Improving the quantitative evaluation of energy efficiency

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dc.check.embargoformatEmbargo not applicable (If you have not submitted an e-thesis or do not want to request an embargo)en
dc.check.infoNot applicableen
dc.check.opt-outYesen
dc.check.reasonNot applicableen
dc.check.typeNo Embargo Required
dc.contributor.advisorO'Gallachoir, Brianen
dc.contributor.authorDennehy, Emer Regina
dc.date.accessioned2020-01-24T11:47:40Z
dc.date.available2020-01-24T11:47:40Z
dc.date.issued2019
dc.date.submitted2019
dc.description.abstractThis thesis considers the adage “what gets measured gets done” and postulates that understanding and improving how energy efficiency is measured can contribute to maximise the contribution of energy efficiency and assist in meeting energy and climate targets. This thesis addresses the research question of how to optimally quantitatively evaluate energy efficiency. The impact of fuel switching, different levels of data aggregation, and data availability and fluctuations on measuring energy efficiency is established through real-world ex-post analysis. The analysis demonstrates use of readily available data sources from existing administrative databases, such as energy balances, to achieve timelier, accurate, and reliable estimates of energy efficiency. The thesis is predominately a mathematical examination of Index Decomposition Analysis (IDA) methods, with a particular a focus on the Logarithmic Mean Divisia Index 1 (LMDI-1) methodology. Often perceived as difficult to understand, mathematical proofs and heuristics are included to aid with understanding, application and interpretation of the LMDI-I methodology. The thesis concludes that general choices of how a decomposition analysis method is applied may be more significant than the choice of IDA methodology. In particular, the choice of energy-efficiency indicator or metric and the level of disaggregation of the analysis, with disaggregation by fuel type or energy source key to improve estimates of the contribution of energy efficiency. Nevertheless, unique properties of the LMDI-I methodology contribute to making that the IDA methodology of choice. To prevent unrealistic expectations of what energy efficiency can achieve, the author also advocates the inclusion of as many explanatory factors as possible in IDA, to contextualise the contribution of energy efficiency in energy systems.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationDennehy, E. R. 2019. Improving the quantitative evaluation of energy efficiency. PhD Thesis, University College Cork.en
dc.identifier.urihttps://hdl.handle.net/10468/9573
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2019, Emer Regina Dennehy.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectLMDIen
dc.subjectFuel or technology switchingen
dc.subjectEnergy efficiencyen
dc.subjectDecomposition analysisen
dc.subjectLogarithmic mean divisia indexen
dc.subjectMonotonicityen
dc.subjectExergyen
dc.subjectExergy efficiencyen
dc.subjectPassenger carsen
dc.subjectOn-road consumptionen
dc.subjectRetrofiten
dc.thesis.opt-outtrue
dc.titleImproving the quantitative evaluation of energy efficiencyen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhDen
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