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Quantification of the energy efficiency gap in the Swedish residential sector

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Abstract

We present a method for quantifying the energy efficiency gap ex ante. To do this, we define the energy efficiency gap as being the difference between the ex ante market and techno-economic energy savings potentials. The estimation of market potential is based on top-down (econometric) modelling of energy demand using data from the period 1970–2005. The techno-economic estimates are made using a bottom-up building stock model (ECCABS) to assess the effects and cost-efficiency of various energy efficiency measures. Common to these two modelling approaches are two scenarios of energy prices, which differ only with respect to the carbon tax component. We implement the method for the case of useful energy demand for space and water heating in the Swedish residential sector up to 2030. In comparison to the level of energy use in 2005 (74 TWh), the top-down model predicts for 2030 reductions in demand for the two price scenarios of 17 and 21 TWh respectively. The bottom-up model predicts corresponding reductions in demand of 25 and 31 TWh respectively. Thus, there is an energy efficiency gap calculated of at least 8 TWh in 2030. An implicit discount rate of 10 % would render the results from the bottom-up modelling identical to those from the top-down modelling. The presence of the energy efficiency gap indicates that there is a need for enhanced policies in order to make future reductions in energy demand reach the levels predicted by the bottom-up modelling.

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Notes

  1. In this review, Gillingham and Palmer describe recent research which uses empirical analysis to investigate, inter alia, the impacts of energy efficiency programmes on heterogeneous consumer types in order to help design the ‘first-best’ policy interventions that would address behavioral anomalies.

  2. Although some well-known bottom-up and hybrid models, such as Poles, Primes and TIMES, take into account the implicit discount rate, they do so in terms of establishing real-world scenarios, as opposed to techno-economic potentials.

  3. For example, in a meta-analysis of 42 utility conservation programmes, Nadel and Keating (1991) found that actual ex post energy savings from residential retrofit programmes ranged from 15 to 117 % of ex ante estimates.

  4. The energy prices and personal income levels must be in the national currencies, in the present case SEK, as householders would have reacted to the dynamics of the currency. However, for comparison purposes, the energy price data are presented in Euro in Table 1.

  5. As stated previously, the present work assumes a constant floor area for the model period, i.e. no construction, demolition or house extensions are considered.

  6. From 1997 to 2005, electricity use for space and water heating is divided into that which is used to power heat pumps and that which is used for direct heating. This is done using data on the number of dwellings that have heat pumps installed (SVEP 2013). For this category, useful energy for space and water heating is assumed to be 1.35 times the level of input electricity (Profu 2013).

  7. As useful energy use is examined in this paper, the terms energy saving measure and energy conservation measure have the same meaning.

  8. As the name suggests, the 450 scenario is one in which the concentrations of greenhouse gases in the atmosphere are stabilised at 450 ppm of CO2equivalent by year 2030.

  9. As the WEO data are given in US dollars, it is first converted to Euro for use in the ENPAC model and then to SEK for modelling purposes using the exchange rates for Year 2005.

  10. While there are other methods of undertaking top-down and bottom-up modelling, e.g. computable general equilibrium for the former and optimization for the latter, the issues that are described below would be similar for these alternative approaches.

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Authors and Affiliations

  1. Department of Energy and Environment, Energy Technology, Chalmers University of Technology, 412 96, Göteborg, Sweden

    Eoin Ó Broin, Érika Mata & Filip Johnsson

  2. Department of Energy and Environment, Physical Resource Theory, Chalmers University of Technology, 412 96, Göteborg, Sweden

    Jonas Nässén

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  1. Eoin Ó Broin
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Ó Broin, E., Mata, É., Nässén, J. et al. Quantification of the energy efficiency gap in the Swedish residential sector. Energy Efficiency 8, 975–993 (2015). https://doi.org/10.1007/s12053-015-9323-9

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