Role of energy efficiency in energy transition: A decomposition analysis of energy use

• Published in: Solar Compass 2024-12, Vol.12, p.100086, Article 100086
• Main Author: Sharma, Pooja
• Format: Article
• Language: English
• Subjects: Decomposition analysis; Energy efficiency; Energy transition; Energy use; Logarithmic Mean Divisia Index (LMDI) method; Norway; Recession
• ISSN: 2772-9400; 2772-9400
• DOI: 10.1016/j.solcom.2024.100086

•The overall energy use between 1990 and 2017 is disaggregated into activity effect, intensity effect, and structural effect.•The activity effect is due to an increase in economic activity of a particular sector, the intensity effect is due to changes in energy use per value of output, while the structural effect is due to structural change in the economy.•The results reveal that services and the residential sector contribute positively to an increase in energy use.•The structural change in the transport sector has increased the overall energy use in Norway. Post-recession, the energy use in the transport sector was due to structural effects.•The policies to enhance energy efficiency in energy-intensive sectors, transport, and services sector must be undertaken to efficiently visualize energy efficiency-driven energy transition. The use of energy-efficient technologies tends to reduce the overall energy use of a country and foster the energy transition pathways. However, a change in energy can occur either due to a change in activity effect, intensity effect, or structural effect. The objective of the study is firstly to examine and measure the magnitude of change in energy use and identify the factor responsible for the change in energy use in the selected sectors. Secondly, the paper aims to analyze the impact of the Norwegian economy on the three effects of energy use. The study contributes significantly to identifying the sector that experiences a reduction in energy use due to energy efficiency and examining the impact of the economy on energy use. The overall energy use between 1990 and 2017 is decomposed into three different effects for selected energy-intensive sectors by deploying the ‘Logarithmic Mean Divisia Index’ (LMDI) method. Further, the impact of the Norwegian economy is examined on the three effects of energy use. It is observed that in each Phase, the key driver for change in energy use in all three Phases is the transport sector. Post-recession, the energy use in the transport sector was due to structural effects. Consumer behavior and limitations of sources of finance are the challenges for the deployment of electric vehicles even after technological breakthroughs in energy efficiency. Finally, the policies to enhance energy efficiency in energy-intensive sectors, such as the transport, and services sector must be undertaken to efficiently visualize energy efficiency-driven energy transition.