In modern power systems, condition based monitoring and diagnosis is essential to ensure the effective and reliable operation of different high voltage equipment (HVE). Compared to other monitoring techniques, partial discharges (PD) measurement is considered as a key method for assessing the insulation health condition. The benefits of PD condition monitoring of HVE can be extended by proper detection, identification, and interpretation of PD signal. Among both on-line and off-line PD monitoring techniques, on-line PD monitoring is a very promising technique that assists in robust monitoring system which reduces the power failure incidents in power system components. Therefore, to understand recent developments and trends in theory and in practice, it is necessary to establish a holistic analysis of current on-line PD monitoring techniques for HVE in power systems. This paper presents an intensive literature review of current on-line PD monitoring techniques used for different high voltage electric components in power system. Finally, a smart PD monitoring techniques based on wireless sensor board is proposed. The proposed smart PD monitoring framework may be used to correctly estimate the insulation degradation in HVE and enhance the overall performance of power systems.

Electrical insulation is an integral part of power components. The aging of electrical insulation is an undeniable fact that limits the operational lifetime of power components. Apart from regular aging, abnormal stresses and the development of defects are real threats because of their contribution in accelerating the aging rate and thereby leading to a premature failure of the power components. Over the decades, various studies have been carried out to understand the aging behavior of electrical insulation mainly considering electrical and thermal stresses. Similarly, a number of mathematical (aging) models have been developed based on the theoretical and experimental investigations and evidences. However, a dependable formulation of the models that can provide more practical estimation of the insulation degradation profile has not been achieved yet. This paper presents a comprehensive review of the aging models considering single and multistress conditions. Further, the paper discusses possible challenges and barricades averting the conventional models to achieve a suitable accuracy. Finally, suggestions are provided that can be considered to improve the modeling approaches and their performance.

The long term and large scale energy storage operations require quick response time and round-trip efficiency, which are not feasible with conventional battery systems. To address this issue while endorsing high energy density, long term storage, and grid adaptability, the hydrogen energy storage (HES) is preferred. This proposed work makes a comprehensive review on HES while synthesizing recent research on energy storage technologies and integration into renewable energy (RE) applications. The proposed research also identifies critical challenges related to system optimization, energy management strategies, and economic viability while featuring emerging technologies like artificial intelligence (AI) and machine learning (ML) for energy management. The proposed survey also discusses key advancements in battery technologies (lithium-ion, Ni-Cd, Ni/MH, and flow batteries) that are examined alongside innovations in HES methods. The proposed survey utilizes an extensive list of publications to date in the open literature to canvass and portray various developments in this area.

The fact that electricity needs to be consumed at the same moment it is generated makes it very complicated to match supply and demand at all times. With the evolution of more and more intermittent renewable energy sources in the system, it has become more challenging to meet demand and supply in real time, hence the demand for energy storage systems to optimize energy costs and ease grid operations. The need for these systems arises because of the intermittency and uncontrollable production of wind, solar, and tidal energy sources. Therefore, a storage system that can store energy produced from renewable energy sources and then convert it into electrical energy when required is highly needed. Modern energy storage technologies play a pivotal role in the storage of energy produced through unconventional methods. This review paper discusses technical details and features of various types of energy storage systems and their capabilities of integration into the power grid. An analysis of various energy storage systems being utilized in the power grid is also presented. A review of a technology would be incomplete without the study of its ramifications for the environment. Therefore, the effect of various energy storage technologies on the environment is also a part of this comprehensive study.

High energy arc faults in medium-voltage (MV) switchgear are serious hazards to personnel or equipment, and may cause process interruptions. Most of the electrical faults leading to arc are developed slowly, e.g., due to insulation degradation or bad connection. In this paper, the detection of partial discharges (PDs) and low energy arcing between loose contacts has been proposed for online monitoring of MV switchgear. The PD measurements in a switchgear panel and arcing measurements across a 0.2-mm sphere-to-rod gap have been carried out. Measured signals are captured by a differential electric field sensor (D -dot sensor) and recorded by a high-frequency oscilloscope. In general, online measured signals are suppressed by high-frequency noise, and therefore, de-noising of measurements is of paramount importance to get reliable information about a fault. An implementation of discrete wavelet transform, to de-noise the measured signals, has been proposed in this paper. Comparison with a well-known infinite impulse response filtering technique has been made. Time and frequency domain comparisons between original and de-noised signals reveal the significance of this technique for arc fault prediction in MV switchgear. A layout for the integration of online monitoring to central control is also presented.