Future energy demand and increasing carbon emission requires an alternative source of energy. In recent few years, Use of DFIG based wind farm increased tremendously, thus effect of wind penetration on small signal stability of existing multi machine system need to be analysed. In This paper effect of penetration of wind turbine with DFIG on stability performance of the IEEE 9 bus and 39 bus sy...

The fractional order systems has been used successfully to model in frequency domain the development of induced currents in electric machines, especially in the dampers or massive parts of large synchronous machines. The objective of this work consists in extending the field of application of fractional order models for small signal stability studies of an electrical network.

Two phenomena can produce chattering: switching of input control signal and the large amplitude of this switching (switching gain). To remove the switching of input control signal, dynamic sliding mode control (DSMC) is used. In DSMC switching is removed due to the integrator which is placed before the plant. However, in DSMC the augmented system (system plus the integrator) is one dimension bi...

A large-signal average model for the controlled on-time boost power-factor-correction (PFC) circuit is developed and subsequently linearized, resulting in a small-signal model for the PFC circuit. AC analyses are performed using the small-signal model, revealing new results on the small-signal dynamics of the PFC circuit. The analysis results and model predictions are confirmed with experimenta...

abstract A new methodology for developing average models of resonant converters is presented and verified against cycle by cycle simulation, showing excellent agreement. The proposed modeling approach applies the concept of R ac () t which represent the instantenous effective load of the resonant network. The model can be used as is to run steady state (DC), large signal (transient) and small s...

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...

The two prevalent s-domain models for current-mode control, the continuous-time model and the unified model, exhibit noticeable differences in their small-signal predictions and therefore have become the subject of comparisons and clarifications. The current letter presents an alternative way of deriving the unified model, thereby providing an additional guide for assessing the validity of the ...

in recent decades, seizure prediction caused a lot of research in both signal processing and neuroscience field. the researches tried to enhance the conventional seizure prediction algorithms such that rate of the false alarms be appropriately small so that seizures can be predicted according to clinical standards. up to now none of the proposed algorithms have been sufficiently adequate. in th...

In analyzing a signal, especially a non-stationary signal, it is often necessary the desired signal to be segmented into small epochs. Segmentation can be performed by splitting the signal at time instances where signal amplitude or frequency change. In this paper, the signal is initially decomposed into signals with different frequency bands using wavelet transform. Then, fractal dimension of ...

in analyzing a signal, especially a non-stationary signal, it is often necessarythe desired signal to be segmented into small epochs. segmentation can beperformed by splitting the signal at time instances where signal amplitude orfrequency change. in this paper, the signal is initially decomposed into signals withdifferent frequency bands using wavelet transform. then, fractal dimension of thed...