Modelling sustainable energy and the implications for policy

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dc.contributor.advisorÓ Gallachóir, Brian P.en
dc.contributor.advisorCurtis, Johnen
dc.contributor.authorClancy, John Matthew
dc.contributor.funderSustainable Energy Authority of Irelanden
dc.date.accessioned2019-01-21T14:00:52Z
dc.date.available2019-01-21T14:00:52Z
dc.date.issued2018
dc.date.submitted2018
dc.description.abstractThe Paris Agreement sets out the collective ambition of the world’s nations to prevent dangerous climate change. However, at national level across the world, there is a gap between action and the required rate of effort. Long-term models show technology pathways but governments must act to realise them. Long-term pathways are often based on a single aim – achieving a level of CO2 reduction at least cost. Yet governments have wider objectives beyond climate mitigation. Economic competitiveness, wellbeing of citizens and employment also feature. This thesis approaches the modelling of sustainable energy from a policymaker’s perspective. The aim is to improve the evidence base and inform policy development. Showing citizens the impact of current policy helps governments to bring forth further support. These assessments can be difficult to implement. The first part of this thesis examines the emissions impact of existing renewable electricity policy. Several methods have been used to explore this question. This thesis applies a comprehensive method: an ex-post power system optimisation model. The purpose is to address questions raised about the effectiveness of wind power in reducing CO2 emissions in Ireland. Using 2012 data, the modelling shows that renewable electricity saved 0.43 – 0.46 tCO2/MWh. Power system modelling is also employed to examine the impact of using waste heat from power generation in heat networks. Linking heat and electricity sectors in this way affects both. The findings show that using waste heat is competitive and results in CO2 savings in both sectors. The second part of the thesis focuses on the challenge of developing coherent supports for bioenergy. A decision support tool that uses mixed methods simulates policy options in Ireland. The model incorporates least-cost use of bioenergy resources and a detailed representation of consumer decision-making in the heat sector. The results show that using domestic biomass resources in the power sector slows the uptake of renewable heat and hence diminishes the benefits of renewable heat policy. This has negative implications for national climate targets. Many decarbonisation pathways need consumers to make sustainable energy decisions. Part three applies empirical methods to representative data from Ireland’s commercial sector. Logistic regressions identify key factors that can help to target policy on the barriers faced by consumers. Tenants in business units that do not make investment decisions locally are 16 times less likely to investigate energy options. Other factors such as the approach to budgeting and knowledge of the building floor area are also important. The primary contribution of this thesis is to provide evidence-based insights for policymaking in Ireland and beyond. The thesis also makes contributions to advancing modelling methods.en
dc.description.statusNot peer revieweden
dc.description.versionAccepted Version
dc.format.mimetypeapplication/pdfen
dc.identifier.citationClancy, J. M. 2018. Modelling sustainable energy and the implications for policy. PhD Thesis, University College Cork.en
dc.identifier.endpage223en
dc.identifier.urihttps://hdl.handle.net/10468/7331
dc.language.isoenen
dc.publisherUniversity College Corken
dc.rights© 2018, Matthew Clancy.en
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/en
dc.subjectEnergy policyen
dc.subjectEnergy modellingen
dc.subjectCO2en
dc.subjectWinden
dc.subjectBioenergyen
dc.subjectDistrict heatingen
dc.subjectConsumer choiceen
dc.thesis.opt-outfalse
dc.titleModelling sustainable energy and the implications for policyen
dc.typeDoctoral thesisen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnamePhDen
ucc.workflow.supervisorb.ogallachoir@ucc.ie
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