Power Systems Disturbance Classification Using Modular Neural Networks with Multilayers Experts

Other types of classification algorithm include applying genetic based optimization technique[7], randomly optimized neural network combined with discrete wavelet transform and fuzzy logic[8] and Gabor-Wigner transform[9] for detection

This paper presents classification and characterization of typical power quality disturbancessag, swell, interruption and harmonics employing S-transform analysis combined with modular neural network. S-transform is used to extract various features of disturbance signal as it has excellent time-frequency resolution characteristics and ability to detect disturbance correctly even in the presence...

Decentralized Interaction Estimators in Large Scale Power Systems with Neural Networks.

A Direct Power Feeding System for AC Railway Networks Using Modular Multilevel Converter

Abstract Traditional railway power supply systems impose substantial power quality problems (PQ) on the utility network, such as unbalance, harmonics and a large amount of reactive power. This paper proposes a topology based on three-phase to single-phase modular multilevel converters (MMC) to obviate these problems. The MMC based traction substations (TSS) are connected directly to the utili...

DISTURBANCE REJECTION IN NONLINEAR SYSTEMS USING NEURO-FUZZY MODEL

The problem of disturbance rejection in the control of nonlinear systems with additive disturbance generated by some unforced nonlinear systems, was formulated and solved by {itshape Mukhopadhyay} and {itshape Narendra}, they applied the idea of increasing the order of the system, using neural networks the model of multilayer perceptron on several systems of varying complexity, so the objective...

Application of ANN Technique for Interconnected Power System Load Frequency Control (RESEARCH NOTE)

This paper describes an application of Artificial Neural Networks (ANN) to Load Frequency Control (LFC) of nonlinear power systems. Power systems, such as other industrial processes, have parametric uncertainties that for controller design had to take the uncertainties in to account. For this reason, in the design of LFC controller the idea of robust control theories are being used. To improve ...