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Unintended Effects of Energy Efficiency Policy: Lessons Learned in the Residential Sector

Author

Listed:
  • Andra Blumberga

    (Institute of Energy Systems and Environment, Riga Technical University, LV-1048 Riga, Latvia)

  • Gatis Bazbauers

    (Institute of Energy Systems and Environment, Riga Technical University, LV-1048 Riga, Latvia)

  • Selina Vancane

    (Institute of Energy Systems and Environment, Riga Technical University, LV-1048 Riga, Latvia)

  • Ivars Ijabs

    (Advanced Social and Political Research Institute, University of Latvia, LV-1019 Riga, Latvia)

  • Jurijs Nikisins

    (Advanced Social and Political Research Institute, University of Latvia, LV-1019 Riga, Latvia)

  • Dagnija Blumberga

    (Institute of Energy Systems and Environment, Riga Technical University, LV-1048 Riga, Latvia)

Abstract

The European Union has set an ambitious goal to tackle climate change, and energy efficiency in the residential sector is among the measures required to close the gap between targeted and actual greenhouse gas emissions. While different policy tools have been applied, the diffusion rate of these measures remains low. A system dynamics simulation model of the residential sector was developed to assess the advantages and drawbacks of energy efficiency policy in the multi-family building sector based on experience accumulated over the last twelve years in Latvia. The model was validated in expert group model building sessions and with historical trends. Simulating the model, a hypothesis was tested that supported the idea that seemingly positive policy tools set the stage for a series of unintended adverse effects due to the complex interactions between different system components. The common assumption that information and financial support should result in significant energy efficiency diffusion proved to be wrong. It instead results in unintended long-term consequences that hamper national energy efficiency goals. The model carried out an analysis and brought insights for improving the effectiveness of government energy efficiency policy. It is concluded that models that broadly describe complex systems are needed to identify effective policies and foresee unintended side effects.

Suggested Citation

  • Andra Blumberga & Gatis Bazbauers & Selina Vancane & Ivars Ijabs & Jurijs Nikisins & Dagnija Blumberga, 2021. "Unintended Effects of Energy Efficiency Policy: Lessons Learned in the Residential Sector," Energies, MDPI, vol. 14(22), pages 1-31, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:22:p:7792-:d:684476
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    References listed on IDEAS

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    Cited by:

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    3. Alberto Barbaresi & Mattia Ceccarelli & Giulia Menichetti & Daniele Torreggiani & Patrizia Tassinari & Marco Bovo, 2022. "Application of Machine Learning Models for Fast and Accurate Predictions of Building Energy Need," Energies, MDPI, vol. 15(4), pages 1-16, February.

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