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dc.contributor.authorTu, Tu
dc.date.accessioned2020-07-30
dc.date.available2020-07-30
dc.date.submitted2020-01-01en_AU
dc.identifier.urihttps://hdl.handle.net/2123/22969
dc.description.abstractThe utilization of renewable energy systems and battery storage is a promising solution for remote area electrification. In particular, the integration of renewable energy systems and battery storage units are commonly used to establish discrete electricity generation and stand-alone micro-grids, due to their commercial availability and well-studied electrical behaviour. However, being a highly feasible solution for micro-grid planning, the underlying challenging to find the optimal balance between economics and amenity is often overlooked. The work presented in this thesis aims to use real-world projects to explore the challenges of optimal micro-grid component sizing, by providing an understanding of the key challenges in the process – the techno-economic balance. Potential solutions are provided after identifying the problem, including the utilization of existing infrastructural hardware, incorporation of novel demand management strategies, the establishment of poly-generation to improve generation and storage diversity and reduce the problem of intermittency. It is modeled and shown in this study that the demand management approach of non-critical load deferring could substantially improve network availability in a stand-alone micro-grid, with its effectiveness comparable to loss of electricity – a conventional demand management approach that is significantly more disruptive. A real-world case study project in Bruny Island, Australia is constructed as a mixed integer linear programming model to validate research concepts and provide sensitivity analysis simulations to proposed micro-grid system configurations. Up-to-date utility tariffs and micro-grid component pricings are adopted to reflect both the infrastructural and social environment of the studied area, followed by a series of scenarios configured to map out the potential infrastructural transition of Bruny Island. Furthermore, after the Bruny Island base scenario is established in the model, desalination, electric vehicles and vehicle-to-grid are introduced into the model as methods of increasing generation and demand diversity. It is shown in the modeling results, although each technology intervention contributes in improving the economics of the micro-grid, their impacts may differ due to the local climate conditions and social mix. From the analysis on the model results, this study quantifies the importance of a comprehensive model that utilizes complete cycle, fine-resolution input data, instead of the over-generalized approach. Additionally, this study attempts to provide a novel design mindset for micro-grid infrastructural transitions, to maximize the benefits of existing hardware, reduce interruption and minimize system cost.en_AU
dc.language.isoenen_AU
dc.publisherUniversity of Sydneyen_AU
dc.subjectMILPen_AU
dc.subjectBattery Storageen_AU
dc.subjectElectric Vehicleen_AU
dc.subjectMicro-griden_AU
dc.subjectrenewablesen_AU
dc.titleThe rise of renewable energy and battery storage based micro-grids: challenges in techno-economic balance and infrastructural transition, modeled with a real-world case-studyen_AU
dc.typeThesis
dc.description.disclaimerAccess is restricted to staff and students of the University of Sydney . UniKey credentials are required. Non university access may be obtained by visiting the University of Sydney Library.en_AU
dc.type.thesisDoctor of Philosophyen_AU
dc.rights.otherThe author retains copyright of this thesis. It may only be used for the purposes of research and study. It must not be used for any other purposes and may not be transmitted or shared with others without prior permission.en_AU
usyd.facultySeS faculties schools::Faculty of Engineering::School of Chemical and Biomolecular Engineeringen_AU
usyd.degreeDoctor of Philosophy Ph.D.en_AU
usyd.awardinginstThe University of Sydneyen_AU
usyd.advisorVASSALLO, ANTHONY
usyd.advisorABBAS, ALI


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