Introduction

In the old day,  not quite gone by, meter readers were employees of the utility who came by once in a while to look at our meter and read what it said about how much energy we were using.  Soon after we would get a bill for the total amount of electricity we had used in a certain period of time.  We were by and large clueless or illiterate about these meters.  In the new days we are expected to become the readers of our own electric and other meters.  A recent report suggests that we need more literacy training.

The Irish Commission for Energy Regulation (CER) has embarked on a Smart Metering Project, focusing on residential customers and Small and Medium Enterprises (SME), and the initial results were reported this spring. The CER is the independent body responsible for overseeing the regulation of Ireland’s electricity and gas sectors.  This digest includes only the portion of the Project that analyzes the findings regarding customer behavior trials. (1)

Background for the Study

The smart meters differ from traditional meters in several important ways.  The smart meters are electronic rather than mechanical and they can convey information about how much electricity is being consumed each 30-minute period and provide that real time information to both the utility and the customer so that both can determine the amounts and patterns of behavior that result in higher usage, and higher costs.  If the customers know when they use more electricity and what usage costs more, then they will reduce their usage or use appliances and equipment at non-peak hours when electricity can be cheaper if time-of-use electricity tariffs are available.  As the CER report summarizes, “Smart meters can facilitate improving energy efficiency by empowering consumers with more detailed, accurate and timely information regarding their energy consumption and costs, thus helping consumers reduce any unnecessary energy usage and shift any discretionary electricity usage away from peak consumption times.”  That at least is the theory and expectation.

The CER undertook this Smart Meter Project to test that hypothesis.  The report notes the European Union (EU) legislative efforts and initiatives that are promoting and exploring the form and use of smart meters.   Appendix C provides a useful summary for the status of smart meter rollouts in various EU countries, as of February 2011.

In the Republic of Ireland (RoI) the government has adopted a National Smart Meter Plan, in part to provide an infrastructure and support for a Smart Grid, and to adhere to EU policies on this issue.  The CER issued a Consultation Paper on its efforts to promote smart metering, engaged with various industry groups, and began the customer behavior trials, and other components of the Project. (2)

Residential and SME customers were recruited, after statistical sampling methods were used to select the general population for the study, and smart meters were installed by the end of June 2009.  Between July and December 2009, usage of electricity was measured as a benchmark before the actual testing began from January to December 2010.

The study used two main variables to assess customer behavior:  time of use tariffs (ToU), where different prices were charged at different times of the day, in conjunction with a number of demand side management (DSM) informational stimuli i.e. detailed billing on a bi-monthly or monthly frequency, in-home displays, an overall load reduction (OLR) incentive and Web access.  Detailed billing, provided bi-monthly or monthly, included graphs of average usage costs by ToU, appliance ToU cost table, text based messages that were personalised and motivational with some historic and peer comparisons.  In-home displays (IHDs) were electronic devices linked to the smart meters that give near real-time information to consumers on their electricity consumption and associated costs, and also provide historical information in the form of day-on-day, week-on-week and month-on-month comparisons, as well a daily budget setting function. IHDs were referred to as ‘electricity monitors’ for the purposes of the customer behaviour trials.  Overall load reduction (OLR) incentive was a financial reward available to customers who can reduce their electricity usage by a certain percentage target when compared to the same period in the previous year.  Finally, web access provided detailed electricity consumption and cost information to customers via a Web account. The Web account was targeted specifically at SMEs but was also available to residential consumers on request.

A representative sample of over 5,000 residential consumers and 650 businesses throughout Ireland participated in the electricity customer behaviour trials.

The Results

For residential customers, the general finding was that time of use tariffs in combination with other demand side management stimuli results in a statistically significant reduction in electricity consumption.  Specifically, the tests resulted in an average reduction in overall electricity usage by 2.5% and peak usage by 8.8%.  Households that prior to the trials had higher consumption experienced greater reductions in usage.  These households tended to have higher educational achievements and social grade.  Those who use more end up saving more through the time of use and demand side stimuli, but families that were fuel poor also benefitted from the time of use tariffs.  Much of the savings came from shifting usage from peak to the post-peak period, especially to nighttime usage.

Of all the residential customers, 82% of participants made some change to the way they use electricity and 74% said the changes were major. Only 18% stated that there had been no impact on the way their household uses electricity.

Fridge magnets and stickers, and the electricity monitor, were found by the customers to be effective in helping them change the way and time that they used electricity.  For those who found it difficult to switch to nighttime usage, they cited safety and convenience as the main barriers.

The time of use pricing seems to have been the most effective tool in reducing usage and getting people to switch from peak to non-peak usage. For the demand side stimuli, the bi-monthly bill, energy statement and electricity monitor, in combination, were most effective at reducing both overall and peak usage. The electricity monitor in particular was found to be easy to use by most participants with 84% stating that it helped them to reduce the amount of electricity they used and 84% stating it helped them to shift usage.

There was a discrepancy between what people perceived to be their level of reduction during peak, and increase in usage during non-peak.  Generally they thought they had reduced their bills and consumption overall and during peak periods, with for example 74% believing they had reduced peak usage when in fact only 68% had actually reduced peak usage.

The trials also found that children below the mid-teen years play a significant role in terms of motivating change and energy reduction in the household. Evidence from the focus groups conducted during the research suggests that that this is driven strongly by school based initiatives such as An Taisce’s Green Schools programme.

Interestingly, for SME customers the savings were substantially less and not statistically significant with overall reduction in electricity usage of 0.3% and reduction in peak usage by 2.2%.  Moreover, no particular tariff or DSM stimulus was effective in reducing usage in a statistically significant amount.  Yet almost half of the SME participants believed that they reduced overall usage and slightly more than half stated they reduced peak usage.

Implications

The results from the Project are encouraging.  At a minimum, users saved enough on their annual electric bill to repay the costs of the smart meters in almost one year with the annual savings thereafter net savings.  The results are a little disappointing in that not more reductions were achieved.

Even many of those who had successfully reduced or shifted usage stated that they found it difficult to shift peak usage, and many found it hard to shift usage to nighttime. The explanation provided by customers was that they did not see a reduction in their bill as a result of reducing their usage during peak times.  The CER acknowledges that, “This is a challenging problem because reduction in peak usage does not necessarily translate into a large reduction in the bill.”

In an interesting finding, customers as a group overestimated their savings in usage suggesting they find it difficult to accurately measure usage, despite being provided the information on actual usage.  The Report notes but does not explore this finding, in particular any implications on training customers on better understanding of the information provided through the various demand side stimuli.  In a similar vein, participants stated that they became more aware of energy usage (54% agreed), which is in keeping with the reduction in usage recorded, but there was a lower level of success in terms of motivating or enabling change with 22% agreeing they now knew more about how to reduce use and 24% stating that they were more interested in reducing their usage.

If we hope to reduce energy usage, and GHG emissions, through energy efficiency then customers seem to require more efforts toward educating them on how to make the savings and how to read their meters more closely.

Perhaps the larger lesson is that technological advances in and of themselves will not sufficiently reduce our dependence on the comfort and convenience of electric appliances and equipment.  More is needed and the more comes from the world of behavior change rather than from technology.  We should not be surprised by this as one of the fast developing issues for those studying climate change is how we persuade individuals and small groups to modify their behavior in order to reduce dependence on fossil fuels — use less energy, use renewables not fossil fuels, drive differently.

One of the real contributions of the Smart Meter Project is that it has begun to ask what conditions are necessary for people to change their behavior in the way they use electricity, and it has begun to provide some valuable lessons on that issue.

Notes

(1)  The other components to the Project are a Technical trials findings report, and a cost-benefits analysis report.

(2)  It appears that CER did not consult with environmental NGOs on the Project.

Sources

CER, Smart Metering Information Paper 4: Results of Electricity Cost-Benefit Analysis, Customer Behaviour Trials and Technology Trials

(16 May 2011). www.cer.ie/en/information-centre-reports-and-publications.aspx?article=5dd4bce4-ebd8-475e-b78d-da24e4ff7339

“Smart Meters” in iePEDIA section of irish environment.