Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.753604
Title: A statistical assessment tool for electricity distribution networks
Author: Abeysinghe, Sathsara
ISNI:       0000 0004 7426 6944
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2018
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Abstract:
With a large penetration of low carbon technologies (LCTs) (E.g. solar photovoltaics, wind turbines and electric vehicles) at medium voltage and low voltage levels, electricity distribution networks (EDNs) are undergoing rapid changes. Research has been carried out to analyse and quantify the impacts of LCTs on EDNs. Most of these previous studies are based on either real or synthetic network samples. The results and conclusions derived from these studies have limited applicability to other networks, thus making it difficult to arrive at generalised and robust conclusions on the impact of LCTs on EDNs. One of the main reasons for using a case study or synthetic networks in research is limited accessibility to real-world network data. To bridge this research gap, the rationale and the development of a network modelling tool that can generate random-realistic representations of different types (sub-urban/urban) of EDNs in aiding statistical analysis of the power networks is presented in this thesis. The ability to generate ensembles of statistically-similar distribution networks is one of the key properties of the proposed tool. Statistically-similar distribution networks are a set networks with a similar set of topological and electrical properties as defined by the user with some given values or ranges of values. As part of this thesis four key contributions are presented. (i) An investigation of the topological properties of real-world EDNs: The key topological properties that characterise different types of EDNs were identified and quantified. A novel depth dependent approach was developed to investigate the network topologies. (ii) An investigation of electrical properties of real-world EDNs: The key electrical properties that characterise different types of EDNs were identified and quantified. A novel depth dependent approach was developed to investigate the electrical properties of EDNs. (iii) Development of a statistically-similar networks generator (SSNG): A SSNG was developed as a data driven model. Real-world network properties as characterised by the previous topological and electrical investigations and the corresponding network planning and design guidelines were used in the development of the SSNG. (iv) The application of the SSNG to analyse the impacts of soft open points (SOPs) on EDNs: A statistical analysis of the impact of Soft Open Points (SOPs) on a set of statistical-similar EDNs with variable distributed generation penetration was presented. The developed SSNG has been validated through a statistical analysis of the impact of SOPs, and the results showed that the SSNG is able to provide robust and generalised conclusions on distribution network studies.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.753604  DOI: Not available
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