This paper proposes a neural-network (NN)-based approach to nonintrusive harmonic
source identification. In this approach, NNs are trained to extract important features from the …

The pattern recognition approach to transient stability analysis (TSA) has been presented as
a promising tool for online application. This paper applies a recently introduced learning …

In this paper, a new hybrid intelligent system is proposed for transient stability prediction.
This intelligent system is composed of a preprocessor, an array of neural networks (NN) and …

In a smart grid, the main goals are to provide grid stability, improve power system
performance and security, and reduce operations, system maintenance, and planning costs …

Transient stability control of power systems is based on actions that are taken automatically
following a disturbance to ensure that the system remains in synchronism. Examples of such …

The stochastic fluctuation of renewable energy resources has significant impact on the
stability of the power system with renewable generations and results in change in stability …

The classical regression and Bayesian classification statistical techniques stand upon a
strict assumption that the underlying probability distribution is known. However, in real life …

This paper proposes a new probabilistic method for short-term load forecasting with the
Gaussian processes (GP). In recent years, the degree of uncertainty increases as the power …

In this study, a new transient stability prediction method is proposed. The measured rotor
angles of generators are first processed by a new non-linear transformation based on …

The paper addresses practical capabilities of artificial neural networks (ANNs) in developing
measurement-based continuous-time dynamic equivalents for power systems. Our method …