Abstract Machine learning and deep learning are subsets of Artificial Intelligence that have
revolutionized object detection and classification in images or videos. This technology plays …

The issue of power quality (PQ) has become increasingly critical in modern power systems
due to the growing integration of sensitive electronic devices, electric vehicles, and …

Electric power utilities must ensure a consistent and undisturbed supply of power, with the
voltage levels adhering to specified ranges. Any deviation from these supply specifications …

The transformation of traditional grid networks towards smart-grid and microgrid concepts
raises many critical issues, and quality in the power supply is one of the prominent ones that …

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 …

In the realm of electrical distribution, managing power quality is critical due to its significant
impact on infrastructure and customer satisfaction. Addressing issues such as voltage sags …

Power quality (PQ) disturbances, such as voltage sags, are significant issues that can lead
to damage in electrical equipment and system downtime. Detecting and classifying these …

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 …

The problem of Power Quality analysis is becoming crucial to ensuring the proper
functioning of complex systems and big plants. In this regard, it is essential to rapidly detect …

The challenges currently faced by network operators are difficult and complex. Presently,
various types of energy sources with random generation, energy storage units operating in …