance varied between the two platforms with E Frog meeting illuminance criteria using daylighting more than W Frog, leading to higher than anticipated indoor lighting loads at W Frog. Air Supply temperature stability across the distribution plenums in the E Frog also showed less than 50% adherence to expectations and should be inspected for issues.
PERFORMANCE CATEGORY 2. MODEL COMPARISON 1. W-E PLATFORM COMPARISON
PERFORMANCE CATEGORY 1:ENERGY
West EastDifference b/tw W & E compared to Optimal:
Anticipated* Optimal* Anticipated* Optimal*
Total (kWh/yr per building)% above or below model value ( +/- )
- 42% - 9% - 48% - 19% 10%
AC - 81% + 31% - 80% + 37% 6%
Fan + 225% - 29% + 115% - 53% 24%
Interior Lighting** + 34% + 19% 15%
Plug** - 45% - 46% 1%
Exterior Lighting*** 1087 kWh 1067 kWh 2%
Solar Radiation (Cumulative Insolation) -10%* N/A
3. STANDARD COMPARISON 1. W-E PLATFORM COMPARISON
PERFORMANCE CATEGORY 2:INTERIOR ENVIRONMENT
West East Difference b/tw W & E compared to standard:
Thermal Comfort (PMV):% time w/in ASHRAE Comfort Zone
25%** 45%** 20%
CO2:% time below ASHRAE threshold
99.94% 99.95% 0.01%
Air Supply: % time dist. temp within 10°F of supply temp
92% 36% 56%
PERFORMANCE CATEGORY 3:DAYLIGHTING
West East Difference b/tw W & E compared to standard:
Illuminance Level% time Lights off w/ >5 ft-cd & lll. ratio <5
70.1% 91.7% 21.6%
*Anticipated model predictions are based on inefficient use and interaction of building systems. Optimal model predictions assume efficient building system use and interaction, specifically for AC/Fans. **Interior Lighting and Plug load model predictions are the same for anticipated/optimal, and lower use is considered preferable. ***Exterior Lighting use was assumed to be 0 kWh in the Phase II ONR Report Energy Demand Models (as seen on page 13). Therefore energy use totals are presented for Exterior Lighting, instead of percentage comparisons to the model.
6 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
In support of the Hawaii Natural Energy Institute’s Project: Hawaii Energy and Environmental Technologies (HEET) Initiative 2010, and under Contract No. N00014-11-1-0391, MKThink instrumented two identical Project Frog high-performance modular buildings at the Kawaikini New Century Public Charter School in Līhu’e, Kauai for testing and analysis.
The two identical portable classrooms were built using passive design elements to decrease energy demand. They are named Hale Akamai I & II, but will be referred to as the West and East buildings throughout the report.
Under this project, the buildings have been monitored for energy and building performance from March 2013 to March 2014. This study will evaluate and report on one year of energy and environmental (interior & exterior) data from the two buildings. Results will be compared between the two buildings, as well as to models which were previously developed specificly for the Hale Akamai buildings and Līhu’e climate. Based upon the findings, recommendations for improved performance as well as areas for future study will be presented.
8 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Study Details2The analysis of this study is split into two parts: Performance Categories & System Analyses.
In the Performance Category sections, data collected from each building is compared to previously established performance criteria. The performance criteria are specific to the Hale Akamai buildings and Līhu’e climate, and were designed using both models and established guidelines for building performance. The intent of the Performance Category part of the study is to present building performance results using a structured, standardized analysis process which can be implemented in future studies of other buildings. The three Performance Categories are: Energy, Interior Environment and Daylighting.
The System Analysis sections look at building systems as a whole and allow for more open-ended analyses across different metrics. While the Performance Category sections focus on performance criteria specific to individual metrics, the System Analysis sections focus on how the different metrics influence each other. Consequently, findings from the Performance Category sections will guide the direction of the System Analysis sections and give clues as to which aspects of the system are underperforming. The System Analysis sections will also focus on how system patterns differ from month to month. The three System Analyses are: 24-Hour Load Profiles by Month, Cooling and Lighting.
Throughout the report, identical charts from each building will be presented side-by-side across pages. Left-hand pages (even page #) will show West building charts, while right-hand pages (odd page #) will show East building charts. The following icons will be seen in the top corners of the pages:
12 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Methodology: Performance Categories21 EnergyCompared measured energy use to energy demand models taken from the Phase II ONR Report. The energy demand models are specific for the Hale Akamai buildings and Līhu’e climate. There are models for the following energy usage groups: mechanical cooling (AC), fans, interior lighting and plugs.
For each energy usage group, there are models representing high, anticipated and optimal estimates of energy use. The following page, ‘Methodology: Energy Demand Models’, describes each model.
Finally, solar radiation measurements from the weather station atop the East Building roof are compared to solar radiation model data from the National Solar Radiation Data Base (hosted by National Renewable Energy Laboratory).
2 Interior EnvironmentThermal comfort is modeled using Predicted Mean Vote (PMV), which takes the following inputs: air temperature, relative humidity, mean radiant temperature, air speed, clothing insulation and metabolic rate. Building performance in relation to thermal comfort is then judged by the percentage of time each building’s PMV value is within the ASHRAE Comfort Zone (-0.5 ≤ PMV value ≤ 0.5).
Building performance in relation to air quality is judged by whether or not indoor carbon dioxide concentrations exceed benchmarks for inadequate ventilation (ASHRAE) or minor cognitive impairment (Satish et al., 2012).
Supply air distribution performance is measured by comparing the plenum inlet temperature to the temperatures by floor diffusers in the northwest, center and southeast areas of the room. Building performance in relation to supply air distribution is then judged by the percentage of time ΔT ≤ 10°F between the plenum inlet and floor diffusers.
3 DaylightingIlluminance levels are measured at the teaching wall and on the ceiling. Ceiling illuminance is used as a proxy for working surface illuminance. The problem of glare is measured using Illuminance ratio, which is the ratio between wall and working surface illuminance. Building performance in relation to daylighting is judged by the percentage of time lights were off while the wall illuminance exceeded 5 ft-cd and illuminance ratio stayed below 5.
04/01/15 | CONTRACT NO.N00014-11-1-0391 13
2 Methodology: Energy Demand Models
STUDY DETAILS
High Anticipated OptimalThe high estimate assumes that natural ventilation is not used at all - that instead, air conditioning is used, with a thermostat setpoint of 77°F. In addition to air conditioning, the high estimate also assumes that the fans are used, even though they should not be on while the buildings are in active cooling mode. This is simply done to be conservative. The high estimate also assumes that daylighting is not used, so that electric lights are used during 100% of occupied hours. This, in turn, is assumed to increase cooling loads by 11%.
The anticipated estimate is a middle value between the two extremes of high and optimal estimates. Anticipated estimates assume that daylighting is used but that natural ventilation is not.
The optimal estimate for each site assumes that the buildings are cooled by natural ventilation up until a thermostat setpoint of 82°F, at which point they switch from passive to active mode, closing the ventilation louvers or windows and turning on air conditioning. This should be comfortable despite the higher temperature setpoint because of the building’s features such as ceiling fans, proper solar control, and reduced interior mean radiant temperatures. The optimal estimate also assumes that daylighting is used to reduce lighting energy.
Total 8,124 kWh/year 5,984 kWh/year 3,806 kWh/yearSource: Phase II ONR Report
14 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Methodology: Date Range2
Active/Non-Active DefinitionsActive Days Non-holiday weekdays (includes summer break)
Non-Active Days Weekends and holidays (excludes summer break)
Monthly Day TotalsMar ‘13 Apr ‘13 May ‘13 Jun ‘13 Jul ‘13 Aug ‘13 Sep ‘13 Oct ‘13 Nov ‘13 Dec ‘13 Jan ‘14 Feb ‘14 Mar ‘14 Total
Active Days 5 22 22 19 22 21 20 23 18 15 14 19 10 230
Non Act. Days 6 8 9 11 9 10 10 8 12 16 17 9 5 130
School Days 5 22 22 5 0 19 20 23 18 15 14 19 10 192
Holidays3/26/13 Prince Jonah Kuhio Kalanianaole Day (HI)
3/29/13 Good Friday (HI)
5/27/13 Memorial Day
6/8/13 - 8/4/13 SUMMER BREAK
8/16/13 Statehood Day (HI)
9/2/13 Labor Day
11/11/13 Veterans Day
11/28/13 - 11/29/13 Thanksgiving Day
12/21/13 - 1/12/14 WINTER BREAK
1/20/14 Dr. Martin Luther King Jr. Day
2/17/14 President’s Day
Study PeriodTotal 3/21/2013 - 3/15/2014
Quarter 1 3/21/2013 - 6/20/2013
Quarter 2 6/21/2013 - 9/20/2013
Quarter 3 9/21/2013 - 12/20/2013
Quarter 4 12/21/2013 - 3/15/2014
04/01/15 | CONTRACT NO.N00014-11-1-0391 15
Equipment: Sensor List2
STUDY DETAILS
Energy
Mechanical Cooling (AC)Condensing Unit 1 (W/E)
Exhaust Fan 1 (W/E)
FansCeiling Fans 1 (W/E)
Fan Coil Unit 1 (W/E)
LightingMain Space 1 (W/E)
Wall and Exterior 1 (W/E)
Louvers Louver Actuator 1 (W/E)
Panel Feed (System Total) Panel Feed 1 (W/E)
Interior Environment
Temperature
Floor - Plenum 3 (W/E)
Floor - Surface 3 (W/E)
Wall - Air 2 (W/E)
Wall - Surface 2 (W/E)
HVAC - End 1 (W/E)
Relative HumidityRoom 1 (W/E)
HVAC 1 (W/E)
Air Speed Room 1 (W/E)
Carbon Dioxide Room 1 (W/E)
Weather StationTemperature
Roof (only East building)
1
Relative Humidity 1
Solar Radiation 3
Wind Speed, Gust Speed 1
Wind Direction 1
Rain 1
Dew Point 1
Air Pressure 1
Daylighting
IlluminanceWall 1 (W/E)
Ceiling 1 (W/E)
16 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
2 Equipment: Sensor Layouts
Cat 5 Cable
18-4 Cable
04/01/15 | CONTRACT NO.N00014-11-1-0391 17
W E
STUDY DETAILS
Cat 5 Cable
18-4 Cable
18 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
2 Equipment: Status Summary
Equipment Item LocationEquipment Operational
(functioning)
Communication Operational
Sensor Operational
(data accurate)
AMX Ni-2100 Central Controller E/W
Serial Communications Adapter E/W
Dent Industries Powerscout 1 E/W
Split Core Current Transformers E/W
1-Wire Network Hub E/W
1-Wire Network 2 Port Box E/W
1-Wire Network 4 Port Box E/W
Floor Surface Digital Temp Sensors E/W
Room Air Digital Temp Sensors E/W
Wall Surface Digital Temp Sensor E/W
Analog Sensor Hub (standard) E/W
Analog Sensor Hub (photometric) E/W
LI-COR LI-210SZ Photometric Sensor E/W
Air Velocity Sensor E/W
Non-Dispersive Infrared CO2 Analyzer E/W
Wall Mounted Humidity Transmitter E/W
YesNo
04/01/15 | CONTRACT NO.N00014-11-1-0391 19
2 Notes
STUDY DETAILS
Energy NotesEnergy and power calculations are performed by summing power values in kilowatts (KW) and dividing by a factor of 6 to account for 10 minute sensor collection frequency, resulting in kilowatt hour (kWh) values. System total energy and plug load energy calculation changed when platform PV panels were installed, making Total Panel Feed data inaccurate.
Before 9/25/13: Total System Power came from the Panel Feed sensor. Plug load was calculated by subtracting the sum of all system loads (AC, Fans, Lighting, Louvers) from the Panel Feed values.
After 9/25/13: Panel Feed values were not usable, therefore Plug Load average power value to date was used as constant value and Total System Power was a sum of all systems (AC, Fans, Lighting, Louvers) with the Plug Load constant also added.
Possible issue with November 2013 West Building mechanical cooling power data, as suggested by comparing it to East building data from the same month.
The pyranometer has a maximum around 1277 W/m2, which was confirmed by the manufacturer. Therefore, measured cumulative solar insolation was potentially less than modeled.
20 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Measured energy use is compared to energy demand models taken from the Phase II ONR Report. The energy demand models are specific for the Hale Akamai buildings and Līhu’e climate. There are models for the following energy usage groups: mechanical cooling (AC), fans, interior lighting and plugs. For each energy usage group, there are models representing high, anticipated and optimal estimates of energy use. The models are described in ‘Methodology: Energy Demand Models’, on page 13.
For each energy usage group, there are average daily use totals and 24-hour load profiles. The charts display averages for active, non-active and top 5% usage days.
Here is the color scheme for energy usage groups used in this section:
Finally, solar radiation measurements from the weather station atop the East Building roof are compared to solar radiation model data from the National Solar Radiation Data Base (hosted by National Renewable Energy Laboratory). However, the validity of the solar radiation data is questionable due to sensor issues, as mentioned in ‘Notes’, on page 19. This solar radiation analysis is in Section A of the Appendix.
Key findings from this performance category are highlighted on the following pages (22-23). The complete ‘Findings’ are on pages 122-123.
Performance Category 1: Energy3
04/01/15 | CONTRACT NO.N00014-11-1-0391 21PERFORMANCE CATEGORY 1: ENERGY
Findings 22
3.01 Total System Energy Use [W/E] 24
3.02 Total Energy Use by Category [W/E] 26
3.03 Average Daily Energy Use: Total [W/E] 28
3.04 Average 24-Hour Load Profiles: Total [W/E] 30
3.05 Average Daily Energy Use: Mechanical Cooling [W/E] 32
3.06 Average 24-Hour Load Profiles: Mechanical Cooling [W/E] 34
3.07 Average Daily Energy Use: Fans [W/E] 36
3.08 Average 24-Hour Load Profiles: Fans [W/E] 38
3.09 Average Daily Energy Use: Total Lighting [W/E] 40
3.10 Average 24-Hour Load Profiles: Total Lighting [W/E] 42
3.11 Average Daily Energy Use: Plugs [W/E] 44
3.12 Average 24-Hour Load Profiles: Plugs [W/E] 46
22 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Findings3
19% 21% 8% 31% 20%
22% 15%5% 35% 22%
656 kWh
686 kWh
714 kWh
472 kWh
289 kWh
159 kWh
1087 kWh
1067 kWh
706 kWh
691 kWh
A HO
A H,O
A,O H
H,A,O
AO3452 kWh
3074 kWh
Performance Category 1: Energy
The total energy use for both buildings was below both the anticipated and optimal estimates. The West building used 13% more total energy than the East. In terms of the percentage breakdown by energy usage group, the biggest discrepency between the buildings was in fan usage, which accounted for 21% of the West total and 15% of the East total.
None of the individual energy usage groups in either building had an energy use total exceeding the high estimate. The East building used more energy on mechanical cooling, despite using less energy overall. The West building used 51% more energy on fans and 82% more energy on interior lighting. The difference in plug load was 2%.
Plu
gs W
E
Energy Demand Models
O: Optimal A: AnticipatedH: High
Ext
erio
r Li
ght
ing W
E
Inte
rio
r Li
ght
ing W
E
Fans
W
E
Mec
h.
Co
olin
g W
E
TOTA
L W
E
04/01/15 | CONTRACT NO.N00014-11-1-0391 23PERFORMANCE CATEGORY 1: ENERGY
EW
W E
EW
EW
The West building had PMV values outside the Comfort Zone 75% of the time
The East building had PMV values outside the Comfort Zone 55% of the time.
In both buildings, carbon dioxide concentrations never exceeded benchmarks for inadequate ventilation (ASHRAE) or minor cognitive impairment (Satish et al., 2012).
In the West building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 8% of the time.
In the East building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 64% of the time.
In the West building, during active days between 6:00 AM and 6:30 PM, the lights were on for 21% of the time. For 9% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
In the East building, during active days between 6:00 AM and 6:30 PM, the lights were on for 6% of the time. For 2% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
Performance Category 2: Interior Environment
Performance Category 3: Daylighting
24 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.01 Total System Energy Use
Findings• The total energy use for the West building was below both the anticipated and optimal estimates.• Fan usage accounted for 21% of the total energy use in the West building.
3452 kWh
Mechanical Cooling
Fans
Interior Lighting
Exterior Lighting
Plugs
Anticipated
Optimal
Ene
rgy
[kW
h]
0
1000
2000
3000
4000
5000
6000
0
04/01/15 | CONTRACT NO.N00014-11-1-0391 25
W E
PERFORMANCE CATEGORY 1: ENERGY
Findings• The total energy use for the East building was below both the anticipated and optimal estimates.• The West building used 13% more total energy than the East.• Fan usage accounted for 15% of the total energy use in the East building.
3074 kWh
Mechanical Cooling
FansInterior Lighting
Exterior Lighting
Plugs
Anticipated
Optimal
Ene
rgy
[kW
h]
0
1000
2000
3000
4000
5000
6000
0
26 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.02 Total Energy Use by Category
Findings• None of the individual energy usage groups in the West building had an energy use total exceeding the high estimate.
Findings• None of the individual energy usage groups in the East building had an energy use total exceeding the high estimate.• The East building used more energy on mechanical cooling, despite using less energy overall.• The West building used 51% more energy on fans• The difference in total plug load between the West and East buildings was 2%.
28 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
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3.03 Average Daily Energy Use: Total
27.73
11.45
5.83
11.45
5.83
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
5
10
15
20
25
30
Top 5% Usage Day Active Day Non Active Day
04/01/15 | CONTRACT NO.N00014-11-1-0391 29
W E
PERFORMANCE CATEGORY 1: ENERGY
28.16
10.53
5.17
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
5
10
15
20
25
30
Top 5% Usage Day Active Day Non Active Day
30 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.04 Average 24-Hour Load Profiles: Total
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 31
W E
PERFORMANCE CATEGORY 1: ENERGY
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
32 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
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3.05 Average Daily Energy Use: Mechanical Cooling
13.58
2.66
0.14
2.66
0.14
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
2
4
6
8
10
12
14
16
18
20
Top 5% Usage Day Active Day Non Active Day
04/01/15 | CONTRACT NO.N00014-11-1-0391 33
W E
PERFORMANCE CATEGORY 1: ENERGY
18.26
2.89
0.08
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
2
4
6
8
10
12
14
16
18
20
Top 5% Usage Day Active Day Non Active Day
34 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
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3.06 Average 24-Hour Load Profiles: Mechanical Cooling
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 35
W E
PERFORMANCE CATEGORY 1: ENERGY
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
36 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
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3.07 Average Daily Energy Use: Fans
10.25
2.56
0.82
2.56
0.82
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
1
2
3
4
5
6
7
8
9
10
11
Top 5% Usage Day Active Day Non Active Day
04/01/15 | CONTRACT NO.N00014-11-1-0391 37
W E
PERFORMANCE CATEGORY 1: ENERGY
8.24
1.79
0.44
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
1
2
3
4
5
6
7
8
9
10
11
Top 5% Usage Day Active Day Non Active Day
38 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
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3.08 Average 24-Hour Load Profiles: Fans
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 39
W E
PERFORMANCE CATEGORY 1: ENERGY
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
40 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.09 Average Daily Energy Use: Total Lighting
9.83
4.18
3.10
4.18
3.10
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
1
2
3
4
5
6
7
8
9
10
11
Top 5% Usage Day Active Day Non Active Day
04/01/15 | CONTRACT NO.N00014-11-1-0391 41
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PERFORMANCE CATEGORY 1: ENERGY
8.27
3.70
3.01
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
1
2
3
4
5
6
7
8
9
10
11
Top 5% Usage Day Active Day Non Active Day
42 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.10 Average 24-Hour Load Profiles: Total Lighting
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 43
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PERFORMANCE CATEGORY 1: ENERGY
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
44 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.11 Average Daily Energy Use: Plugs
3.85
2.071.77
2.071.77
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
1
2
3
4
5
6
7
8
9
10
11
Top 5% Usage Day Active Day Non Active Day
04/01/15 | CONTRACT NO.N00014-11-1-0391 45
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PERFORMANCE CATEGORY 1: ENERGY
6.86
2.121.61
Ave
rag
e D
aily
Ene
rgy
Use
[kW
h]
0
1
2
3
4
5
6
7
8
9
10
11
Top 5% Usage Day Active Day Non Active Day
46 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
3.12 Average 24-Hour Load Profiles: Plugs
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 47
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PERFORMANCE CATEGORY 1: ENERGY
Top 5% Usage DayActive DayNon Active Day
Po
wer
[kW
]
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
48 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Thermal comfort is modeled using Predicted Mean Vote (PMV), which takes the following inputs: air temperature, relative humidity, mean radiant temperature, air speed, clothing insulation and metabolic rate. Building performance in relation to thermal comfort is then judged by the percentage of time each building’s PMV value is within the ASHRAE Comfort Zone (-0.5 ≤ PMV value ≤ 0.5). Assumptions used while calculating PMV are stated in ‘Notes’, on page 19.
The ‘5% most/least comfortable day’ averages from charts 4.01 and 4.02 are calculated by finding the 5% of days with the highest and lowest percentages of PMV values within the ASHRAE Comfort Zone. Building performance in relation to air quality is judged by whether or not indoor carbon dioxide concentrations exceed benchmarks for inadequate ventilation (ASHRAE) or minor cognitive impairment (Satish et al., 2012).
Supply air distribution performance is measured by comparing the plenum inlet temperature to the temperatures by floor diffusers in the northwest, center and southeast areas of the room. Building performance in relation to supply air distribution is then judged by the percentage of time ΔT ≤ 10°F between the plenum inlet and floor diffusers. The supply air charts (4.04 - 4.05) only use data from days with AC usage.
Key findings from this performance category are highlighted on the following pages (50-51). The complete ‘Findings’ are on pages 122-123.
4.01 Average 24-Hour Predicted Mean Vote (PMV) Profiles [W/E] 52
4.02 Percentage of Time PMV within Comfort Zone [W/E] 54
4.03 Average 24-Hour Carbon Dioxide Concentration Profiles [W/E] 56
4.04 Average 24-Hour Supply Air Temperature Profiles [W/E] 58
4.05 Supply Air Distribution Criteria Building Comparison 60
50 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Findings4
19% 21% 8% 31% 20%
22% 15%5% 35% 22%
656 kWh
686 kWh
714 kWh
472 kWh
289 kWh
159 kWh
1087 kWh
1067 kWh
706 kWh
691 kWh
A HO
A H,O
A,O H
H,A,O
AO3452 kWh
3074 kWh
Performance Category 1: Energy
The total energy use for both buildings was below both the anticipated and optimal estimates. The West building used 13% more total energy than the East. In terms of the percentage breakdown by energy usage group, the biggest discrepency between the buildings was in fan usage, which accounted for 21% of the West total and 15% of the East total.
None of the individual energy usage groups in either building had an energy use total exceeding the high estimate. The East building used more energy on mechanical cooling, despite using less energy overall. The West building used 51% more energy on fans and 82% more energy on interior lighting. The difference in plug load was 2%.Energy
The West building had PMV values outside the Comfort Zone 75% of the time.
The East building had PMV values outside the Comfort Zone 55% of the time.
In both buildings, carbon dioxide concentrations never exceeded benchmarks for inadequate ventilation (ASHRAE) or minor cognitive impairment (Satish et al., 2012).
In the West building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 8% of the time.
In the East building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 64% of the time.
In the West building, during active days between 6:00 AM and 6:30 PM, the lights were on for 21% of the time. For 9% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
In the East building, during active days between 6:00 AM and 6:30 PM, the lights were on for 6% of the time. For 2% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
Performance Category 2: Interior Environment
Performance Category 3: Daylighting
52 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
4.01 Average 24-Hour Predicted Mean Vote (PMV) Profiles
04/01/15 | CONTRACT NO.N00014-11-1-0391 53
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PERFORMANCE CATEGORY 2: INTERIOR ENVIRONMENT
54 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
Percentage of Time PMV within Comfort Zone4.02
Findings• The West building had PMV values outside the Comfort Zone 75% of the time.
24.69% 24.84% 24.65%
89.00%
0%
% o
f ti
me
wit
hin
AS
HR
AE
Co
mfo
rt Z
one
0
10
20
30
40
50
60
70
80
90
100
Overall Active Day Non Active Day 5% Most Comf. Day 5% Least Comf. Day
04/01/15 | CONTRACT NO.N00014-11-1-0391 55
W E
PERFORMANCE CATEGORY 2: INTERIOR ENVIRONMENT
Findings• The East building had PMV values outside the Comfort Zone 55% of the time.
44.95% 44.00% 45.23%
87.87%
0%
% o
f ti
me
wit
hin
AS
HR
AE
Co
mfo
rt Z
one
0
10
20
30
40
50
60
70
80
90
100
Overall Active Day Non Active Day 5% Most Comf. Day 5% Least Comf. Day
56 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
Average 24-Hour Carbon Dioxide Concentration Profiles4.03
Findings• In the West building, carbon dioxide concentrations never exceeded benchmarks for inadequate ventilation (ASHRAE) or minor
cognitive impairment (Satish et al., 2012).
Top 5% CO2 DayActive DayNon Active Day
Minor Cognitive Impairment (Satish et al., 2012)
Proxy for Inadequate Ventilation (ASHRAE)
CO
2 C
onc
entr
atio
n [p
pm
]
300
400
500
600
700
800
900
1000
1100
1200
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 57
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PERFORMANCE CATEGORY 2: INTERIOR ENVIRONMENT
Findings• In the East building, carbon dioxide concentrations never exceeded benchmarks for inadequate ventilation (ASHRAE) or minor
cognitive impairment (Satish et al., 2012).
Top 5% CO2 DayActive DayNon Active Day
Minor Cognitive Impairment (Satish et al., 2012)
Proxy for Inadequate Ventilation (ASHRAE)
CO
2 C
onc
entr
atio
n [p
pm
]
300
400
500
600
700
800
900
1000
1100
1200
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
58 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
Average 24-Hour Supply Air Temperature Profiles4.04
SE PlenumCenter PlenumNW PlenumPlenum Inlet
Tem
per
atur
e [°
F]
64
66
68
70
72
74
76
78
80
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 59
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PERFORMANCE CATEGORY 2: INTERIOR ENVIRONMENT
SE PlenumCenter PlenumNW PlenumPlenum Inlet
Tem
per
atur
e [°
F]
64
66
68
70
72
74
76
78
80
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
60 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Supply Air Distribution Criteria Building Comparison4.05
Findings• In the West building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 8% of the time.• In the East building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 64% of the time.
92%
8%
36%
64%
ΔT<10°F between plenum inlet and floor diffusersΔT≥10°F between plenum inlet and floor diffusers
62 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Illuminance levels are measured at the teaching wall and on the ceiling. Ceiling illuminance is used as a proxy for working surface illuminance. The problem of glare is measured using Illuminance ratio, which is the ratio between wall and working surface illuminance. Building performance in relation to daylighting is judged by the percentage of time lights were off while the wall illuminance exceeded 5 ft-cd and illuminance ratio stayed below 5.
The ‘5% lowest illuminance day’ average profile from charts 5.01 was calculated by finding the 5% of days with the lowest average illuminance values.
Key findings from this performance category are highlighted on the following pages (64-65). The complete ‘Findings’ are on pages 122-123.
5.01 Average 24-Hour Illuminance Profiles [W/E] 66
5.02 Daylighting Criteria Building Comparison 68
64 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Findings5
19% 21% 8% 31% 20%
22% 15%5% 35% 22%
656 kWh
686 kWh
714 kWh
472 kWh
289 kWh
159 kWh
1087 kWh
1067 kWh
706 kWh
691 kWh
A HO
A H,O
A,O H
H,A,O
AO3452 kWh
3074 kWh
Performance Category 1: Energy
The total energy use for both buildings was below both the anticipated and optimal estimates. The West building used 13% more total energy than the East. In terms of the percentage breakdown by energy usage group, the biggest discrepency between the buildings was in fan usage, which accounted for 21% of the West total and 15% of the East total.
None of the individual energy usage groups in either building had an energy use total exceeding the high estimate. The East building used more energy on mechanical cooling, despite using less energy overall. The West building used 51% more energy on fans and 82% more energy on interior lighting. The difference in plug load was 2%.Energy
The West building had PMV values outside the Comfort Zone 75% of the time
The East building had PMV values outside the Comfort Zone 55% of the time.
In both buildings, carbon dioxide concentrations never exceeded benchmarks for inadequate ventilation (ASHRAE) or minor cognitive impairment (Satish et al., 2012).
In the West building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 8% of the time.
In the East building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 64% of the time.
In the West building, during active days between 6:00 AM and 6:30 PM, the lights were on for 21% of the time. For 9% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
In the East building, during active days between 6:00 AM and 6:30 PM, the lights were on for 6% of the time. For 2% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
Performance Category 2: Interior Environment
Performance Category 3: Daylighting
66 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
5.01 Average 24-Hour Illuminance Profiles
Active Day5% Lowest Illuminance Day
Illum
inan
ce [
ft-c
]
0
5
10
15
20
25
30
35
40
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
04/01/15 | CONTRACT NO.N00014-11-1-0391 67
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PERFORMANCE CATEGORY 3: DAYLIGHTING
Active Day5% Lowest Illuminance Day
Illum
inan
ce [
ft-c
]
0
5
10
15
20
25
30
35
40
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
68 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Daylighting Criteria Building Comparison5.02
70%
21%
9%
92%
6%
2%
Lights Off & Illuminance Criteria Met (>5 ft-cd & Illum. ratio <5)*Lights On*Lights Off & Illuminance Criteria NOT Met*
W E
*(from 6:00 AM - 6:30 PM on active days)
Findings• In the West building, during active days between 6:00 AM and 6:30 PM, the lights were on for 21% of the time. For 9% of the time,
the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).• In the East building, during active days between 6:00 AM and 6:30 PM, the lights were on for 6% of the time. For 2% of the time,
the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
70 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
System Analysis 1: 24-Hour Load Profiles by Month6Daily load profiles for each building are averaged for each month in charts 6.02 - 6.13. Charts 6.01 shows the average daily totals for all months.
Energy usage groups used in this section are more detailed than those used in the ‘Performance Category 1: Energy’ section. The lighting group is broken into interior and exterior lighting. Also, an energy usage group for louvers is used in this section. However, louver energy use makes up a very small percentage (< 1%) oftotal energy use, and its inclusion does little to change the overall load profiles.
Here is the color scheme (updated from ‘Performance Cateogry 1: Energy’, page 20) for energy usage groups used in this section:
Totals from June and July are lower than the rest of the year due to summer break. Totals from March 2013 are also lower than expected since the study period began in the middle of this month.
Finally, as mentioned in ‘Notes’ on page 19, there is a possible issue with November 2013 West building mechanical cooling power data, as suggested by comparing it to East building data from the same month (charts 6.10). One possible explaination is that the mechanical cooling energy sensor malfunctioned during this month, and the energy was then instead counted as plug energy.
Key interpretations from this section are summarized on pages 72-73. Each interpretation is explained with findings used as evidence.
6.01 Average Daily Energy Use Totals, by Month [W/E] 74
6.02 Average 24-Hour Load Profiles: March 2013 [W/E] 76
6.03 Average 24-Hour Load Profiles: April 2013 [W/E] 78
6.04 Average 24-Hour Load Profiles: May 2013 [W/E] 80
6.05 Average 24-Hour Load Profiles: June 2013 [W/E] 82
6.06 Average 24-Hour Load Profiles: July 2013 [W/E] 84
6.07 Average 24-Hour Load Profiles: August 2013 [W/E] 86
6.08 Average 24-Hour Load Profiles: September 2013 [W/E] 88
6.09 Average 24-Hour Load Profiles: October 2013 [W/E] 90
6.10 Average 24-Hour Load Profiles: November 2013 [W/E] 92
6.11 Average 24-Hour Load Profiles: December 2014 [W/E] 94
6.12 Average 24-Hour Load Profiles: January 2014 [W/E] 96
6.13 Average 24-Hour Load Profiles: February 2014 [W/E] 98
72 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Interpretations6
Before the 2013 summer break, the East building used more energy than the West; after the break, the West used more energy
As seen in charts 6.01, in Apr ‘13 and May ‘13 the East building used more energy than the West.
The 2013 summer break occured in June and July, as listed in ‘Methodology: Date Range’ on page 14.
For every month beginning in Aug ‘13 until the end of the study period (Feb ‘14), the West building used more energy than the East.
February 2014 had the biggest discrepancy in energy use patterns between buildings*
*This is only looking at “complete” months without interruptions from vacations or the start/end of the study period (Apr ‘13, May ‘13, Aug ‘13, Sep ‘13, Oct ‘13, Nov ‘13, Feb ‘14)
As seen in charts 6.01, the West building used 39% more energy than the East in Feb ‘14.
For the East building, Feb ‘14 had the lowest energy use among “complete” months, while for the West building more energy was used in Feb ‘14 than in Apr ‘13 or May ‘13.
The load profiles in charts 6.13 show that the discrepancy in energy use between buildings occured in the afternoon. In the West building, AC and fan use increased in the afternoon while interior lighting use continued from the morning. Meanwhile in the East building, AC, fan and interior lighting use ceased between 3:00 PM and 5:00 PM.
AC usage dipped during lunchtime in East building from August to October, 2013
As seen in charts 6.07 - 6.09, there are differences in the shapes of the mechnical cooling load profiles of the two buildings. The East load profiles show dips occuring at around 12:00 PM for the three months. Meanwhile, the West load profiles have no such dips which clearly separate the morning load from afternoon load.
East building interior lighting use patterns changed in November 2013, when daytime usage became consistent
As seen in charts 6.03 - 6.09, East building interior lighting use occured mostly at night before Nov ‘13. Meanwhile, the West building had consistent daytime usage over the same period.
Starting in Nov ‘13, the East building interior lighting began to be used consistently during school hours, with a load profile similar to that of the West building. This can be seen in charts 6.10 - 6.14.
Plug load consistent throughout the day and night for both buildings during the entire study period
The only exception was in May ‘13 for the East building, when there was a noticible increase in plug energy use during school hours. This can be seen in charts 6.04.
The plug load data for the West building in Nov ‘13 is most likely erroneous labeled and should really be counted as mechanical cooling energy use, as mentioned in ‘Notes’ on page 19.
Highest energy usage months coincided with months when fans were left on overnight
The three months with the highest overnight fan energy use (Aug ‘13, Sep ‘13 and Dec’13, all for West building), were also three out of the top four highest energy usage months.
The exception among the top four highest energy usage months was Aug ‘13 for the East building. Unlike in the West building, the fans in the East building were rarely left on overnight.
74 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
100 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Chart 7.01 shows how often the AC and fans were used simultaneously.
Charts 7.02 are histograms of the outdoor temperatures during AC or fan usage.
Charts 7.03 show average profiles of PMV and supply air temperature for days of AC usage. With the two profiles overlapped, the average time period of greatest AC usage can be inferred. Also, the effectiveness of the AC system is expressed in the shape of the PMV profile.
Charts 7.04 - 7.06 show daily energy use totals by month for mechnical cooling, fans and louvers.
Key interpretations from this section are summarized on pages 102-103. Each interpretation is explained with findings used as evidence.
7.01 Outdoor Temperatures during AC/Fan Usage [W/E] 104
7.02 Average 24-Hour PMV & Supply Air Temperature Profiles [W/E] 106
7.03 Monthly Mechanical Cooling Energy Use Building Comparison 108
7.04 Monthly Fans Energy Use Building Comparison 109
7.05 Monthly Louvers Energy Use Building Comparison 110
7.06 Simultaneous AC & Fan Usage Building Comparison 111
102 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
Interpretations7
Before the 2013 summer break, the East building used 4x more AC than the West; after the break, both buildings consistently used AC at comparable levels
As seen in chart 7.03 , West building AC was only used sporadically in Apr ‘13 and May ‘13, while it was used four times as much in the East.
From May ‘13 to Aug ‘13, West building AC usage increased twentyfold.
From Aug ‘13 to Dec ‘13, AC usage was comparable in both buildings
The mechanical cooling energy use data for the West building in Nov ‘13 is most likely erroneous. Plug energy use was mislabeled and should really be counted as mechanical cooling energy use, as mentioned in ‘Notes’ on page 19.
West building AC usage stopped at 4:00 PM on average; East stopped at 3:00 PM on average
As seen in charts 7.02, both the average supply air temperature and PMV spiked upwards at around 4:00 PM in the West building.
The East building had upward spikes in average supply air temperature at both around 11:00 AM and 3:00 PM. However, it was only after the 3:00 PM spike that the supply air temperature returned to its nighttime baseline.
Buildings switched from AC cooling to fan cooling at different temperatures
As seen in charts 7.01, the buildings switched from fans to AC at different temperatures.
The West building used AC more often than fans at a threshold temperature of 77°F.
The East building used AC more often than fans at a threshold temperature of 79.5°F.
Louver usage in West building ceased after August 2013
As seen in chart 7.05, louver usage in the West building ceased after Aug ‘13, with the exception of small energy totals in Dec ‘13 and Feb ‘14.
In the East building, louver usage still continued after Aug ‘13, but at a lower rate when compared to before.
For both buildings, Apr ‘13 was the month with highest louver use.
Simultaneous AC and fan usage occured less than 2% of the time in both buildings
As seen in chart 7.06, simultaneous AC and fan usage occured 1.8% of the time in the West building and 1.6% of the time in the East building.
The West building used fans 31.9% of the time (52.8% of active time, 3.9% of holiday time).
The West building used AC 2.0% of the time (8.6% of active time, 1.3% of holiday time).
The East building used fans 12.4% of the time (35.2% of active time, 7.7% of holiday time).
The East building used AC 2.4% of the time (8.9% of active time, 0% of holiday time).
The West building used more energy for fans than the East building in every month*
*This is only looking at “complete” months without interruptions from vacations or the start/end of the study period (Apr ‘13, May ‘13, Aug ‘13, Sep ‘13, Oct ‘13, Nov ‘13, Feb ‘14)
As seen in chart 7.04, the West building used more energy for fans than the East building in every “complete” month.
In the highest energy usage months (Aug ‘13 and Sep ‘13), the West building used 45% and 77% more fan energy than the East building.
104 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
7.01 Outdoor Temperatures during AC/Fan Usage
Findings• The West building used fans 31.9% of the time (52.8% of active time, 3.9% of holiday time).• The West building used AC 2.0% of the time (8.6% of active time, 1.3% of holiday time).
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SYSTEM ANALYSIS 2: COOLING
Findings• The East building used fans 12.4% of the time (35.2% of active time, 7.7% of holiday time).• The East building used AC 2.4% of the time (8.9% of active time, 0% of holiday time).
106 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
W E
7.02 Average 24-Hour PMV & Supply Air Temperature Profiles
04/01/15 | CONTRACT NO.N00014-11-1-0391 107
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SYSTEM ANALYSIS 2: COOLING
108 TASK 4.2 FINAL REPORT - KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
7.03 Monthly Mechanical Cooling Energy Use Building Comparison
0
0.4 0.4
0 0
7.9
8.3
5.0
0.
4.1
1.7
2.4
0
1.61.9
0 0
8.2
7.4
3.6 3.7 3.6
0
0.7
West East
Dai
ly A
vera
ge
Ene
rgy
Usa
ge
[kW
h/d
ay]
0
1
2
3
4
5
6
7
8
9
Mar '13 Apr '13 May '13 Jun '13 Jul '13 Aug '13 Sep '13 Oct '13 Nov '13 Dec '13 Jan '14 Feb '14
04/01/15 | CONTRACT NO.N00014-11-1-0391 109
7.04 Monlthy Fans Energy Use Building Comparison
SYSTEM ANALYSIS 2: COOLING
Findings• In the highest energy usage months (Aug ‘13 and Sep ‘13), the West building used 45% and 77% more fan energy than the East
building.
0.1
2.0
3.1
0.5
1.1
6.4
6.9
2.62.3
4.9
0.8
1.6
0.2
1.9
2.6
0
1.9
4.4
3.9
2.5
1.3
1.0 0.90.7
West East
Dai
ly A
vera
ge
Ene
rgy
Usa
ge
[kW
h/d
ay]
0
1
2
3
4
5
6
7
8
9
Mar '13 Apr '13 May '13 Jun '13 Jul '13 Aug '13 Sep '13 Oct '13 Nov '13 Dec '13 Jan '14 Feb '14
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7.05 Monthly Louvers Energy Use Building Comparison
0.
0.1
0.
0.
0.
0.
0 0 00.
00.
0.
0.1
0.1
0
0.
0.
0. 0.
0.
0.
0.
0.
West East
Dai
ly A
vera
ge
Ene
rgy
Usa
ge
[kW
h/d
ay]
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.10
0.11
0.12
Mar '13 Apr '13 May '13 Jun '13 Jul '13 Aug '13 Sep '13 Oct '13 Nov '13 Dec '13 Jan '14 Feb '14
8.02 Monthly Interior Lighting Energy Use Building Comparison 118
8.03 Monthly Exterior Lighting Energy Use Building Comparison 119
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Interpretations8
The West building used more interior lighting than the East building
As seen in charts 8.01, the West has higher interior lighting energy use, which occurs mostly during school hours and at night from around 6-7 PM.
This is also reflected in chart 8.02. Nov ‘13 was the only month when the East building used more interior lighting than the West.
Nighttime exterior lighting accounted for a third of overall energy use
In the West building, interior lighting accounted for 8.4% of total energy use and 21% of total lighting energy use. A total of 289 kWh was used for interior lighting.
In the West building, exterior lighting accounted for 32% of total energy use and 79% of total lighting energy use. A total of 1087 kWh was used for exterior lighting.
In the East building, interior lighting accounted for 5.1% of total energy use and 13% of total lighting energy use. A total of 159 kWh was used for interior lighting.
In the East building, exterior lighting accounted for 35% of total energy use and 87% of total lighting energy use. A total of 1067 kWh was used for interior lighting.
Interior lighting energy use spiked during the winter
As seen in chart 8.02, for both buildings the four months with the highest interior lighting energy use were Nov ‘13, Dec ‘13, Jan ‘14 and Feb ‘14.
Between Apr ‘13 and Oct ‘13, the average daily interior lighting energy use was 0.5 kWh/day for the West building and 0.1 kWh/day for the East building.
Between Nov ‘13 and Feb ‘14, the average daily interior lighting energy use was 1.9 kWh/day for the West building and 1.1 kWh/day for the East building.
Exterior lighting energy use steadily increased over the course of the study period
As seen in chart 8.03, West building exterior lighting use either increased or stayed the same every consecutive month during the study period.
The West building daily average exterior lighting energy use was 37% higher in Feb ‘14 than in Mar ‘13.
East building exterior lighting energy use either increased or stayed the same every consecutive month starting from Jun ‘13 until the end of the study period (Feb ‘14).
The East building daily average exterior lighting energy use was 30% higher in Feb ‘14 than in Apr ‘13.
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W E
Average 24-Hour Interior & Exterior Lighting Load Profiles8.01
Findings• In the West building, interior lighting accounted for 8.4% of total energy use and 21% of total lighting energy use. A total of 289
kWh was used for interior lighting.• In the West building, exterior lighting accounted for 32% of total energy use and 79% of total lighting energy use. A total of 1087
kWh was used for exterior lighting.
04/01/15 | CONTRACT NO.N00014-11-1-0391 117
W E
SYSTEM ANALYSIS 3: LIGHTING
Findings• In the East building, interior lighting accounted for 5.1% of total energy use and 13% of total lighting energy use. A total of 159 kWh
was used for interior lighting.• In the East building, exterior lighting accounted for 35% of total energy use and 87% of total lighting energy use. A total of 1067
kWh was used for interior lighting.
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8.02 Monthly Interior Lighting Energy Use Building Comparison
Findings• Between Apr ‘13 and Oct ‘13, the average daily interior lighting energy use was 0.5 kWh/day for the West building and 0.1 kWh/day
for the East building.• Between Nov ‘13 and Feb ‘14, the average daily interior lighting energy use was 1.9 kWh/day for the West building and 1.1 kWh/day
for the East building.
0.
0.6
0.4
0.1 0.1
0.6
0.70.9
1.0
1.8
2.8
2.1
00.1
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0.20.1
1.5
0.70.8
1.5
West East
Dai
ly A
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rgy
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[kW
h/d
ay]
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Mar '13 Apr '13 May '13 Jun '13 Jul '13 Aug '13 Sep '13 Oct '13 Nov '13 Dec '13 Jan '14 Feb '14
04/01/15 | CONTRACT NO.N00014-11-1-0391 119
8.03 Monthly Exterior Lighting Energy Use Building Comparison
SYSTEM ANALYSIS 3: LIGHTING
2.7 2.7 2.7 2.7 2.72.8
3.13.2
3.43.5 3.5
3.7
1.7
3.0 2.9
2.72.8
3.23.3 3.3
3.53.5 3.6
3.8West East
Dai
ly A
vera
ge
Ene
rgy
Usa
ge
[kW
h/d
ay]
0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Mar '13 Apr '13 May '13 Jun '13 Jul '13 Aug '13 Sep '13 Oct '13 Nov '13 Dec '13 Jan '14 Feb '14
Findings• The West building daily average exterior lighting energy use was 37% higher in Feb ‘14 than in Mar ‘13.• The East building daily average exterior lighting energy use was 30% higher in Feb ‘14 than in Apr ‘13.
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Conclusion9
The findings for the Performance Category criteria, introducted in ‘Methodologies: Performance Categories’ on page 12, are summarized on pages 122 - 123. These findings address the following research questions:
• Model Comparison - Do platforms perform as predicted by models?• Standard Comparison - Do platforms perform better than established standards?
Interpretations, which are based on the findings from all sections, are presented on pages 124-127. Pages 124-125 have a table and summary of the seasonal trends in energy use for both buildings throughout the year. Pages 126-127 have a discussion addressing the broad project goal (as stated in the Task 1 Report) of minimizing energy demand from the various building systems as much as possible without adverse effects to occupant comfort and performance. The discussion begins by addressing the following research question:
• W-E Platform Comparison - Is performance consistent across platforms?
Recommendations for future studies are summarized on pages 128-129.
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Findings9
19% 21% 8% 31% 20%
22% 15%5% 35% 22%
656 kWh
686 kWh
714 kWh
472 kWh
289 kWh
159 kWh
1087 kWh
1067 kWh
706 kWh
691 kWh
A HO
A H,O
A,O H
H,A,O
AO3452 kWh
3074 kWh
Performance Category 1: Energy
The total energy use for both buildings was below both the anticipated and optimal estimates. The West building used 13% more total energy than the East. In terms of the percentage breakdown by energy usage group, the biggest discrepency between the buildings was in fan usage, which accounted for 21% of the West total and 15% of the East total.
None of the individual energy usage groups in either building had an energy use total exceeding the high estimate. The East building used more energy on mechanical cooling, despite using less energy overall. The West building used 51% more energy on fans and 82% more energy on interior lighting. The difference in plug load was 2%.Energy
The West building had PMV values outside the Comfort Zone 75% of the time
The East building had PMV values outside the Comfort Zone 55% of the time.
In both buildings, carbon dioxide concentrations never exceeded benchmarks for inadequate ventilation (ASHRAE) or minor cognitive impairment (Satish et al., 2012).
In the West building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 8% of the time.
In the East building, ΔT ≥ 10°F between the plenum inlet and floor diffusers 64% of the time.
In the West building, during active days between 6:00 AM and 6:30 PM, the lights were on for 21% of the time. For 9% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
In the East building, during active days between 6:00 AM and 6:30 PM, the lights were on for 6% of the time. For 2% of the time, the lights were off but the lighting criteria wasn’t met (wall illuminance > 5 ft-cd and illuminance ratio < 5).
Performance Category 2: Interior Environment
Performance Category 3: Daylighting
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9 Interpretations
Top 3 Energy Usage Groups by MonthMar ‘13 Apr ‘13 May ‘13 Jun ‘13 Jul ‘13 Aug ‘13 Sep ‘13 Oct ‘13 Nov ‘13 Dec ‘13 Jan ‘14 Feb ‘14 TOTAL
Wes
t 1 Ext. L. Ext. L. Fans Ext. L. Ext. L. Mech. Mech. Mech. Fans Ext. L. Ext. L. Ext. L.
2 Plugs Plugs Ext. L. Plugs Plugs Fans Fans Ext. L. Mech. Int. L. Mech. Fans
3 Fans Fans Plugs Fans Fans Ext. L. Ext. L. Fans Ext. L. Plugs Int. L. Plugs
Eas
t 1 Ext. L. Ext. L. Plugs Ext. L. Ext. L. Mech. Mech. Mech. Mech. Mech. Ext. L. Ext. L. Ext. L.
2 Plugs Plugs Ext. L. Plugs Plugs Fans Fans Ext. L. Ext. L. Ext. L. Plugs Plugs Plugs
3 Fans Fans Fans Fans Ext. L. Ext. L. Fans Plugs Plugs Fans Int. L. Mech.
The November 2013 data is excluded due to a likely sensor error, as mentioned in ‘Notes’ on page 19. At the bottom of the table, there are monthly average temperatures recorded from the rooftop weather station. Other measured weather station data can be seen in Section B of the Appendix.
The following interpretations are broken up by time of year, based on both the school calendar and the seasons of Līhu’e, Kauai.
Charts 6.01, on pages 74-75, show the daily average energy use values in [kWh/day] for each month.
Consistent Year-round Load Patterns Consistent overnight load pattern throughout year (Findings 8.01, 3.01)
Consistent energy use throughout day/night all year (Interpretations 6, Charts 6.01-6.13)
2012-2013 School Year, Spring (Mar - May ‘13)
Fans used more often than AC during these months (Interpretations 7, Charts 7.03-7.04 & 6.02-6.04)
Summer Break (Jun - Jul ‘13)
Minimal daytime use. Majority of energy use from consistent year-round loads: exterior lighting and plugs (Charts 6.05-6.06)
2013-2014 School Year, Summer (Aug - Sep ‘13)
AC used the most energy during these two months, which were also the warmest and also the months with highest total energy use (Charts 6.07-6.08)
Fan usage was also the highest during these two months for both buildings (Charts 7.03-7.04 & 6.07-6.08)
2013-2014 School Year, Fall (Oct - Dec ‘13)
Despite the fact that the average temperatures during these months were close to those of the previous Spring, the AC usage was much higher during these months (Charts 7.03 & 6.09-6.11)
2013-2014 School Year, Winter (Jan - Feb ‘14)
These were the first months when interior lighting use was among the top 3 energy use groups (Charts 6.12-6.13)
Fans
Ext. L.
Int. L.
Mech.
Plugs
Fans
Mech.
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Interpretations9West/East Platform Comparison: Is performance consistent across platforms?Despite the identical construction of the two Hale Akamai buildings, this study has shown that their energy demand patterns differed. The contrasts in these patterns give clues as to how the buildings were utilized differently, and how those occupant decisions ultimately affected the buildings’ energy use totals.
The most obvious example is the difference in overall energy use between the two school years. As seen in charts 6.01, In April ‘13 and May ‘13 the East building used more energy than the West. But then for every month beginning in Aug ‘13 until the end of the study period (February ‘14), the West building used more energy than the East. This was mainly caused by a shift in AC usage patterns in the West building. Before the summer, the West building rarely used AC; roughly a quarter as much was used by the East building. However, the increase in West building AC use before and after summer (comparing May ‘13 to August ‘13) was twentyfold. Then West building AC usage continued at the higher level for the remainder of the study period.
Along with AC use, fan use was the other main cause for the highest energy months in summer. The West building also used more energy for fans than the East building. In the highest energy usage months (August ‘13 and September ‘13), the percent differences were as high as 45% and 77%. This was despite the fact that the AC use was similar for both buildings.
Lighting usage also generally increased over the course of the study period. Between April ‘13 and October ‘13, the average daily interior lighting energy use was 0.5 kWh/day for the West building and 0.1 kWh/day for the East. Then between November ‘13 and February ‘14, the average daily interior lighting energy use was 1.9 kWh/day for the West building and 1.1 kWh/day for the East building. The East building interior lighting began to be used consistently during school hours starting in November ‘13. Even the exterior lighting, which had a constant daily profile throughout the enitre study period, increased steadily. The West building daily average exterior lighting energy use was 37% higher in February ‘14 than in March ‘13. The East building daily average exterior lighting energy use was 30% higher in February ‘14 than in April ‘13.
One possible explaination for the increased energy usage across all systems is that the building occupants gradually stopped taking advantage of the energy efficient features of the building. The case of louver usage strongly suggests this. For both buildings, April ‘13, which was the first full month of occupancy, was the month with highest louver use, as seen in chart 7.05. But then louver use in the West building ceased after Aug ‘13, with the exception of small energy totals in Dec ‘13 and Feb ‘14. Louver use in the East building continued, but at a small rate. This drop in louver use didn’t coincide with a drop in AC or fan use, so the buildings were still in need of cooling.
What are the possibilities for reducing energy demand?Based on the discussion from the previous page, it is difficult to predict whether building occupants will fully take advantage of all the energy reducing features of a building. Therefore, when looking for possibilities for energy demand reduction, it’s easier to go after predictable, repetitive patterns of energy demand which don’t rely on occupant decisions. An example in this case would be nighttime exterior lighting.
Nighttime exterior lighting accounted for roughly a third of overall energy use for both buildings. As seen in charts 3.03 - 3.05, the exterior lighting load profile stayed the same for all days, including weekends and holidays.
There were also several months when fans in the West building were left on overnight. The three months with the highest overnight fan energy use (August ‘13, September ‘13 and December ’13), were also the three highest energy use months for the West building. This can be seen in charts 6.07, 6.08 and 6.11.
Finally, the plug load was consistent throughout the night and day throughout the entire study period. However, without knowing the details of what is being plugged in, it is difficult to find strategies for reducing demand.
In terms of looking for ways to reduce demand during school hours, one approach is to look back at months or periods of time when energy demand was comparative low. For example, February ‘14 had the lowest energy use among “complete” months for the East building. However, for the West building more energy was used in February ‘14 than in April ‘13 or May ‘13. The load profiles in Charts 6.13 show that the discrepancy in energy use between buildings occured in the afternoon. In the West building, AC and fan use increased in the afternoon while interior lighting use continued from the morning. Meanwhile in the East building, AC, fan and interior lighting use ceased between 3:00 PM and 5:00 PM. Although more information about class schdules and building use is needed to make specific recommendations, this approach gives clues as to where or when to look for proven strategies.
There are other examples of energy demand reduction possibilies suggested by the data. From August to October 2013, there were lunchtime dips in AC use in the East building, but not in the West building. This can be seen in charts 6.07 - 6.09. Next, the air supply temperature profiles reveal that AC use stopped at 4:00 PM on average in the West building but at 3:00 PM on average in the East building. This can be seen in charts 7.02.
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Recommendations9
RECOMMENDATION 2Investigate use of Fans / AC / Louvers interaction to determine operating states and auto/manual triggering
DESCRIPTION OF ISSUE/OPPORTUNITYBoth Frogs appear to be using more than the Optimal model AC energy and less than the Optimal model Fan energy. Both platforms were designed to use fans and louvers up and until a specified setpoint at which the louvers closes and the AC system turns on. The current study attempted to use the Louvers energy use as an indicator of use, but the power demand was so small that system activation did not necessarily align with system use -- and it did not indicate status of the louver as open or closed. This hampered efforts to understand how louvers and fan use correspondended to AC use.
STRATEGIES & TACTICS1 - Observe louvers / fan / AC states through manual data collection
Direct a building administrator to evaluate system ‘states’ five times a day for 2 weeks - 1month to confirm system actions and interactions
2 - Add state sensors to louvers to determine when are in closed/open positionInstall state sensors to each louvers in independent combination and connect sensor to building CPU and/or collect manually at intervals
RECOMMENDATION 1Investigate Air Supply Distribution differences between W & E Frog
DESCRIPTION OF ISSUE/OPPORTUNITYThe W Frog showed greater than 10% increases in distribution temperature more than 50% of the time, particularly during later months in the study. This may represent a problem in system operations and should be investigated to ensure optimal performance of cool air distribution.
STRATEGIES & TACTICS1 - Conduct site visit to test distribution temperatures at various locations to determine the cause of the temperature rise
Turn system on and manually measure supply temperature and output temperature. Walk length of distribution and visually identify disturbances to plenum that may be causing changes in temperature.
2 - Add additional sensors to determine location and triggers of issues over timeInstall additional air temperature sensors at every 10’ to isolate problem zones
RECOMMENDATION 3Adjust Thermal Comfort (TC) model assumptions and verify
DESCRIPTION OF ISSUE/OPPORTUNITYThe thermal comfort model assumptions used in this report were based on the best understanding of user occupant behavior.
However, using these assumptions led to thermal comfort models that showed user occupants turning AC on when the conditions were already below the comfort guidelines in the platform. These findings do not make sense and need to be investigated.
STRATEGIES & TACTICS1 - Adjust thermal comfort model assumptions to fit curvature to inferred user comfort response behavior based on use of AC.
Clothing insulation - 0.50 (Knee-length skirt, short-sleeved shirt, sandals)Metabolic rate: 95W/m2 (standing, light activity)See Appendix for how these assumptions were determined and exhibit 9.02)
2 - Confirm user TC satisfaction through additional methodsSend out user surveys five times a day for 2 weeks - 1 month to confirm comfort / discomfort at various times of day and across weather conditions
RECOMMENDATION 4Investigate user behavior of platforms related to occupancy and building system manipulation
DESCRIPTION OF ISSUE/OPPORTUNITY4 of 9 performance measures showed greater than 20% variation between the E & W Frog platforms. Since the platforms share the same orientation, microclimate, and facility attributes, it is inferred that a portion of the variation is attributable to user behavior. Currently user behavior is completely inferred through building system usage patterns as measured through energy use over time. However, these measurements don’t distinguish between manual and automatic system responses and they can mislead perceptions of active hours when systems are inadvertently left on over time. A better understanding of user behavior will help confirm what variation is attributable to building design / system ops versus user behavior.
STRATEGIES & TACTICS1 - Collect building scheduling information and attendance records
Select an administrator to provide building scheduling and attendance information at each cycle period during the school year
2 - Collect automatic system setpoints and control logicSend out user surveys five times a day for 2 weeks - 1 month to confirm comfort / discomfort at various times of day and across weather conditions
3 - Install occupancy/utilization sensors to determine building active hours Install infrared occupancy sensors at building entrance/exits and connect to building CPU for data aggregation and communication
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Acknowledgments
The present work benefited from the input of Dr. Sara Cerri, ONRG grantee (ONRG grant N62909-13-1-N233, Task 2.a)from Cureggio, Italy, who provided additional data analysis, specifically related to the monthly load profiles.
TASK 4.2 FINAL REPORT APPENDIXKAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
PREPARED BY:
MKThinkMark R. Miller, AIA LEEDAP
CEO, Director of Innovation Services
PREPARED UNDER CONTRACT TO:
Office of Naval ResearchDr. Richard CarlinDepartment Head, Code 33
PREPARED FOR:
Hawaii Natural Energy InstituteUniversity of Hawaii at ManoaDr. Rick RocheleauDirector
TASK 4.2 FINAL REPORT APPENDIX- KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
04/01/15 | CONTRACT NO.N00014-11-1-0391 TABLE OF CONTENTS 3
Table of Contents
A Solar Radiation 4
B Weather Summary 8
C Performance Category Extremes 26
D Weather Extremes 46
E A-E Relationships 72
4 TASK 4.2 FINAL REPORT APPENDIX- KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
The annual actual horizontal solar radiation incident on the test platform roof and compare to annual solar radiation measured at Lihue Airport for a previous 5 year period.
A pyranometer was installed on a weather station at Kawaikini to measure onsite solar radiation and insolation. The data was collected at 5-minute intervals.
No calculations were performed on the solar irradiance (W/m2) data. To calculate solar insolation (Wh/m2) each irradiance data point was multiplied by (5/60) since it was assumed that each data point was constant for the preceding 5 minute period. These values were then summed cumulatively to yield a running solar energy total in Watt-hours per square meter.
The sensor has a maximum around 1277 W/m2, which was confirmed by the manufacturer.
Measured cumulative solar insolation was potentially less than modeled due to sensor maximum value threshold.
Findings• Q2 had the highest available solar radiation, followed by (in decreasing order): Q1, Q4, Q3* Solar radiation sensor maximum detection limit of 1277 W/m2 (confirmed by manufacturer)
1277 761.456 786.739 609.381 639.287
0.6 1 0.641 0.842 1
201.317 209.033 227.177 149.969 162.513
310.932 257.225 282.769 207.492 224.089
CLIENT HNEISHEET #
PROJECT 01 HNEI Part One- Kawaikini NCPCS
CHART Kawaikini Q4 Observed Solar IrradianceDATE - UPDATE 07/10/2014
PREPARED BY admin
DIMENSIONS 1d 2d 3d T V SCALE
DATA INPUTS
Observed Q1 Average Q2 Average Q3 Average Q4 AverageITEM
ATTRIBUTESensor (1/128) - Solar Radiation
(W/m^2)
Sensor (1/128) - Solar Radiation
(W/m^2)
Sensor (1/128) - Solar Radiation
(W/m^2)
Sensor (1/128) - Solar Radiation
(W/m^2)
Sensor (1/128) - Solar Radiation
(W/m^2)
MEAS. DEVICEKawaikini - Weather Station - Solar
Rad
Kawaikini - Weather Station - Solar
Rad
Kawaikini - Weather Station - Solar
Rad
Kawaikini - Weather Station - Solar
Rad
Kawaikini - Weather Station - Solar
Rad
SENSOR TYPE
SENSOR REF
TEST LOCATION
TEST INTERVAL
TEST DURATION - - - - -
Irrad
ianc
e
Observed
Q1 Average
Q2 Average
Q3 Average
Q4 Average
00:0
006
:00
12:0
018
:00
00:0
003
:00
09:0
015
:00
21:0
0-‐‑250
0
250
500
750
1000
1250
1500
DATA OUTPUTS
STAT Observed Q1 Average Q2 Average Q3 Average Q4 AverageMAX
8 TASK 4.2 FINAL REPORT APPENDIX- KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
This section includes an analysis of environmental conditions to identify dominant microclimate typologies, annual averages, monthly averages, and environmental extremes.
26 TASK 4.2 FINAL REPORT APPENDIX- KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
This section looks at days where performance cateogries were within 5% of their annual maximum or minimum (extreme performance days). Then the percentage differences in weather attributes (compared to the annual average) on those days were examined to understand the magnitude of their potential contribution to the measured performance. category.
Charts on the left side are for the West Frog, and charts on the right side are for the East Frog.
Air Temperature Relative Humidity Solar Radiation Wind Speed Wind Direction
46 TASK 4.2 FINAL REPORT APPENDIX- KAWAIKINI NEW CENTURY PUBLIC CHARTER SCHOOL
This section looks at days where weather metrics were within 5% of their annual maximum or minimum (extreme weather days). The extreme weather days were compared against annual averages. Then the building performance categories on those days were examined to understand how the buildings were impacted on days of extreme weather events.
The active days charts show the percentage difference in performance attributes on extreme weather days as compared to the annual average.
Active days charts on the left side are for the West building, and active days charts on the right side are for the East building.
AC Power Fan Power Light Power CO2 Supply Air Illuminance PMV
Kawaikini East Frog Performance Statistics for 5% Least Windy Active Days
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A-E Relationships
This section looks at the correlation strength between building performance (assets, A) and changes in weather (environmental conditions, E). These A-E relationships indicate what metrics affect each other in context of the building performance. In addition, the clustering of data points reveals how building performance responds to the full variation of weather conditions, particularly where building systems limit performance along operational thresholds (e.g. power ratings).
The data points are daily averages.
Coefficient of determination (r2) values above 0.10 are listed in the findings. Correlations calculated but below 0.10 are not noted in the findings.