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The general focus of this study is to design a multilevel deep learning model that provides big data analytics and emergency management knowledge. A big data covariance analysis approach has been used to find multilevel representations of data based on prior knowledge from large scale power systems. For purpose of meeting requirements of incremental knowledge discovery, an adaptive regression algorithm...
A simple eigenvalue representation result that justifies the celebrated phase compensation principle, from algebraic point of view, is presented. The result generalizes phase compensation principle, it appears as a stability criterion, applicable to multi-machine systems. It allows us to find compensation angle for machines individually. Furthermore, the problem of gain coordination is also reduced...
Reactive power plays a crucial role in power system operation and voltage management. However reactive power issues have rarely been considered in reliability evaluation of power systems. This paper investigates the effect of reactive power on reliability of the 220 kV Taiyuan Power System in Shanxi Province of China. Reactive power shortage and the associated voltage violations due to the failures...
A power system stabiliser (PSS) design method, which aims at enhancing the damping of multiple electromechanical modes in a multi-machine system over a large and pre-specified set of operating conditions, is introduced. With the assumption of normal distribution, the statistical nature of the eigenvalues corresponding to different operating conditions is described by their expectations and variances...
Power system stabilizer (PSS) is one the most economical and effective controllers to enhance the power system damping. Under multioperating conditions, the probabilistic PSS (PPSS) design problem can be formulated as a parameter optimization problem with probabilistic eigenanalysis included and the statistical nature of the eigenvalues is described by their expectations and variances. This paper...
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