Electromechanical oscillations are an inherent property of power systems and the damping of the oscillations is the limiting factor for the transmission capacity of certain transmission corridors. In the most severe situations, unstable oscillations may lead to blackouts. Thus, it is important to monitor the characteristics of the oscillations. The oscillations can be monitored for example by using phasor measurement units (PMU). The development of wide area monitoring systems (WAMS) consisting of several PMUs has enabled the use of multiple synchronized measurement signals received from several locations in the power system to be used for the monitoring and analysis of the oscillatory modes. This thesis presents four new multivariate methods (i.e. use several measurements from different locations of the grid) for the monitoring of the electromechanical modes. The methods are able to continuously identify electromechanical modes using ambient oscillations, which are mainly excited by load variations and are constantly present in power systems. The performance, characteristics and limitations of the methods are studied using simulated data as well as real measured data. This thesis also presents comparisons of different modal identification methods and illustrates additional analysis tools that can be used to support the modal identification in real power systems. This thesis shows that the proposed methods are functional for monitoring of electromechanical modes. Due to certain limitations in modal identification methods, the thesis also highlights the need of using additional tools, such as spectral analyses, which may significantly help the interpretation of modal identification results. The methods presented in this thesis can be used as building blocks for transmission system operators (TSO) to create functional applications for real-time and offline modal analysis of power systems. Consequently, the information given by the methods may be used to improve the security and reliability of power systems.
|Translated title of the contribution||Menetelmiä sähkömekaanisen heilahtelun valvontaan voimajärjestelmässä|
|Publication status||Published - 2017|
|MoE publication type||G5 Doctoral dissertation (article)|
- ambient oscillation
- electromechanical oscillation
- modal identiﬁcation
- power system dynamics