Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.785676
Title: Identification of influential parameters affecting power system voltage and angular stability analysis
Author: Qi, Buyang
ISNI:       0000 0004 7971 1728
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2019
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Abstract:
This thesis investigates the effects of system uncertain parameters on power system voltage and angular stability analysis in network with Renewable Energy Sources. The main outcome of this research is the fast and accurate ranking of the system parameters based on their influence on power system voltage and angular stability. The planning and operation of modern power systems have changed significantly compared to conventional power systems due to the addition of new types of load devices and renewable energy sources. These new technologies exhibit significant temporal and spatial uncertainties in generating and loading profiles within power systems and introduce additional level of uncertainty in network operation. This research proposes a probabilistic analysis approach for the evaluation of the effect of uncertain parameters on power system voltage and angular stability. The Morris Screening sensitivity analysis method coupled with a multivariate Gaussian copula to account for parameter correlations is used for the assessment of the importance of correlation modelling between uncertain parameters. This research for the first time combines and validates the identification of critical parameters affecting system stability in general by using sensitivity analysis method. It also for the first time establishes the importance of modelling parameter correlation by using Copula theory. The approach proposed in this study facilitates efficient identification of important system parameters that needs to be accurately modelled for reliable system stability studies and such ensures cost effective use of human and financial resources by system operators.
Supervisor: Milanovic, Jovica ; Preece, Robin Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.785676  DOI: Not available
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