A framework to characterize energy efficiency measures

Trianni, Andrea; Cagno, Enrico; Donatis, Alessio De

doi:10.1016/j.apenergy.2013.12.042

Cited by 147 publications

(154 citation statements)

References 68 publications

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“…Trianni et al (2014) and Fleiter et al (2012), but in regard to EEU, less work has been done. For the sake of simplicity and for follow-up reasons, it is recommended that the taxonomy for EEU be integrated with the research already presented concerning EEMs, with at least an integration of type of sector, and type of process (support and production processes, etc.…”

Section: The Need Of a New Taxonomy For Categorizing Eeu And Eems Amomentioning

confidence: 99%

“…The characteristics are further divided into attributes to find out the overall possible adoption rate of the specific EEM. Trianni et al (2014) introduce a framework to characterize EEMs that is more directed towards decisions on-site than decisions regarding policy measures, which is the scheme that Fleiter et al (2012) tend to emphasize. Trianni et al (2014) propose instead a characterization framework applied to the EEMs in selected cross-cutting technologies including characteristics such as economic, energy, environmental production-related and implementation-related.…”

Section: Categorization Of Eem Datamentioning

confidence: 99%

“…Classification schemes for EEMs, such as proposed by Fleiter et al (2012) and Trianni et al (2014), are located on a higher aggregation level and are based on, and dependent on, divi- …”

Section: Categorization Of Eem Datamentioning

confidence: 99%

“…Some work is currently being developed about EEM classification (e.g. Fleiter et al, 2012;Trianni et al, 2014), but in general, contributions are scarce.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

International study on energy end-use data among industrial SMEs (small and medium-sized enterprises) and energy end-use efficiency improvement opportunities

Thollander

Paramonova

Cornelis

et al. 2015

Journal of Cleaner Production

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The industrial sector is important to study in terms of improved energy efficiency, being one of the major energy-using sectors and responsible for a major share of CO2 emissions.The energy end-use (EEU) in the industrial sector is complex in general as processes are intertwined and interrelated. Moreover, bottom-up data of EEU on an aggregated level is scarce.Data for total energy supply like electricity, oil, coal, and natural gas exists but bottom-up data of what processes these energy carriers are used in, and moreover, where the major potential for implementation of energy efficiency measures (EEMs) exists, is less prevalent.This holds in particular for industrial small and medium-sized enterprises (SMEs). This makes policy formulation and design for industry a great challenge. Knowledge on where and how energy is used, as well as where opportunities for improvement exist, may provide good support for developing the most effective policies. Therefore, the aim of this study has been to present and compare available bottom-up energy data for industrial SMEs in four countries, namely Belgium, Italy, Japan and Sweden. Results show that the existence and quality of bottom-up EEU data differs largely between the countries and the development of a general taxonomy of structuring EEU data as well as EEMs is needed. Without the development of such a general taxonomy, the deployment level of EEMs and carbon dioxide emission reductions is unlikely to ever reach its full potential as knowledge is missing on how large the potential is, in which processes the major potential is found, how far industry has reached in terms of deployment levels, and in which areas future energy policies are needed. In conclusion, this paper of EEU and EEM in industrial SMEs addresses the high importance of future research in creating a harmonized data categorization, as this will greatly support the transition towards sustainable industrial energy systems.

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Section: The Need Of a New Taxonomy For Categorizing Eeu And Eems Amomentioning

confidence: 99%

Section: Categorization Of Eem Datamentioning

confidence: 99%

“…Classification schemes for EEMs, such as proposed by Fleiter et al (2012) and Trianni et al (2014), are located on a higher aggregation level and are based on, and dependent on, divi- …”

Section: Categorization Of Eem Datamentioning

confidence: 99%

“…Some work is currently being developed about EEM classification (e.g. Fleiter et al, 2012;Trianni et al, 2014), but in general, contributions are scarce.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

International study on energy end-use data among industrial SMEs (small and medium-sized enterprises) and energy end-use efficiency improvement opportunities

Thollander

Paramonova

Cornelis

et al. 2015

Journal of Cleaner Production

Self Cite

View full text Add to dashboard Cite

show abstract

“…With more and more emphasis on curbing energy consumption and the consequent greenhouse gas (GHG) emissions in modern societies, this study used statistical analysis to support housing downsizing (moving to a smaller dwelling) as a proposed method for reducing annual residential energy consumption (in MW-h). Downsizing of equipment (e.g., heaters and air conditioning units [6] and even automobile engines [7]) to save energy has already received earlier attention, whereas engineers should realize more the energy saving due to smaller living spaces and avoiding under-occupancy. The total sample size was N = 991 households which represent part of the 2011 Energy Follow-Up Survey (EFUS) by the British Department of Energy and Climate Change, and the 2011/2012 English Housing Survey (EHS).…”

Section: Second Study: Downsizing Homes For Reduced Energy Consumptionmentioning

confidence: 99%

Case Studies of Statistical Analysis in Engineering

Marzouk¹

2017

IJSDA

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Statistical analysis finds a wide range of applications in scientific research, management, finance, and engineering. In this article, we aim at shedding some light on the significance of two tools of statistical analysis, namely ANOVA and regression, in civil (including environmental), mechanical, and architectural engineering disciplines through a short survey of recent research studies that utilized these tools to reach important engineering models or rules of interest to engineers for design or development. The studies represent diverse areas of traffic planning, residential energy, indoor air quality, and high-speed machining. We briefly present some sample selection rules and analysis outcomes in these studies.

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Cost‐effectiveness analysis of energy efficiency measures in the Swiss chemical and pharmaceutical industry

Zuberi

Patel

2018

Int J Energy Res

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Summary Energy efficiency improvement is an effective way of reducing energy demand and CO2 emissions. Although the overall final energy savings potential in chemical industry has been estimated in a few countries, energy efficiency potentials by concrete measures applicable in the sector have been scarcely explored and their associated costs are hardly analyzed. In Switzerland, the production of chemicals and pharmaceuticals exceeds all other industrial sectors in terms of energy use and CO2 emissions, and it accounted for 22% of the total industry's overall final energy demand and 25% of the CO2 emissions related to non‐renewable energy sources in 2016. In this study, the economic potentials for energy efficiency improvement and CO2 emissions reduction in the Swiss chemical and pharmaceutical industry are investigated in the form of energy efficiency cost curves. The economic potential for final energy savings and CO2 abatement based on energy‐relevant investments is estimated at 15% and 22% of the sector's final energy use and fossil fuel‐related CO2 emissions in 2016, respectively. Measures related to process heat integration are expected to play a key role for final energy savings. The economic electricity savings potential by improving motor systems is estimated at 15% of the electricity demand by these systems in 2016. The size of economic potential of energy efficiency improvement across the sector decreases from 15% to 11% for 0.5 times lower final energy prices while the size increases insignificantly for 1.5 times higher final energy prices. The additional power generation potential based on Combined Heat and Power plants is estimated at 14 MW for 2016. This study is a contribution to the so far limited international literature on economic energy efficiency measures applicable in this heterogeneous sector and can support policy development. The results for specific costs of energy efficiency measures can also be adapted to other parts of the world by making suitable adjustments which in return may provide useful insights for decision makers to invest in economically viable clean energy solutions.

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A framework to characterize energy efficiency measures

Cited by 147 publications

References 68 publications

International study on energy end-use data among industrial SMEs (small and medium-sized enterprises) and energy end-use efficiency improvement opportunities

International study on energy end-use data among industrial SMEs (small and medium-sized enterprises) and energy end-use efficiency improvement opportunities

Case Studies of Statistical Analysis in Engineering

Cost‐effectiveness analysis of energy efficiency measures in the Swiss chemical and pharmaceutical industry

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