Letters: May/June 2012
Should Energy Source Matter in Home Energy Auditing?
In the context of home energy auditing, the Home Energy Score can be very misleading since it is based on "source energy," which severely penalizes electrical energy sources ("Energy Performance Score," Jan/Feb '12, p. 6). Environmental and home energy efficiency issues are thus combined. Home energy auditing is concerned with improving the energy efficiency of residences regardless of the energy source. The credibility of this score would be enhanced if its basis is made clear and scoring is based only on the energy consumption of homes. Environmental concerns are valid but do not belong in home energy auditing.
via Home Energy website
Dariush Arasteh, an efficient windows expert in the Environmental Energy Technologies Department at Lawrence Berkeley National Laboratory, passed away on February 3 after an eight-year battle with cancer. He was 51 years old. A 30-year lab veteran, Arasteh was involved in all aspects of research on energy-efficient windows, with a focus on highly insulating "superwindows," creating a suite of computer tools to analyze window-heat transfer, and leading industry to develop a rating system for the thermal performance of windows.
He will be missed by his wife Nancy Hendrickson, his son Jasper Arasteh, his colleagues at the lab and many friends.
Author Steve Mann replies:
Thank you for your comment. Personally, I don't agree. Electric energy sources are inherently inefficient because of production and delivery methods. Many legal authorities and energy codes recognize that inefficiency. A lot of analysis software produces CO2 emissions numbers because homeowners are interested in understanding their carbon footprint.
Those numbers would be useless if they ignored source energy. Like so many things in this world, including source energy in home energy auditing software seems to me to be a matter of personal taste, not a black and white issue. We do agree on one thing—the credibility of all home energy auditing scores depends on a very clear explanation of the principles underlying that score.
Home Energy occasionally receives letters from readers that do not refer to previous articles but reflect a common concern of the home performance community. The editors have decided to create a new category in the Letters section, the Readers Forum. We invite readers to send letters expressing opinions and ideas for this section of the magazine.
Energy Bill Disclosure and Modeling
There is little dispute that energy bills are a major cost to American homeowners, often the single biggest monthly cost after a mortgage payment. Clearly, the fact that this information is not disclosed at the time of sale is a major missing link in the value chain of residential energy efficiency. While it is logical to assume that a house that costs less to operate should command a higher resale value, and should have a measurably lower risk of default, than a typical home, we currently lack sound data to validate this assumption. Public policies concerning energy bill disclosure are moving forward based on incomplete data, and on the belief that labeling the energy use of homes for sale will cause a significant increase in the adoption of residential energy efficiency. This belief is not clearly supported by the data either.
While it is valid to assume that energy bill disclosure will increase the value, and the market penetration, of efficient houses, this assumption remains unproven. No study has demonstrated the relative value of different approaches to energy disclosure; nor has there been any statistically valid analysis linking the cost of various approaches with their relative impact on the market. Without this information, no informed policy decisions can be made that balance the value of a particular approach to energy disclosure with its costs, and with its ability to drive the private investment of capital.
We must stop looking for a one-size-fits-all approach to energy bill disclosure. Valid approaches may range from simple disclosure, on the one hand, to a savings prediction that is valid on a house-by-house basis. Up to now, we have been searching for one approach that will produce two different things at once. First, it will produce an asset rating that is based on the house independent of occupant behavior—a rating that is modeled on large volumes of data (averages) or on the relationship of actual home performance to code. Second, it will produce an accurate savings prediction to individual homeowners—a prediction of statistically acceptable accuracy sufficient to drive capital investment on a pooled basis, insure risk, and allow the conversion of energy efficiency (EE) into a measurable resource.
As the saying goes, good / fast / cheap, pick any two. If we want to put labels on perhaps 70 million homes over the next 20 years, it is reasonable that simple disclosure or labeling should be fast and cheap rather than good—that is, accurate. A $500 rating is not a reasonable policy objective when you consider the $30+ billion price tag to reach every house. However, if we want to guarantee consumer savings, attract capital that will offset debt load as a means of reducing risk, or sell savings to a utility as a capacity resource, we need to be good. We need to adopt more stringent techniques for applications that require this additional level of accuracy. Such techniques must include occupant behavior in predicting savings. The relationship of a house to code, or relative to other homes, is not important in these cases. What really matters is the actual savings delivered at the meter. This is the tangible value that EE creates.
For EE to become a tradable resource, it is essential that market actors agree on a standard way to measure that resource, whether it be in pounds, kilograms, or kilowatt-hours. Standardized measures provide transparency and efficient pricing, which allows the market to function. To date, the residential EE sector has suffered from the lack of a standard for measuring the savings resulting from EE measures. Until a precise and accurate system for quantifying energy savings can be developed, the market for EE will remain underdeveloped and unable to access the massive flows of private capital that comprise the world's largest sector—energy.
Approaches to Energy Disclosure
Below is a list of the various methods of energy disclosure, beginning with the cheapest approach.
Disclose historical energy use. With regulatory changes, simple disclosure could be essentially free. There is also an argument to be made that actual bills are much more relevant to, and more easily interpreted by, consumers than any sort of metric or score. What is Btu/ft2 or a 7 out of 10, let alone a 139 on a HERS scale, to your average homeowner? It may in fact be easier to get potential buyers to take the real bill and then normalize factors such as occupancy or relative size of the house, based on common sense and their own experience, than to try to get people to adopt new metrics (we need study!).
This is actually closer to miles per gallon (mpg) in many ways than it is to a HERS score. Mpg is not a metric calculated by adding up all the components of a car; it is gas use per mile based on running and measuring the whole car performance. However, it is also important to note that when you are on a car lot, you assess that car based on structured, tested mpg; but if you ask someone the mileage of the car they own, they will almost always answer based on the consumption they are actually getting.
Disclose normalized energy use. This approach normalizes energy bill data based on a few simple metrics that are generally available in the public domain. These metrics include size, location (heating and cooling degree-days), and occupancy based on number of bedrooms plus one. The result is an approach that is based on actual data, but is normalized to make it easier to compare two houses side-by-side. This approach has the disadvantage of being more confusing to the consumer than the simple dollars per month of just looking at the bills. But it could easily be combined with simple bill disclosure, and it could accomplish energy use disclosure with a simple regulatory change to disclosure requirements.
Simple energy scores. This category includes the DOE Home Energy Score (HES) and the Earth Advantage Energy Performance Score (EPS). While these take different approaches, and generate different types of output (EPS uses Btu/ft2; HES uses a scale of 1 to 10), each is designed to deliver a simple asset score based on a very limited number of inputs and little to no performance testing. Although it has not been shown conclusively that simple energy scores as a disclosure item drive adoption of EE, or influence home value, better than bill disclosure, at least they are cheaper and faster than a full HERS test. HES also has the advantage of being built with an application programming interface (API) that allows third-party software to generate the rating without requiring auditors to use yet another piece of software. It is also important that ratings be performance based (that is, that they demonstrate accuracy against real homes) and that they not be exclusive to one system. However, if we are to accept the selection of a single winning system, rating algorithms should be transparent and subject to the American National Standards Institute (ANSI) consensus process rather than be hidden in a proprietary black box.
The disadvantage of simple energy scores is that they cannot be used to generate work scopes or savings predictions on an individual house. Their limited inputs do not always allow for the variety of measures conducted in the field. This, and the fact that they cannot be calibrated with actual occupant behavior or bills, makes them too blunt a tool for home performance that relates to a specific house—rather than an average based on a pool of houses.
Home energy ratings. HERS scores are based on creating a whole house simulation of a building, based on standard occupant behavior, and comparing that simulation to a code reference house. This approach combines the cost and complexity of a full-scale energy audit and modeling exercise with the lack of accuracy that results from using average data for behavior and constraints on model inputs. A score that is based how a house compares to a code (which changes every few years) is a score that is hard for consumers to understand. This is partly because the score is expressed as a number on a scale where 0 is best, and partly because energy consumption is based on source consumption and not on the consumer's meter.
Home Performance Modeling
We are currently in a transitional period in the home performance industry. Let's look first at what is best practice today, and then at where we need to be in the future. Today's best practice to provide modeled results that closely resemble actual savings is based on the combination of a simulation model of building characteristics and actual occupant behavior that is calibrated to actual energy bills (see BPI Standard 2400). This approach can be seen in the recently proposed 25E tax credit.
As we move forward we need to move to a model where rather than specify a standard for how to predict saving, we instead measure how an approach to retrofitting (standards, certification, QA, software) delivers on predicted savings in terms of variance and average savings against actual bill data. This would constitute a true performance approach. Such an approach will provide the type of data that will create manageable risk around portfolios of energy efficiency retrofits, which will allow utilities to start treating them as an actual capacity resource, and will allow for securitization of those portfolios into an investment-grade product that financial markets can invest in.
In sum, bill disclosure, or even a simple rating at time of sale, will probably help to close the loop on the energy efficiency value chain that has been broken by the inability of home sellers and buyers to realize its value at the time of sale. However, any home retrofitting policy that is deployed should carefully balance costs against benefits. And—given the absolute requirement that private capital markets must begin to invest in residential EE in order for this industry to reach scale—these rating or labeling policies must be harmonized with the type of investment-grade output that the market requires.
One size does not fit all, and policy makers should recognize that any disclosure system that gets implemented must leave room for market innovation. Energy labeling and home retrofitting policy should be developed in a way that does not force an evolving energy efficiency market into a regulatory straitjacket. As an industry, we must test our beliefs and assumptions based on scientifically valid results from actual tests in the market, and compare these results to real performance measured at the meter. And we must do this before we spend billions of dollars on large-scale rollouts of untested systems that are supported by conflicting data that make the effectiveness of these systems, at the very least, uncertain.
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