by K.T. Weaver, SkyVision Solutions
What if the billions and billions of dollars being spent to deploy so-called “smart meters” were found to be justified based upon biased and false assumptions? Should consumers still be required to pay for smart meters that were erroneously promoted as being installed for their benefit, i.e., to help them manage their energy bills?
This article will demonstrate that based upon the latest research and under the most optimistic circumstances, consumers within the general population might reduce their energy consumption by only as much as 0.5 to 0.7 % if they have access to enhanced feedback from smart meters.
In this instance, “enhanced feedback” consists of energy consumption information that can be communicated through in-home displays (IHDs) and/or can be disaggregated by individual appliance (or load types or behaviors) by analyzing data from smart meters for each customer.
In reality, very few consumers yet have access to this level of detail where smart meter data has been displayed through IHDs or disaggregated into individual uses. Generally in the United States and Canada, consumers with smart meters have access to their granular data through a web portal (on a delayed basis) so they can see when they use the most energy. In addition, there is little evidence that consumers are interested in having access to this data. As previously reported at this website, less than 1% of the millions of smart meter customers in Texas have ever logged in to view their usage data .
In my prior article at this website (Part 1) , I laid the foundation for why prior studies going back some 20 years or so have provided inflated, positively biased results that smart meter enabled feedback mechanisms can help consumers conserve energy. These prior studies asserted that smart meters could enable energy savings of up to 12 to 15%.
Specifically, the American Council for an Energy-Efficient Economy (ACEEE) has made claims that “12 % savings are possible for programs with real-time information and feedback.” 
In my prior article, I demonstrated how energy feedback studies suffer from a number of possible positive biases, such as:
- Lack of discussion or consideration of potential bias in systematic reviews of energy feedback studies
- “Opt-in” nature of pilot studies where participants are “energy enthusiast volunteers”
- The Hawthorne effect where study participants are affected by knowledge of being in a study
- Little recognition that potential savings fade over time due to “novelty factor”
- Publication bias
Two more recent and rigorous systematic reviews of energy feedback studies have been published, the latest one just last month. Unlike prior studies, these new studies attempt to account for the types of biases mentioned above. The two new studies are:
- “Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature” (May 2016) 
- “Setting a Standard for Electricity Studies” (November 2013) 
In the May 2016 review of studies , the authors primarily examined the possible effect on consumers for disaggregated energy feedback:
“We examine twelve studies on the efficacy of disaggregated energy feedback. The average electricity reduction across these studies is 4.5 %. However, 4.5 % may be a positively-biased estimate of the savings achievable across the entire population because all twelve studies are likely to be prone to ‘opt-in’ bias hence none test the effect of disaggregated feedback on the general population.”
“The average opt-in rate is 16 %. … If 16 % of the population reduced their energy consumption by 4.5 % then the mean reduction would be 0.7 %.”
For the November 2013 review of studies , the authors’ primary finding was with regard to IHDs, stating the aggregate feedback offered by IHDs provided the best overall reduction in energy use:
“We present a meta-analysis of 32 studies of the impacts of these interventions, conducted in the US or Canada. We find that methodological problems are common in the design of these studies, leading to artificially inflated results relative to what one would expect if the interventions were implemented in the general population. Particular problems include having volunteer participants who may have been especially motivated to reduce their electricity use, letting participants choose their preferred intervention, and having high attrition rates.”
“… we made no adjustment for volunteer bias in the 27 studies that reported relying on individuals who selected themselves into the test (and the one that said nothing).”
“In-home displays provided the best overall reduction in energy use, approximately 3 % after adjustment for risk-of-bias.”
Although the 2013 review  made attempts to account for study biases, it did not provide adjustments for the volunteer selection bias, stating that “no adjustment estimates are available.” The previously mentioned 2016 study  developed a rationale to assign an adjustment value of 16 %, estimating that the average opt-in rate is 16 %. If one were to assign the same value to the 2013 study results, then the reduction in energy use expected from IHDs would drop from 3 % to about 0.5 % for the general population.
With an expected potential savings of less than 1 % for the general population through the use of smart meter enabled enhanced feedback, it would be meaningless (and a waste of resources) to attempt massive expenditures for smart meter deployments. Without any interaction with smart meter feedback, a consumer could easily save much more energy by simply reviewing and acting on some of the helpful information provided at the website of Exploring Energy Efficiency & Alternatives  or my prior article of Tips on How to Save Energy and Money without a ‘Smart’ Meter .
Utility companies have been able to largely fund smart meter deployments based upon biased and false assumptions that enhanced feedback enabled by smart meters would result in consumers significantly reducing their energy consumption. Certainly in trying to convince regulators on the concept of smart meters and having the customers pay for the meters, this was the “sales pitch” from a policy perspective.
As stated in my prior article (Part 1) , the ACEEE created a chart in 2010 that indicated that direct feedback through IHDs could be expected to reduce “average household electricity savings” by 9.2 %. The ACEEE also proclaimed that “real-time info down to the appliance level” could reduce the same savings by up to 12.0 %.
We now find that based upon more objective studies and as highlighted in this article, the maximum potential electricity savings for the general population is more in the range of 0.5 to 0.7 %:
Smart meter proponents have begun to realize that smart meters have failed and were a dumb investment in terms of meeting their initial expectations (as outlined in my 2014 article at this website) . Unfortunately, rather than admitting defeat, they are now pushing for crude and heavy-handed pricing mechanisms in attempt to change consumer behavior  . It is quite clear that policy makers and electric utility companies are not acting in the best interests of consumers.
There is an urgent need for smart meter deployment projects to be re-evaluated and for governments and regulators to rationally judge these projects based upon unbiased information and from a consumer protection perspective.
References for this Article
 Assessing the Prevalence of Bias in Studies Showing Savings Linked to Energy Consumption Feedback (Part 1), SkyVision Solutions Blog Article, June 2016, at https://smartgridawareness.org/2016/06/03/accounting-for-bias-in-energy-consumption-feedback-studies/
 “Advanced Metering Initiatives and Residential Feedback Programs: A Meta-Review for Household Electricity-Saving Opportunities,” American Council for an Energy-Efficient Economy (ACEEE), Report Number E105, June 2010; available at https://skyvisionsolutions.files.wordpress.com/2016/06/aceee-ami-feedback-programs-2010.pdf
 “Does disaggregated electricity feedback reduce domestic electricity consumption? A systematic review of the literature,” by Jack Kelly and William Knottenbelt, Department of Computing, Imperial College London, UK.; May 2016; available at http://arxiv.org/abs/1605.00962; http://arxiv.org/pdf/1605.00962v2.pdf
 “Setting a Standard for Electricity Studies,” by A. L. Davis, et.al., Energy Policy, vol. 62, pp. 401–409, Nov. 2013; available at http://www.sciencedirect.com/science/article/pii/S0301421513007362
 “Exploring Energy Efficiency & Alternatives,” at http://e3a4u.wyoextension.org/energy-technologies/home-energy/top-ten-tips/
 “Tips on How to Save Energy and Money without a ‘Smart’ Meter,” SkyVision Solutions Blog Article, January 2016, at https://smartgridawareness.org/2016/01/28/how-to-save-energy-without-a-smart-meter/
 ‘Smart’ Meters Have Failed and Were a Dumb Investment, SkyVision Solutions Blog Article, December 2014, at https://smartgridawareness.org/2014/12/18/smart-meters-have-failed/.
 “Little Justification for Smart Meters Unless to Serve as ‘Crude and Heavy-Handed Price Mechanism’ to Change Consumer Behavior,” SkyVision Solutions Blog Article, April 2016, at https://smartgridawareness.org/2016/04/07/little-justification-for-smart-meters/
 “Smart Meter Enabled Demand Charges: ‘No Way to Live’,” SkyVision Solutions Blog Article, May 2016, at https://smartgridawareness.org/2016/05/26/smart-meter-demand-charges/