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DNV GL © 2015-05-12 SAFER, SMARTER, GREENER1 DNV GL © 2015-05-12 HVAC-4 Webinar at CPUC
2015-05-12
ENERGY
HVAC-4 Deemed Measures Study, Year 1
Public Webinar
for California Public Utilities Commission
DNV GL © 2015-05-122
Presentation Outline
Study Objectives
Measure selection
Literature review
Description of Crystal Ball® analysis tool
By Measure
– Background Information
– Results
– Recommendations
Year 2 study plans
DNV GL © 2015-05-123
Study Objectives
Select 3 deemed measures to study
Perform literature review for each
Perform Monte Carlo simulations of ex ante savings using Crystal Ball®
Identify input parameters in need of updates or information gaps
Inform other HVAC Roadmap data collection efforts
Suggest study plans for Year 2
DNV GL © 2015-05-124
Measure Selection: HVAC Roadmap Savings
Top 5 Natural Gas Saving Measures
Top 5 Annual Electric Saving Measures
Rank Measure GroupPreliminary Ex Ante
Savings, therms
1 HVAC Furnace 2,830,079
2 HVAC Duct Sealing 1,578,223
3 HVAC Boiler 1,427,112
4 HVAC Controls: Energy Management Systems (EMS) 875,857
5 HVAC Controls: Thermostat 470,346
Rank Measure GroupPreliminary Ex Ante
Savings, kWh
1 HVAC Rooftop or Split System 37,981,291
2 HVAC Motor Replacement 28,987,677
3 HVAC Chiller, Water-cooled 22,339,413
4 HVAC Chiller, Air-cooled 21,756,495
5 HVAC Fan Variable Frequency Drive (VFD) 17,612,888
DNV GL © 2015-05-125
Measure Selection: HVAC Roadmap Measure Trends
Quarterly Natural Gas
Savings Claims
Quarterly Electric
Savings Claims
DNV GL © 2015-05-126
Measure Selection: Selection Criteria
Selection Criteria
Residential Furnaces
Residential QM & Blower Motor Replacements
Mini-Splits and VRF Systems
Electric Gas Electric Gas Electric Gas
High savers in HVAC Roadmap?False(but
growing)True False False True False
Growing participation? True(particularly with VSMs)
True True
Not currently being evaluated? True True False(during HVAC-1 pilot)
ESPI measure? False True True
DNV GL © 2015-05-127
Literature Review Process
Review IOU workpapers
Review secondary sources
Identify information gaps
Identify opportunities for improvements
DNV GL © 2015-05-128
Description of Crystal Ball Analyses: General
Crystal Ball is an add-in for Microsoft Excel®
Monte Carlo simulation was named for Monte Carlo, Monaco
When rolling a single die, the roller knows that a 1, 2, 3, 4, 5, or 6 will result, but
cannot know the outcome for any given roll.
To set up Monte Carlo simulations, define the conditions of the input variable—in
this case, an integer between 1 and 6, incl.
DNV GL © 2015-05-129
Description of Crystal Ball Analyses: Simulating a Single Die Roll
DNV GL © 2015-05-1210
Description of Crystal Ball Analyses: For Ex Post/Ex Ante Comparison
Snapshot of deemed savings from sample workpaper:
Snapshot of gross savings reporting table from CA Evaluation Framework1:
1 “The California Evaluation Framework,” TecMarket Works Framework Team for Southern California Edison Company, June 2004. (p. 380)
DNV GL © 2015-05-1211
Residential Furnaces: Background (PG&E)
For central, natural gas furnaces1 with ≥ 95 AFUE and < 97 AFUE
– w/variable-speed fan motors (and w/o)
Annual natural gas deemed savings based on 2011 DEER2 database
Electric deemed savings assume baseline equipment = constant volume fan
1 “High Efficiency Furnace 95 AFUE (1.04 HIR)—Residential,” Pacific Gas & Electric Company, 8/28/2012.
2 “Database for Energy Efficient Resources,” at http://www.deeresources.com/
DNV GL © 2015-05-1212
Residential Furnaces: Retrofit Prototypes Used in DEER
eQUEST prototype models:
Multifamily Building Prototype
Mobile Home Prototype
Single Family Home Prototype
DNV GL © 2015-05-1213
Residential Furnaces: Input Parameters VSMs
DNV GL © 2015-05-1214
Residential Furnace VSMs: Simulation Results
Monte Carlo simulation results:
Deemed Savings per PG&E workpaper:
Statistical Descriptors
Annual Electric Savings, kWh
CZ11 CZ12 CZ13
PG&E Workpaper 315 224 297
Simulated Mean 320 225 297
Standard Deviation 141 107 134
Coefficient of Variation 0.44 0.48 0.45
Minimum 131 85 149
Maximum 705 547 675
Mean Standard Error 1.41 1.07 1.34
DNV GL © 2015-05-1215
Residential Furnace VSMs: Simulation Results
Annual Electric Savings Distribution by Dwelling Type in CZ11
DNV GL © 2015-05-1216
Residential Furnace VSM: Monte Carlo Simulation Results
Savings Variance Contributions for Single Family Homes in CZ11
In most cases, building vintage accounted for the majority of the variance
Thermostat usage bin weights are the next highest contributor to the variance.
Savings at SFM buildings vary significantly by the number of stories.
DNV GL © 2015-05-1217
Residential Furnace & VSM: Recommendations
Assess average blower motor power during non-cooling modes for the baseline and post-retrofit case
Update building vintages represented in the participant population
Update thermostat usage bins and associated weights
DNV GL © 2015-05-1218
Residential Quality Maintenance & Blower Motor Retrofits: Background
Residential Quality Maintenance Measure Components by IOU
DNV GL © 2015-05-1219
Residential Quality Maintenance & Blower Motor Retrofits: Background
Residential Quality Maintenance Measure Components by IOU
DNV GL © 2015-05-1220
Residential Quality Maintenance: Workpaper
Source: PG&E Workpaper
DNV GL © 2015-05-1221
Residential Quality Maintenance: Background
Annual Electric Energy per Ton, Baseline and Post-Measure, in CZ03*
* Excludes blower motor replacement
DNV GL © 2015-05-1222
Residential Quality Maintenance: Comparison to Deemed Savings
Simulated Savings and Ex Ante Annual Electric Energy Savings, per Ton
• The annual electric energy estimates are within 25% of the ex ante savings in all climate zones except CZ12
• For peak demand, the simulated savings and ex ante savings in all climate zones except for Climate Zone 1 are within 25%.
• For natural gas energy, however, the ex ante savings are significantly higher than the simulated savings.
DNV GL © 2015-05-1223
Residential Quality Maintenance: Sensitivity Results
Sensitivities of Baseline Annual kWh, kW and therms consumptions
DNV GL © 2015-05-1224
Residential Quality Maintenance: Recommendations
Update thermostat offset values and weights based on the 2009 RASS
Verify distributions of duct UAs and furnace AFUEs
Verify building shell Uas
For those ex ante savings that differ significantly from the simulation results, hold a working session with the PG&E workpaper authors to identify the source of the discrepancies
DNV GL © 2015-05-1225
Mini-Split and Variable Refrigerant Flow Systems: Background
Mini- and multi-split units:
– Ductless split systems <65 kBtuh of cooling capacity
– Minimum seasonal energy efficiency ratio (SEER) rating of 16-22
Variable Refrigerant Flow (VRF) systems with inverter-driven compressors to vary refrigerant flow during part-load conditions:
– In systems of single- or multi-zone configurations
Fan coil units with electronically commutated motors (ECM) to vary the fan speed during part-load conditions
Heat recovery configurations that capture inverter waste heat removed from zones being cooled and diverting the captured heat to zones being heated
DNV GL © 2015-05-1226
Mini-Split Systems Background: SCE Methodology
At systems installed at commercial applications:
– Savings are scaled based on DEER savings for a 14 SEER package system at a single family home prototype
– Additional savings are included based on duct sealing savings to account for the ducted to ductless conversion
DNV GL © 2015-05-1227
Mini-Split Review
With savings based on DEER values and secondary sources Monte Carlo Analysis cannot be conducted
There is insufficient data available for savings associated with these measures. Basing savings on single family home DEER prototype may yield a rough estimate of savings, but is not necessarily representative of commercial applications. The question is how valid is this relationship:
– No secondary sources were provided in the workpaper to support the validity of this relationship.
– Each DEER Savings value has error associated with it, this will propagate through the calculation
DNV GL © 2015-05-1228
Mini-Split Review
Three studies are referenced for duct sealing savings with savings ranging from 10% to 18%.
– These savings values are from conditioned air leaking to unconditioned spaces The conversion from ducted to ductless systems will only result in fan savings
– SEER ratings already account for ductless systems operating with lower static pressure
DNV GL © 2015-05-1229
Mini-Split Recommendations
– Further study regarding whether the increased energy savings that go hand-in-hand with an improved SEER rating scale up at the same rate when installed at commercial applications as at residential ones
– Further investigation regarding the energy savings from the elimination of ductwork are already accounted for by the higher SEER ratings of ductless mini- and multi-split heat pumps
DNV GL © 2015-05-1230
VRF Workpaper Methodology
2011 DEER does not provide savings for VRF measures
2 cases are considered: 1) commercial VRF units or systems with heat recovery and 2) commercial VRF units or systems without heat recovery.
Savings are determined by running EnergyPro® v5.1 building simulations
Two assumptions are made:
– The equipment was manufactured by either Daikin or Mitsubishi, the two largest manufacturers of VRF equipment.
– Half of the zones in the building models were served by ducted systems and the other half by ductless units. This assumption was based on the sales proportions provided during interviews with Daikin and Mitsubishi representatives.
DNV GL © 2015-05-1231
VRF Review Recommendations
Gather ex post evaluation data to verify VRF deemed savings
Use EnergyPro® v5.1—with adjustable performance curves—instead of fixed SEER ratings
Through HVAC-1 evaluation, consider gathering:
– Proportions of ducted and ductless zones in commercial spaces
– Cooling capacities of these zones
– Typical lengths of duct runs in ducted zones
Field or Lab tests could greatly improve these measures to:
– Gather data regarding the full range of commercial building types, occupancy types, and associated load profiles. Alternatively, since the tracking data do not contain consistent building type fields, improving the tracking of participant building types would greatly facilitate the identification of building simulation models
DNV GL © 2015-05-1232
Year 2 Plans
Based on Year 1 findings:
Review 2014 tracking data for any new trends to inform future efforts
Further investigate measures that have been examined in Year 1
Gather underlying data used for the DEER parametric runs to facilitate running Monte Carlo simulations on parameters that feed into models
DNV GL © 2015-05-1233
SAFER, SMARTER, GREENER
www.dnvgl.com
Posting Comments http://www.energydataweb.com/cpuc/search.aspx; select “2013-2014” program cycle and search “HVAC”. Public comment may be posted to the Public Document Area through Friday May 15, 2015.
Rachel [email protected]