Power quality disturbance detection and classification using signal processing and soft computing techniques: A comprehensive review
M Mishra - International transactions on electrical energy …, 2019 - Wiley Online Library
Power quality (PQ) studies have gained huge attention from the academics and the industry
over the past three decades. The main objective of this article is to provide a comprehensive …
over the past three decades. The main objective of this article is to provide a comprehensive …
Wind pattern recognition and reference wind mast data correlations with NWP for improved wind-electric power forecasts
A new statistical approach has been proposed for improved short-term wind-electric power
forecasts of wind power plants (WPPs) based on a new wind-pattern-recognition technique …
forecasts of wind power plants (WPPs) based on a new wind-pattern-recognition technique …
Optimal feature selection for classification of the power quality events using wavelet transform and least squares support vector machines
In this paper, a new optimal feature selection based power quality event recognition system
is proposed for the classification of power quality events. While Apriori algorithm is capable …
is proposed for the classification of power quality events. While Apriori algorithm is capable …
Towards automated statistical partial discharge source classification using pattern recognition techniques
H Janani, B Kordi - High Voltage, 2018 - Wiley Online Library
This study presents a comprehensive review of the automated classification in partial
discharge (PD) source identification and probabilistic interpretation of the classification …
discharge (PD) source identification and probabilistic interpretation of the classification …
Multistage wind-electric power forecast by using a combination of advanced statistical methods
A multistage advanced statistical method has been proposed for the real-time wind-electric
power generation forecast of wind power plants (WPPs) based on a combination of artificial …
power generation forecast of wind power plants (WPPs) based on a combination of artificial …
Automatic recognition system of underlying causes of power quality disturbances based on S-Transform and Extreme Learning Machine
In this paper, a new S-Transform and Extreme Learning Machine (ST–ELM)-based event
recognition approach for the purpose of classifying power quality (PQ) event signals …
recognition approach for the purpose of classifying power quality (PQ) event signals …
Automatic classification of power quality events and disturbances using wavelet transform and support vector machines
In this study, a new approach for the classification of power quality events is presented. Also,
power quality disturbances, which occur in each phase of the power system after a fault …
power quality disturbances, which occur in each phase of the power system after a fault …
Classification of power quality events using deep learning on event images
In this paper, a new method for the classification of power quality (PQ) events of the
electricity networks based on deep learning approach is presented. In contrast with the …
electricity networks based on deep learning approach is presented. In contrast with the …
Real-time implementation of optimized power quality events classifier
The future's smart grid consists of an increasing number of dispersed energy generation and
consumption devices. Due to its complexity, the energy sector yields the development of …
consumption devices. Due to its complexity, the energy sector yields the development of …
Using smart meters data for energy management operations and power quality monitoring in a microgrid
EJ Palacios-Garcia, E Rodriguez-Diaz… - 2017 IEEE 26th …, 2017 - ieeexplore.ieee.org
Smart metering devices have become an essential part in the development of the current
electrical network toward the paradigm of Smart Grid. These meters present in most of the …
electrical network toward the paradigm of Smart Grid. These meters present in most of the …