This paper presents a novel approach to detect and classify the power quality disturbance
(PQD) signals based on singular spectrum analysis (SSA), curvelet transform (CT) and deep …

The excessive use of power semiconductor devices in a grid utility increases the malfunction
of the control system, produces power quality disturbances (PQDs) and reduces the …

An important challenge for our society is the transformation of traditional power systems to a
decentralized model based on renewable energy sources. In this new scenario, advanced …

The aim of this paper is to investigate the power quality analysis by using 2D discrete
orthonormal S-transform, machine learning and multi-objective evolutionary algorithms. The …

In this paper, a new generation Internet-based Power Quality Monitoring System (IPQMS)
that transmits real-time power quality (PQ) data over the internet has been developed. The …

Power Quality (PQ) is becoming more and more important day by day in the electric network.
Signal processing, pattern recognition and machine learning are increasingly being studied …

Power quality disturbances (PQDs) have major challenges in embedded generation
systems, renewable energy networks, and HVDC/HVAC electrical power transmission …

This article presents an efficient method for power quality events (PQEs) detection and
classification based on Curvelet transform (CT) and optimized extreme learning machine …

Remote sensing image technology is of great significance for dynamic management and
monitoring of ground buildings. In order to improve the data fusion ability of remote sensing …

In terms of generation and consumption, complex power grids can transform a traditional
power system to a distributed one. This new paradigm suggests better monitoring and …