Rogowski coil (RC) is a low-cost, air-cored, and flexible induction sensor for nonintrusive condition monitoring and thus can be used in a variety of applications. In this paper, a lumped parameter model of RC is presented and an experiment-based methodology is developed to determine its parameters. The performance of the RC is analyzed for detection and measurement of high-frequency (pulsed) signals such as partial discharge (PD) current pulses. A simple and efficient technique of numerical integration is adopted to avoid the conventional type of expensive and complex design analogue integrators. RC is modeled and simulated in the alternative transient program-electromagnetic transient program environment. The designed coil is tested to measure PDs in the laboratory. Simulated and experimental performance of RC is compared with a high-frequency current transformer. This comparison shows a good match and, hence, validates the design of RC for PD applications.

For wide use of electric vehicles (EVs), there are different aspects of the electric power system to consider for making it ready for the increased load by battery charging. The topics include power production, peak load management, distribution transmission capacity but also distribution network power quality and many more. This paper presents an overview on the likely power quality impacts in the distribution networks associated with EV charging. Based on a literature review, focus is especially put on harmonics and load unbalance in the network. Most relevant papers observing these topics are presented summarizing their contribution. The power quality aspects in distribution networks discussed here are not often presented within analysis of permissible EV penetration levels. Harmonics or voltage unbalance and effects associated with these could introduce additional limits to the EV charging capacity for the distribution networks. Therefore the analysis on the EV charging influence on these power quality topics requires also high-priority discussions before drawing conclusions on the distribution networks capabilities.

Power system planning in numerous electric utilities merely relies on the conventional statistical methodologies, such as ARIMA for short-term electrical load forecasting, which is incapable of determining the non-linearities induced by the non-linear seasonal data, which affect the electrical load. This research work presents a comprehensive overview of modern linear and non-linear parametric modeling techniques for short-term electrical load forecasting to ensure stable and reliable power system operations by mitigating non-linearities in electrical load data. Based on the findings of exploratory data analysis, the temporal and climatic factors are identified as the potential input features in these modeling techniques. The real-time electrical load and meteorological data of the city of Lahore in Pakistan are considered to analyze the reliability of different state-of-the-art linear and non-linear parametric methodologies. Based on performance indices, such as Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE), the qualitative and quantitative comparisons have been conferred among these scientific rationales. The experimental results reveal that the ANN–LM with a single hidden layer performs relatively better in terms of performance indices compared to OE, ARX, ARMAX, SVM, ANN–PSO, KNN, ANN–LM with two hidden layers and bootstrap aggregation models.

The uptake of electric vehicles (EV) is increasing every year and will eventually replace the traditional transport system in the near future. This imminent increase is urging stakeholders to plan up-gradation in the electric power system infrastructure. However, for efficient planning to support an additional load, an accurate assessment of the electric vehicle load and power quality indices is required. Although several EV models to estimate the charging profile and additional electrical load are available, but they are not capable of providing a high-resolution evaluation of charging current, especially at a higher frequency. This paper presents a probabilistic approach capable of estimating the time-dependent charging and harmonic currents for the future EV load. The model is based on the detailed travel activities of the existing car owners reported in the travel survey. The probability distribution functions of departure time, distance, arrival time, and time span are calculated. The charging profiles are based on the measurements of several EVs.

Due to their efficiency and control capabilities, induction motors fed with inverters have become prevalent in various industrial applications. However, ensuring the reliable operation of the motor and diagnosing faults on time are crucial for preventing unexpected failures and minimizing downtime. This paper systematically analyzes condition monitoring and practical diagnostic techniques for inverter-fed motor drive systems. This study encompasses a thorough evaluation of different methods used for condition monitoring and diagnostics of induction motors, with the most crucial faults in their stator, rotor, bearings, eccentricity, shaft currents, and partial discharges. It also includes an assessment of their applicability. The presented analysis includes a focus on the challenges associated with inverter-fed systems, such as high-frequency harmonics, common-mode voltages causing the bearing currents, and high voltage gradients (dv/dt) due to fast switching frequency, which can impact the motor operation, as well as its faults analysis. Furthermore, this research explores the usefulness and efficiency of various available diagnostic methods, such as motor current signature analysis and other useful analyses using advanced signal processing techniques. This study aims to present findings that provide valuable insights for developing comprehensive condition monitoring strategies, and practical diagnostic techniques that enable proactive maintenance, enhanced system performance, and improved operational reliability of inverter-fed motor drive systems.