Queen's University Belfast
Power quality impacts of the low carbon evolution within modern distribution networks
Abstract
dc:description.abstractThis thesis explores the contemporary and future power quality context of low carbon technologies within the distribution networks of the United Kingdom. The work was conducted in parallel with a series of research activities undertaken as part of Ofgem’s Low Carbon Network Fund project, entitled "Smart Street".<br/><br/>The power quality behaviours of a selection of modern lighting technologies and residential photovoltaic systems were the subject of a series of empirical investigations. From this a collection of static load models are composed, each specified in polynomial form. This process includes the development of a novel approach for characterising harmonic current phasors, expressed in cartesian form, as functions of a modulating parameter, either supply voltage or appliance load factor.<br/><br/>The method is subsequently proven to incorporate the concept of phase angle diversity within associated, aggregate load model instances. Crucially, this feature serves to embody the natural, diversity led attenuation of harmonic current flows in practical power systems. By contrast, the same effect is consistently found to be neglected for comparative examples in literature.<br/><br/>The aforementioned load model traits are employed in the time series, harmonic power flow simulation of representative demand profiles. This analysis is conducted upon a selection of power system models of real world, distribution networks. For a mix of present day and future envisaged, demand profile mixes, several of the technologies trialled within the Smart Street project are observed to impart alleviative, power quality benefits to distribution network customers. This includes the installation of on-load tap changing transformers, as implemented at low voltage substations, the deployment of conservation voltage reduction and the application of meshing between adjacent low voltage feeders.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy
- Level dc:type.qualificationlevel
- Doctoral Thesis
- Grantor dc:publisher.institution
- Queen's University Belfast
- Year dc:date.issued
- 2020
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- McLorn, Gareth
- Advisors dc:contributor.advisor
-
- McLoone, Sean
- Liu, Xueqin
Subjects
dc:subject × 6Rights
- Language dc:language
- eng
Identifiers
dc:identifier.*- Identifier
- oai:pure.qub.ac.uk/portal:studenttheses/18f2a908-821d-4731-ad80-ca670ef45dcd
- OAI identifier oai:identifier
- oai:pure.qub.ac.uk/portal:studenttheses/18f2a908-821d-4731-ad80-ca670ef45dcd