• Yue Wang

Student thesis: Phd


Modern power networks are characterised by, among others, the following two features: a) Large amounts of low carbon technologies (LCTs) have been connected to both transmission and distribution networks; and b) In mature systems, power components are quite old and their ageing needs to be considered. LCTs have introduced new uncertainties and consequently operational issues in transmission networks. One important aspect, which needs to be addressed both in planning and operation, is the correlation between uncertain phenomena, such as wind speed, load fluctuations, etc. On the other hand, ageing of power system components can significantly affect network reliability performance, which, in turn, can have a negative impact on the asset “health”. In this research, sequential Monte Carlo simulation is developed to analyse operation and reliability of transmission networks. The above-mentioned phenomena, correlation between stochastic processes and asset ageing, are modelled and integrated into the sequential Monte Carlo simulation procedure. The correlation is modelled using Nataf transformation in conjunction with Cholesky decomposition and the technique is applied to both wind power and load since correlation between them has a significant impact on transmission networks. Asset ageing condition is also integrated into the SMC algorithm. The probabilistic expansion planning methodology under development shall model both component reinforcement and replacement. In the UK, transmission and distribution companies use methodologies for asset replacement based on asset Health Indices (HIs) which are used to describe asset conditions. In this research, two Monte Carlo procedures are developed to model the reliability of individual component. The first is deterministic approach, which is developed from the UK guide for distribution companies “DNO Common Network Asset Indices Methodology”. The second is a proposed probabilistic approach, which makes use of proportional hazards models and Kijima II virtual age model. The outputs for these two approaches are system-wide and nodal reliability indices, as well as asset interventions and asset profiles. The proposed probabilistic HI methodology is tested on IEEE RTS-96, and then compared to the deterministic HI method. Advantages of the transition to any HI approach are finally pointed out.
Date of Award1 Aug 2023
Original languageEnglish
Awarding Institution
  • The University of Manchester
SupervisorJovica Milanovic (Supervisor) & Victor Levi (Supervisor)

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