The rising integration of offshore wind energy into the electric grid provides remarkable
opportunities in terms of environmental sustainability and cost efficiency. However, it poses …

The electric machines are the elements most used at an industry level, and they represent
the major power consumption of the productive processes. Particularly speaking, among all …

As a result of the widespread use of power electronic equipment and the increase in
consumption, the importance of effective energy policies and the smart grid begins to …

This work proposes an innovative approach to detect, segment and classify voltage sags
according to their causes. To detect and segment, Independent Component Analysis is …

With the advancement of technology, the demand for high quality and sustainable electrical
energy has been increased due to the widespread use of electrical devices in our daily lives …

Monitoring electrical power quality has become a priority in the industrial sector background:
avoiding unwanted effects that affect the whole performance at industrial facilities is an aim …

In this paper, a deep learning approach for power quality monitoring in systems with
distributed generation sources is presented. The proposed method focuses in the multi …

The rapid growth of energy storage scale in power systems has posed higher demands on
the monitoring and classification of power quality disturbances (PQDs). Therefore, a method …

This study proposes SVM based Random Subspace (RS) ensemble classifier to
discriminate different Power Quality Events (PQEs) in a photovoltaic (PV) connected …

In this paper, a long short-term memory (LSTM)-based method with a multi-input tensor
approach is used for the classification of events that affect the power quality (PQ) in power …