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Making smart meters smarter the smart way

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  • Gosnell, Greer
  • Martin, Ralf
  • Muuls, Mirabelle
  • Coutellier, Quentin
  • Strbac, Goran
  • Sun, Mingyang
  • Tindermans, Simon

Abstract

We report first results from a large scale randomized control trial of different forms of energy consumption feedback facilitated by smart meters and smart phone feedback apps. Nearly 40,000 customers of a large energy retailer in the UK were exposed to either very basic feedback apps - i.e. simply giving consumers access to monthly energy consumption - or more advanced feedback involving peer group comparisons as well as dis-aggregation of total electricity consumption. We find that more advanced feedback can lead to an average consumption reduction of nearly 4% (Intent to Treat). Taking into account that a large number of customers never sign in to any feedback apps suggests that the reduction effect among customers that do sign in is up to 12%. The smart meter installation was implemented by different installation firms across our sample and we find the reduction effect only for one customers of one installer who displays higher capabilities along a number of metrics. This could suggest that achieving energy preservation objectives does not only depend on the technology involved but also on the capabilities and skills of firms installing those technologies. In the UK, smart meters are by default installed with In Home Displays (IHD) that provide real time feedback on energy use. Some of the customers in our sample did not receive an IHD and we explore if this had any impact on the consumption reduction effect described above. Customers with (and without) IHD comprise a self-selected sample so we have to be careful in drawing causal conclusions. However, we do not find any evidence that any energy reducing effect is contingent on IHDs.

Suggested Citation

  • Gosnell, Greer & Martin, Ralf & Muuls, Mirabelle & Coutellier, Quentin & Strbac, Goran & Sun, Mingyang & Tindermans, Simon, 2019. "Making smart meters smarter the smart way," LSE Research Online Documents on Economics 102618, London School of Economics and Political Science, LSE Library.
    • Handle: RePEc:ehl:lserod:102618
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    References listed on IDEAS

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    1. Lynham, John & Nitta, Kohei & Saijo, Tatsuyoshi & Tarui, Nori, 2016. "Why does real-time information reduce energy consumption?," Energy Economics, Elsevier, vol. 54(C), pages 173-181.
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    Cited by:

    1. Batalla-Bejerano, Joan & Trujillo-Baute, Elisa & Villa-Arrieta, Manuel, 2020. "Smart meters and consumer behaviour: Insights from the empirical literature," Energy Policy, Elsevier, vol. 144(C).

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    More about this item

    Keywords

    behavioural intervention; household energy demand; randomised control trial; information;
    All these keywords.

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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