Fast methods for voltage stability analysis and control selection considering parameter uncertainties

• Autor(a) principal: Lucas Sales Neves
• Data de Publicação: 2022
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Biblioteca Digital de Teses e Dissertações da USP
• Texto Completo: https://doi.org/10.11606/T.18.2022.tde-27042022-162432

With the ongoing load increase in current power systems, voltage stability analysis has become an essential tool to ensure that a power system can withstand different loading variations. In this scenario, this work deals with parameter uncertainties and control selection in voltage stability analysis of power systems. The main contributions of this thesis are related to: • Modelling: – A new static power system model is proposed. The new model enables na unified analysis of different voltage instability mechanisms. Specifically, all static bifurcations are transformed into saddle-node bifurcations. – A new model to take parameter uncertainties into account is proposed, where parametric variations are represented by a Brownian motion and the uncertainty region is described by a cone. • Voltage stability margin computation: – A new method for contingency ranking is proposed. The proposed method is both fast and accurate in computing the contingency ranking, and is able to compute different bifurcation types. – A new method is proposed to compute the voltage stability margin. The method is robust to different parameter variation scenarios and is able to compute diferente bifurcation types. The method is also fast, with a execution time equivalent to a few continuation power flow computations.• Voltage stability margin control: A new method is proposed to select control actions which aim for increasing the voltage stability margin. The method takes uncertainties into account, and results show that proposed method is fast on selecting a small number of control actions that are sufficient to increase the voltage stability margin to a predefined value.All propositions were tested by means of several simulations on different test-systems. Implementation results corroborate that the proposed methods are fast and robust, with potential for online voltage stability assessment of large-scale power systems.