Recent Advances in Electrical & Electronic Engineering - Online First

Aims and Background A re-evaluation of distribution transformer ratings is necessary to ensure efficient and reliable operation due to the significant impact of the growing number of electric vehicles (EVs) on load dynamics. The objective of this study is to optimize the rating of the distribution transformers to accommodate the year-round demand for electric vehicle charging while minimizing expenses and no-load l Read More

In the field of machine learning, federated learning (FL) has become a breakthrough paradigm, provided a decentralized method of training models while solving issues with data security, privacy, and scalability. This study offers a thorough analysis of FL, including an examination of its underlying theories, its varieties, and a comparison with more conventional machine learning techniques. We explore the drawbacks of convention Read More

The application of computer vision such as monitoring traffic, surveillance, autonomous driving, and vehicle detection, is a crucial task. Traditionally, vehicle detection has been addressed using methods based on supervised learning that involve a huge quantity of labelled data. However, collecting and annotating huge amounts of data is expensive and time-consuming, leading researchers to explore methods based on su Read More

Introduction Human health is significantly compromised by air pollution, especially by local air quality. The majority of our society spends their lives in a confined geographical location, which if subjected to air pollution can expose them to long-term air contamination. It is also possible that poor air quality can pose serious health risks, especially to susceptible individuals thereby impacting their lifestyle. Air quality can be improve Read More

Background The rapid growth of distribution grids and the increase in load demand have made distribution grids play a crucial role in urban development. However, distribution networks are prone to failures due to multiple events. These faults not only incur high maintenance costs, but also result in reduced productivity as well as huge economic losses. Therefore, accurate and fast fault localization methods are very imp Read More

Background Integration of cloud components in a wireless mesh network of Wireless-Optical Broadband Access Network (WOBAN) contributes to enhancing network performance. Aim This study aims to deploy the minimum cloudlets at the optimum location and to offload excess traffic from overloaded cloudlets to underloaded ones. Objective The objective of this study is to optimize cloudlet positioning and traffic offloading f Read More

Introduction Arc fault has become an increasingly prominent problem affecting the safe operation of power distribution networks. Research on arc fault detection can effectively reduce electrical fire accidents caused by arc faults, which is of great significance for ensuring the safe and reliable operation of power distribution networks. Methods In this paper, an arc fault detection method based on current convolution is proposed Read More

Background With the continuous development of permanent magnet synchronous motors (PMSM) and the increasing demand for the application of flywheel battery, the requirements for PMSMs are also increasing. Methods A multi-objective genetic algorithm is used to solve the optimal design solution. Results Multi-objective genetic algorithm is fast and accurate in calculation results, and it is easy to obtain the optimal solution. Read More

Introduction In grid-connected operation control, the Brushless Doubly-Fed Reluctance Generator (BDFRG) faces issues with strong parameter coupling and weak disturbance rejection. Methods This paper proposes a direct power control strategy with a novel integral sliding mode controller. By analyzing the correlation between the voltages on the stator control winding side and the active/reactive power, a direct power contr Read More