Hossam E. Mostafa

An Intelligent Wide Area Synchrophasor Based System for Predicting and Mitigating Transient Instabilities

Increasing expansion of power systems and grids are accompanied nowadays by innovation in smart grid solutions to maintain systems stability. This paper proposes an intelligent wide area synchrophasor based system (IWAS) for predicting and mitigating transient instabilities. The IWAS incorporates artificial neural networks (ANN) for transient stability prediction. The ANN makes use of the advent of phasor measurements units (PMU) for real-time prediction. Coherent groups of generators-which swing together-is identified through an algorithm based on PMU measurements. A remedial action scheme (RAS) is applied to counteract the system instability by splitting the system into islands and initiate under frequency load shedding actions. The potential of the proposed approach is tested using New England 39 bus system.

Wide area transient stability prediction using on-line Artificial Neural Networks

This paper proposes a real-time wide area protection system which incorporates artificial neural networks (ANN) for transient stability prediction. The ANN makes use of the advent of phasor measurements units (PMU) for real-time prediction. Rate of change of bus voltages and angles for six cycles after fault tripping and/or clearing is used to train a two layers ANN. Coherent groups of generators which swing together is identified through an algorithm based on PMU measurements. A remedial action scheme (RAS) is applied to counteract the system instability by splitting the system into islands and initiate under-frequency load shedding actions. The potential of the proposed approach is tested using New England 39-bus system.

A wide area synchrophasor based ANN transient stability predictor for the Egyptian Power System

This paper proposes an Artificial Neural Networks (ANN) based technique for transient stability prediction. The ANN makes use of the advent of Phasor Measurements Units (PMU) for real-time prediction. Rate of change of bus voltages and angles is used to train a two layers ANN. Potential of the proposed approach is tested using the Egyptian Power System (EPS) as a study system.

Evaluation of current transformer performance in the presence of remnant flux and harmonics

This paper studies and evaluates the effect of current transformer (CT) distortion parameters on its performance using various secondary current calculation methods according to IEC 44–1 & 44–6 like: magnitude (ratio) error, peak instantaneous error, phase error and composite error. These parameters include: multiple short circuit level (Isc/IR), secondary burden value & type, DC component (X/R ratio & fault inception angle), remanent factor (Kr) and both external & internal harmonics.