Wavelet-based arcing signal source localization algorithm using a compact multi-square microstrip antenna.

Ensuring power system safety involves effective arc fault detection and localization. Existing devices struggle to differentiate between normal and abnormal conditions, especially in confined spaces, posing precision challenges. Strategically placing antennas around the arc helps detect electromagnetic radiation, even in limited areas, enabling valuable data collection for real-time monitoring.

A Novel Polyester Varnish Nanocomposites for Electrical Machines with Improved Thermal and Dielectric Properties Using Functionalized TiO Nanoparticles.

Recently, there has been a growing interest in polymer insulating materials that incorporate nanoscale inorganic additives, as they have shown significantly improved dielectric, thermal, and mechanical properties, making them highly suitable for application in high-voltage insulating materials for electrical machines. This study aims to improve the dielectric and thermal properties of a commercial polyester varnish by incorporating different concentrations of titanium dioxide nanoparticles (TiO) with proper surface functionalization. Permafil 9637 dipping varnish is the varnish used for this investigation, and vinyl silane is the coupling agent used in the surface functionalization of TiO nanoparticles.

Condition Assessment of Natural Ester-Mineral Oil Mixture Due to Transformer Retrofilling via Sensing Dielectric Properties.

Mineral oil (MO) is the most popular insulating liquid that is used as an insulating and cooling medium in electrical power transformers. Indeed, for green energy and environmental protection requirements, many researchers introduced other oil types to study the various characteristics of alternative insulating oils using advanced diagnostic tools. In this regard, natural ester oil (NEO) can be considered an attractive substitute for MO.

Influence of Mineral Oil-Based Nanofluids on the Temperature Distribution and Generated Heat Energy Inside Minimum Oil Circuit Breaker in Making Process.

The enhancement of the thermal properties of insulating oils has positively reflected on the performance of the electrical equipment that contains these oils. Nanomaterial science plays an influential role in enhancing the different properties of liquids, especially insulating oils. Although a minimum oil circuit breaker (MOCB) is one of the oldest circuit breakers in the electrical network, improving the insulating oil properties develops its performance to overcome some of its troubles.

Towards Precise Interpretation of Oil Transformers via Novel Combined Techniques Based on DGA and Partial Discharge Sensors.

Power transformers are considered important and expensive items in electrical power networks. In this regard, the early discovery of potential faults in transformers considering datasets collected from diverse sensors can guarantee the continuous operation of electrical systems. Indeed, the discontinuity of these transformers is expensive and can lead to excessive economic losses for the power utilities.

Proposed ANFIS Based Approach for Fault Tracking, Detection, Clearing and Rearrangement for Photovoltaic System.

In the last few decades, photovoltaics have contributed deeply to electric power networks due to their economic and technical benefits. Typically, photovoltaic systems are widely used and implemented in many fields like electric vehicles, homes, and satellites. One of the biggest problems that face the relatability and stability of the electrical power system is the loss of one of the photovoltaic modules.

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic.

This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency. Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system. In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units.

Deep Learning-Based Industry 4.0 and Internet of Things towards Effective Energy Management for Smart Buildings.

Worldwide, energy consumption and saving represent the main challenges for all sectors, most importantly in industrial and domestic sectors. The internet of things (IoT) is a new technology that establishes the core of Industry 4.0.

Reliable Industry 4.0 Based on Machine Learning and IoT for Analyzing, Monitoring, and Securing Smart Meters.

The modern control infrastructure that manages and monitors the communication between the smart machines represents the most effective way to increase the efficiency of the industrial environment, such as smart grids. The cyber-physical systems utilize the embedded software and internet to connect and control the smart machines that are addressed by the internet of things (IoT). These cyber-physical systems are the basis of the fourth industrial revolution which is indexed by industry 4.

Recent Advances in Polymer Nanocomposites Based on Polyethylene and Polyvinylchloride for Power Cables.

Polymer nanocomposites used in underground cables have been of great interest to researchers over the past 10 years. Their preparation and the dispersion of the nanoparticles through the polymer host matrix are the key factors leading to their enhanced dielectric properties. Their important dielectric properties are breakdown strength, permittivity, conductivity, dielectric loss, space charge accumulation, tracking, and erosion, and partial discharge.