Residential UES: Smart Plug Power Strips Josh Rushton Regional Technical Forum Aug 18, 2015

Objectives Seeking RTF decision on updates to Residential Smart Plug Power Strips UES measure. Review Research Strategy Approve as Planning measure with extended sunset date 2

Measure Background August, 2013: RTF approved the measure (Planning category) with a detailed Research PlanResearch Plan August, 2015: ETO has some research in the pipeline – Applies to IR-sensing APS in home entertainment settings – Results expected Q1, 2016 – Staff believes the ETO work justifies Provisional category for IR-sensing APS in workstations Need to document RTF Research Plan; – Mostly point to ETO contractor’s planning memo – Clarify things like adjustments related to delivery channel and persistence Staff plans to move forward with this process immediately – SDG&E “Phase II” pre/post study (IR-sensing home entertainment) may be also be helpful when completed. Today’s main intent is to align the measure with RTF’s current usage of Planning versus Provisional categories – Minor modifications to measure itself – Retain Planning category – Replace existing Research Plan with new Research Strategy. 3

Measure Overview Sector:Residential Measure name:Advanced Power Strips Applications: Home entertainment (AV), load-sensing Home entertainment (AV), IR-sensing Home office, load-sensing Home office, motion-sensing Home office, PC interaction-sensing Eligibility: Must have at least one controlled device Delivery channel:Retail, direct-install, or mail-by-request only CurrentProposed Category:PlanningPlanning Status:ActiveActive Baseline:Pre-conditionsPre-conditions Sunset Date: 08/31/201508/31/2018 Annual Savings:VariesVaries Measure life: 5 years5 years B/C Ratio: VariesVaries 4 Often called Tier II

Measure applications Research Strategy does not use “Tier I/Tier II” terminology – Performance expected to be specific to APS technology and usage setting Measure divided into five distinct applications: – Home entertainment (AV), load-sensing – Home entertainment (AV), IR-sensing – Home office, load-sensing – Home office, motion-sensing – Home office, PC interaction-sensing Research Strategy describes objectives and research methods specific to each application – Research questions look alike for most applications – Answers likely to be highly context-dependent Don’t necessarily expect all five applications to make it to proven 5

Load-sensing APS, Home entertainment How it works – APS configured so that peripheral devices are powered down when the TV is turned off – Typical controlled devices include DVD player and other AV equipment; – Controlled equipment should not include set-top box, cable modem, DVR, some game consoles, or AV equipment used separately from TV Research questions – Primary: How much energy does it typically save? – Secondary: What are the typical controlled devices? Do controlled devices change over time? Are some controlled devices associated with poor persistence? 6

IR-sensing APS, Home entertainment How it works – IR sensor monitors remote-control signals; – After 1-2 hour period of inactivity, APS powers down controlled devices (user is given chance to over-ride) – Typical controlled devices include TV, DVD player, and IR- controlled AV equipment; – Controlled equipment should not include set-top box, cable modem, DVR, some game consoles Research questions – Primary: How much energy does it typically save? – Secondary: What are the typical controlled devices? Do controlled devices change over time? Are some controlled devices (including TV) associated with poor persistence? 7

Load-sensing APS, Home office How it works – Load-sensing APS configured so peripheral devices are powered down when the PC is shut down or put to sleep – Typical controlled devices include external monitors, speakers, desk lamps, and some printers; – Controlled devices typically should not include home- network printers, modem/routers, phone, external hard drives Research questions – Primary: How much energy does it typically save? – Secondary: What are the typical controlled devices? Do controlled devices change over time? Are some controlled devices associated with poor persistence? 8

Motion-sensing APS, Home office How it works – Motion-sensing APS configured so peripheral devices are powered down when no movement is detected by the sensor for a period of time – Typical controlled devices include external monitors, speakers, desk lamps, and some printers; – Controlled devices typically should not include home-network printers, modem/routers, phone, external hard drives Research questions – Primary: How much energy does it typically save? – Secondary: What are the typical controlled devices? Do controlled devices change over time? Are some controlled devices associated with poor persistence? – Secondary: Are sensor-placement instructions needed to ensure savings or persistence? 9

PC interaction-sensing APS, Home office How it works – User-downloaded PC application monitors user interactions via the keyboard and mouse; when no activity is detected for a period of time, the application initiates shut-down routine (user is given a chance to over-ride). – Typical controlled devices include the PC, monitor(s), speakers, desk lamps, and some printers; – Controlled equipment typically should not include home-network printers, modem/routers, telephone, external hard drives Research questions – Primary: How much energy does it typically save? Must account for efficiency achieved by baseline PC energy saver settings. – Secondary: What are the typical controlled devices? Are some controlled devices (including the PC) associated with poor persistence? Only one retail product currently available for this application 10

Research Strategy: Data Collection MeasureMinimum Sample SizePre/Post IR-Sensing, Home Entertainment60Yes Load-Sensing, Home Entertainment60Yes Load-Sensing, Home Office60Yes Motion-Sensing, Home Office60Yes PC Interaction-Sensing, Home Office60Yes Pre and post metering (3 weeks min each), cumulative kWh of controlled devices – For IR-Sensing, Home Entertainment: APS control algorithms vary, so research should test whether savings vary significantly across different models – Manufacturer of PC-interaction-sensing APS: Devices can be programmed to collect pre/post kWh and submit to evaluator via internet for low-cost evaluation. – Metering periods should be staggered to avoid seasonal effects. – Study design should try to ensure same equipment metered pre/post. Site audits to inform – Typical configurations of controlled equipment – First-year removal rates (via follow-up phone call?) Research plan should be appropriate for expected program delivery methods. 11

Research Strategy: Data Analysis 12 Annual savings based difference between average daily kWh in the pre- period minus average daily kWh in the post-period. Researchers should check for important savings determinants – Is energy savings correlated with connected device types? – IR-sensing (A/V): Is savings correlated with TV energy-saver functionality? – PC-interaction-sensing: Is savings correlated with baseline PC energy- saver settings. – Results may help inform program design and UES maintenance. Adjustments may be needed to account for differences between study conditions (e.g., participants and delivery channels) and expected programs conditions. – Final research plan should describe expected adjustments Estimated Cost Range (all five applications): ( $2million)

Other Research Paths 13 The RTF’s judgment is that the following methods are not likely to provide sufficient rigor for Proven UES estimates: Bottom-up savings Post-only or pre-only metering with simulated counterfactual The RTF does not have a strong opinion as to whether this method can provide sufficient rigor for Proven UES estimates Wide study with AMI interval data

UES Planning values 14 APS typeApplication settingDelivery channelKWh savings (current) KWh Savings*, ** (proposed) Load-Sensing Home EntertainmentDirect install40 Home OfficeDirect install20 UnknownMail-by-request/retail30 Motion- Sensing Home OfficeDirect install70 Home Offic -by-request/retail70 IR-Sensing Home EntertainmentDirect install Home EntertainmentMail-by-request/retail PC-SensingHome OfficeUnknownN/A238 * RTF Planning estimates are not reliable. ** Savings figures refer to properly-installed APS units and do not include adjustments for improper installation or subsequent removal.

Origin of Planning UES values 15 IR-sensing, home entertainment. – Value is weighted average of two estimates from study prepared for SDG&E (AESC, 2014) – Savings of 234 kWh, based on CalPlug methodology applied to 42 sites – Savings of 134 kWh, based on pre/post data collected for 9 sites – Simple weighted average is (42* *134)/51 = 216 PC-interaction-sensing, home office – Value based on percent savings rate applied to RBSA-based estimate of relevant workstation energy – RBSA Metering Study Report (Ecotope, 2014) estimates average annual energy consumption by end use. – "CPU" (331 kWh), "Computer accessory" (145 kWh), “Monitor" (145 kWh) – Many accessories (modem, external hard drive) should not be APS controlled, so we count only Monitor and CPU in base energy ( = 476 kWh) – (ECW, 2012) suggests 50% potential savings for Energy Saver settings (476*0.50 = 238 kWh)

Reminder 16 Unlike Proven UES values, RTF Planning values are not subject to stringent reliability requirements. For Proven UES measures, evaluated savings is based on published UES values and measure counts obtained through Delivery Verification. For Planning UES measures, programs are expected to evaluate all aspects of measure savings. Evaluations should account for: – Installation rate. Units that are not installed, or not installed correctly, may save little or no energy (especially relevant to mail-by-request and retail delivery channels) – Removal rate. Customers who are not satisfied with a measure may remove it after installation (relevant to all channels) – Actual savings for installed units. Evaluated savings should be based on primary data or reliable published unit savings values (RTF planning values are not reliable). (relevant to all channels)

Cost updates 17 APS typeApplication settingDelivery channelMeasure cost (current) Measure cost* (proposed) Load-Sensing Home EntertainmentDirect install$35$37 Home OfficeDirect install$35$37 UnknownMail-by-request/retail$32 Motion-Sensing Home OfficeDirect install$35$50 Home Offic -by-request/retail$32$40 IR-Sensing Home EntertainmentDirect install$60$52.5 Home EntertainmentMail-by-request/retail$100$42.5 PC Interaction- Sensing Home OfficeDirect installN/A$55 Home Offic -by-request/retailN/A$45 * Prices based on amazon.com and/or manufacturer webpages (Feb. 4, 2015), correspondence with manufacturer, and SDGE Work Paper REHE0004. Direct install costs assume device price same as retail; installation is $5/unit for load-sensing, $10 all others.

B/C Ratios 18

Proposed Motion “I, ______________, move that the RTF approves the Residential Advanced Power Strips as a UES measure – Keep category Planning – Keep status Active – Set sunset date to August, 2018” 19

Additional Slides 20

Alternative Research Method: Bottom-up savings Basic method for estimating savings: – Research the type and quantity of controlled equipment; – Combine with secondary data on estimates of stand-by and active power; – Use judgment to estimate average duration of savings periods for various controlled devices in different operating modes. Similar method appears to have been used in other jurisdictions for some applications. The RTF’s judgment is that this method is not likely to provide sufficient rigor for Proven UES estimates 21

Alternative Research Method: Simulated counterfactual Basic method for estimating savings: This slide will describe the Simulated-counterfactual approach used in several recent “Tier II” studies in California The RTF’s judgment is that this method is not likely to provide sufficient rigor for Proven UES estimates 22

Alternative Research Method: AMI Interval Data Basic method for estimating savings: – Rather than a small sample of plug-load data, use a large sample of whole-house data; – Could use actual pre-post consumption data; – At minimum, interval data could help identify unoccupied vacation periods (might permit longer study periods); – Method details not spelled out in research strategy Con: Reliability hard to know in advance (harder than usual) Pro: Add to understanding of The Great AMI Opportunity Estimates could apply directly to UES for mail-by-request program (assuming units in the study were mailed out) The RTF does not have a strong opinion as to whether this method can provide sufficient rigor for Proven UES estimates 23

References [AESC, 2014] Valmiki, M., and A. Corradini, (AESC, Inc.), Tier 2 Advanced Power Strips in Residential and Commercial Applications, Prepared for SDG&E Emerging Technologies Program. [Ecotope, 2014] Larson, B., L. Gilman, R. Davis, M. Logsdon, J. Uslan, B. Hannas, (Ecotope, Inc.) Residential Building Stock Assessment: Metering Study, NEEA. study.pdf?sfvrsn=6 [ECW, 2012] Bensch, I., S. Pigg, K. Koski, R. Belshe, (Energy Center of Wisconsin), Electric Savings Opportunities for Home Electronics and Other Plug-in Devices in Minnesota Homes, Energy Center of Wisconsin. 24