1. Welcome to CEE’s Home Energy Efficiency Index Webinar
Jenny Edwards and Carl Nelson
September 13, 2012
We’ll start the presentation
shortly.
Hover your cursor at the top
of your screen to access the
WebEx menu bar and open
your Chat window.
We will use the chat function for Q&A at the end of the
presentation, but feel free to ask clarifying or technical support
questions
throughout
3. Community Energy Services
key features
• Extensive community engagement
• Comprehensive pathway to energy savings
• Good energy habits
• Direct install of materials
• Major energy upgrades
• Contractor program w. quality assurance
• Follow-up services / financing
Page 3
4. Home Energy Visits
1½ - 2 hour visit
2 energy experts
Direct installation of
materials
Blower door test and
insulation checks
iPad data collection; print
report at site
Page 4
5. [insert slide on recommendations]
Frequency of Different Upgrade
Recommendations
Page 5
8. Minnesota Home Energy Score Pilot
10
“Zone of Unattainability”
8
7
Potential Score
6
Score
5
Current Score
4
3
2
1
1
Page 8
1 Pilot Homes 154
9. Common approach to building asset ratings
Building
Energy
Simulation Estimated Energy Use
Model
Site Data Collection
Rating or
Score
Occupancy Assumptions
Page 9
10. CEE Scoring Methodology
Representative
Housing Types
SIMPLE
Building
Energy
Model
Number of
Stories, House
Age, Floor Area
Point distribution
for each retrofit
Page 10 (1 story home)
13. Summary of Early Experience
+ CEE has delivered 447 scores in Minneapolis and St
Louis Park
+ Score does not add appreciable time increase to visit
+ Positive reaction: Homeowners respond to having a good
grade, and staff have tool to back up recommendations
+ Priorities of action are clear from point system
+ Compared to giving recommendations without a score:
+ Low available points can be a hurdle for action
+ However, this is justified – we are applying the pressure to act
where there are more savings
Page 13
14. Score Distribution
100
90 50% of homes score
80 a 73 or higher
70
CEE Energy Index
20% of homes score
60 an 85 or higher
50
40
30
20
10
Based on 447 Homes
0
0% 20% 40% 60% 80% 100%
Page 14
Percent of Homes
16. Which upgrades offer the most points?
76% of points come
from
immediate, cost-
effective
recommendations
Page 16
17. Relationship between Index and Site Energy Use
10
9
8
Gas Use Intensity Index
7
6
5
4
3
2 y = -0.046x + 8.062
R² = 0.308
1
0
0 20 40 60 80 100
Page 17
CEE Energy Index
18. Next Steps
+ Partner with other groups to deliver the score in new
regions
+ Offer certificate of completion when homeowners have
made upgrades
+ Investigate the impact of the score on homeowner follow
through.
+ Consider refinements such as accounting for ‘above-
and-beyond’ energy retrofits, e.g. PV
Page 18
19. For More Information
Visit the Innovation Exchange website:
http://mncee.org/Innovation-Exchange/Home/
Contact Jenny Edwards:
jedwards@mncee.org
(612) 335-5873
Next Webinar:
Using Tablets to Collect Data in the Field
November 8, 2012 – 12:00 pm CST
http://mncee.org/Innovation-Exchange/
Events-and-Webinars
Editor's Notes
JennyPrimarily designed for existing-home retrofits.Used by field staff during a home audit to help communication what needs to be doneGoal was: something easy and quick to apply for staff; quantitative rigor; easy visual design and communication for the homeowner25 data points
Community Energy Services is a residential energy-efficiency program started nearly 3 years ago. Started in Mpls. – 5,000 homes. Recently started in adjacent suburb – SLP – and plan to expand to other cities comprehensive home performance program Marketing for the program involves extensive community engagement; partnering with neigh. groups, hosting community workshops, active presence at community events The program is designed to be a comprehensive pathway to energy savings and, we work to get energy savings through good energy habits (behavior change), direct install of materials like CFLs, and most importantly through major energy upgrades, including air sealing, insulation and HVAC replacement We maintain a list of qualified insulation contractors, who are required to go through our training and become BPI certified (insulation/air sealing installer cert) We also provide assistance to homeowners in completing upgrades, including providing financing The program is primarily funded by Xcel Energy and CenterPoint Energy, with additional assistance from the cities, and the in-home visit component of the program is part of the utility’s Home Energy Squad program.
The Home Energy Visit itself is conducted by two energy experts – an energy counselor and an energy technician. The counselor primarily assists with the direct installation of materials, including door weatherstripping, programmable thermostats, showerheads, CFLs, and a couple other items. The energy technician conducts a blower door test, checks and records insulation levels, conducts a combustion safety test, and prepares the recommendations report for the homeowner. All data is collected by iPad, and the report for the homeowner is printed out at the site.
Our primary objective in creating our energy rating was to help increase the number of CES participants that completed upgrades. We wanted to create a tool that would provide a clear prioritization of the upgrades needed in the home, and -- by tapping into all of our natural desire to achieve good grades – to provide an additional mechanism to persuade the homeowner to complete upgrades.This goal led to the following design Principles:First and foremost we wanted to provide actionable information about upgrades needed in the home; that is, we wanted the score to link directly to the recommendations that our technicians were making in the home related to major upgrades. Thus, the points in our score should be based on what the homeowner can do; in our case, there are 5 categories. The homeowner is not going to change their window orientation, so we didn’t want to include a value for that in the score. We just wanted to include what can be cost-effectively done in that particular house, and whether or not it has been done or not. And we wanted to include immediate and long term recommendations. Typically, a long-term recommendation would be to replace upon failure with the most efficient model. It is worth pointing out that our focus on major upgrades means that we were looking for what is called an “asset rating”, or one that focuses on the home, and not the energy implications of the behavior of the occupants. So, actionable information.We also wanted homeowners to be able to achieve a perfect score – when homeowner has done everything cost-effective for that house type. This is really important if the tool is to be motivating for the homeowner. We want the homeowner to feel the satisfaction of getting a perfect score when they’ve done what we recommend.Easy-to-understand design to clearly communicate to homeowners.Minimal time to collect data. We wanted to minimize adding any unnecessary time to collect additional data that we wouldn’t already be collecting for our recommendations. We wanted something with sufficient quantitative rigor that is appropriate for good homeowner decision making. You don’t need a complicated building simulation model to support sound, science-based decision making.
CarlHomeowner receives the score as part of a full report
A lot of people say to us why another rating system? Doesn’t the world have enough rating systems? Well, we agree, and we looked quite carefully at several others before we decided that none of them would meet our design criteria. One of the main contenders was the DOE’s Home Energy Score. We like a lot of the aspects of this, enough so that we signed up to be one of the 11? Home Energy Score pilot cities. What you are looking at are the results of the scores from the 154 homes in this pilot. In gray is the distribution of current scores, and the blue is the increase they would receive in the score if they implemented all of our recommendations. As you can see, none of the homes are able to get to a perfect score after implementing the recommendations, and some of them are still quite low scores. We call this the “zone of unattainability”. While this is a more accurate method of comparing scores across homes, we found that it did not help with motivating homeowners to do the upgrades. Since this is our primary goal in implementing the rating, this was a major reason we chose to create our own rating. Another reason was that we can customize the rating to the specific recommendations that we make in the home, which is different than other parts of the country. Minnesota homes, for example, do not typically have ducts outside the conditioned space of the home, so this is not a major recommendation for us, although it may be in many other areas of the country.
In theory this is a direct way to understand the energy use of a home, but there are challenges:it is also a challenge to collect all the necessary data in a timeframe that is reasonable for residential audits. And you are often spending time collecting information that impacts the energy use, but that a homeowner cant change, such as the color of the roof or the orientationThis approach provides a consistent way to compare across a populaition homes, but that means many homes end up scoring poorlAlso it is very hard to predict building energy use. It is easier if you have perfect information, but in the case of a field tool for retrofits, you rarely have the resources to collect perfect info about the home. So for these reasons CEE took a different approach.
What CEE did is different in a fundamental way. Instead of modeling a specific houseThe points available reflect what is cost effective for that home. So for example the points available for wall insulation will be the energy savings available from insulating a home up to its full cost-effective level. For homes here that is (R-30??) – Different for newer homes?
Then, at the time of the home visit, we collect data on the specific state of the house. We arent modeling its enegry use, but we are measuring how close it is to its full cost-effective potential. Our staff send the data to our Index APIMeasure weights are based on housing type, and the score is based on the homeWe call this a “prescriptive approach with quantitative weighting”
For this example a home was built in 1910 and it is 1 story – so it has a 2x4 wall cavity. The recommended level of insulation is R-30. plugging that into an energy model gives the weighted value of wall insulation at 27 points. So that takes into account the fact that a one story home has less wall area than a two story home – it will have fewer points available. 2x6 home is R-19…The state of the actual home is (empty walls)MAYBE use the label we actually have
Carl
Overall distribution of scores
This shows where homeowners can get the most points. Like carl’s slide from earlier it shows which measures are being recommended, but also what the relative savings from those different upgrades is. About ¾ of all points are from near-term, cost effective measures. Wall insulation offers the largest potential, but a fairly even distribution across the different measures. The exception is windows, less than 1% of points is from windows. Future points are mostly from the heating system, when we recommend that the owner get a more efficient version when they replace their current model.
For those of you that know something about energy model, the R2 for a field asset tool this is pretty good. Obviously a lot of other factors – occupant behavior is a huge oneAccurate enough for us to feel confident giving recommendations
Ultimate questions is: does this get people to do what we want them to?