Uncertainty Modelling for Power System Analysis

UoM administered thesis: Master's Thesis


Modern power systems are experiencing increasingly rapid development in many regions all over the world. As many facilities and renewable resources are being introduced to the network, system stability is becoming vulnerable of uncertainties, whilst operating at the margin of security. However, classis deterministic methods had been found to be insufficient for the network in assessing the system stability. Hence it is computationally essential to suggest effective probabilistic approaches to investigate power system uncertainties.

This project explores and examines the utilisation of probabilistic small signals stability assessment (PSSSA) with uncertainties in power system. The uncertainties lead to changing in the damping of critical eigenvalue of modes. An efficient point estimate method has been proposed and evaluated for effective simulation of deviations in critical eigenvalues, in the form of three diverse variants. Meanwhile, the uncertainties are clarified into different levels to determine the power of uncertainties to variations. All technical schemes are in comparison with each other and with the numerical Monte Carlo method, for assessing precision and effectiveness.


Original languageEnglish
Award date2015