Journal of Advance Electrical Engineering and Devices

Smart Distribution Transformers in Smart Grids: A Review with Real-time Data

Ashvin Madanlal Maheshwari, Pratikkumar Arvindbhai Kabrawala — Wed, 04 Feb 2026 00:00:00 +0000

Smart transformers under development have the potential to transform conventional power distribution networks into intelligent, reliable, cost-effective, and environmentally friendly systems. Unlike traditional transformers that only perform voltage transformation, smart distribution transformers integrate power electronics, communication, sensing, and control capabilities. These features enable automatic voltage regulation, real-time monitoring, telemetry, and remote control, which are essential for Smart Grid (SG) applications. Present power grids mainly operate in a unidirectional manner, where energy flows from generation to consumers. However, the increasing penetration of renewable energy sources, electric vehicles, and distributed generation requires bidirectional power flow and adaptive control. Advanced Metering Infrastructure (AMI) and Advanced Sensor Infrastructure (ASI) play a critical role in protecting distribution transformers from overloading, overheating, voltage fluctuations, and premature failure. This paper presents a comprehensive review of smart distribution transformers, their architecture, enabling technologies, and applications. In addition, real-time operational data trends and a practical case study of a smart distribution transformer deployment are discussed to highlight performance improvements, reliability enhancement, and loss reduction in modern power distribution systems.

Comprehensive Performance and Thermal Analysis of Power Transformers Under Variable Load Conditions

Md. Ali — Fri, 20 Mar 2026 00:00:00 +0000

This study aims to investigate the behavior of power transformers under diverse load conditions, including light load, rated load, and overload scenarios. Power transformers serve as vital components in electrical power systems, ensuring the reliable transformation of voltage and uninterrupted power delivery. Because load conditions fluctuate continuously, transformer performance is highly sensitive to these variations, influencing efficiency, voltage regulation, and thermal stability. Experimental measurements, coupled with analytical calculations, were employed to assess key parameters such as efficiency, voltage drop, and temperature rise. The results demonstrate that efficiency reaches its maximum near rated load, whereas it declines under both light and overload conditions. Moreover, temperature rise becomes significantly more pronounced during overload operation, highlighting potential thermal management challenges. These findings offer practical guidance for utilities and engineers, enabling them to optimize transformer operation, minimize energy losses, and enhance the overall reliability of power systems.

Review on Modern Optimization Techniques for Optimal Distributed Generation in IEEE Radial Distribution Systems

Kunal P. Sananse, Dolly Thankachan — Fri, 13 Feb 2026 00:00:00 +0000

Modern life cannot be existed without electricity. The energy that powers lives and provides all the things needed to survive is generated by electric power. Throughout history, electricity was produced at large central generating plants and was transported to consumers via long-distance Transmission and Distribution (T&D) lines. This system has served well for many years; however, it has significant limitations: a high level of energy loss through T&D lines, increasing energy costs, and reliance on traditional sources of energy, which are harmful to the environment. The increasing demand for energy and the need for more sustainable forms of energy production have prompted a shift in focus from Central-Generation Power Plants (CGPPs) to Distributed Generation (DG). A DG is defined as any small or medium-sized source of electrical power that is located close to consumers, such as solar and wind power. DGs can help to reduce the amount of energy that is lost through the T&D system, improve the system’s voltage profile, and enhance the reliability of electricity to consumers. DG technologies also help to integrate renewable energy into the existing electric grid, providing consumers with cleaner, greener, and more sustainable sources of electricity. The major challenge in realizing the benefits of DGs is in their careful planning and installation. Poor placement may result in increased costs, decreased efficiency and/or instability to the overall electric system. As a result, the area of research in DG is becoming increasingly important; specifically, the optimal placement and sizing of DGs using optimization techniques and load flow analysis.

Optimal Shunt Capacitor Placement for Voltage Profile Improvement in an 11kV Distribution Network: A Marine Base Feeder Case Study

Hachimenum Nyebuchi Amadi, Chidinma Peace Onyeanya, Kingsley Okpara Uwho — Tue, 13 Jan 2026 00:00:00 +0000

The study examines the degradation of voltage profiles in the marine base 11 kV distribution network in Port Harcourt, Rivers State, Nigeria, caused by increased load demand and insufficient reactive power support. Using operational data obtained from the Port Harcourt Electricity Distribution Company (PHED), the network is modelled and analysed in ETAP 19.1 software. A Newton–Raphson load flow method is employed to assess the steady state operating condition of the feeder and to identify weak buses that violate the statutory voltage limits of 0.95–1.05 per unit. Results from the base case analysis reveal that several downstream buses experience unacceptable voltage drops, with minimum voltage levels reaching as low as 94.15 percent. To address this deficiency, an optimal shunt capacitor placement strategy is applied. The analysis identifies bus 16 as the most effective location for compensation, and a capacitor bank rated at 3 × 300 kVAr is optimally sized and installed. Post compensation simulations demonstrate a significant improvement in voltage profile across the entire feeder, with all buses operating within permissible limits and the maximum voltage drop reduced from 5.85 percent to 1.79 percent. The novelty of the paper lies in its practical, utility-driven application of optimal capacitor placement on a real Nigerian 11 kV distribution network using field data, providing clear quantitative evidence of voltage enhancement through targeted reactive power compensation. The findings offer actionable guidance for distribution utilities seeking cost-effective solutions for improving power quality and system reliability.

Automated Transportation Setting using Hybrid Powered Unmanned Vehicle

Karanam Gururaj, Darshan K., Mruthyunjaya N., Raghuveer Naik, Shubash K. C. — Tue, 24 Feb 2026 00:00:00 +0000

become a key solution for automating material transportation. However, traditional AGV systems, which rely on fixed infrastructure and static path planning algorithms, often struggle in dynamic environments, leading to inefficiencies, delays, and potential collisions. This project focuses on improving AGV path planning using a hybrid approach that combines the strengths of the D* algorithm and the Dynamic Window Approach (DWA). The D* algorithm is used for global path planning due to its strong adaptability in dynamic environments, while an improved DWA handles local obstacle avoidance with smoother navigation and lower computational complexity. A grid-based map is used to model the workshop layout, enabling real-time adaptability and route flexibility. The AGV is designed to maintain uniform speed and optimal turning radius, enhancing energy efficiency and reducing wear and tear. Simulation results demonstrate that the proposed fusion algorithm reduces transport time by approximately 45% and path length by 17% compared to the traditional D* algorithm, proving its effectiveness and practicality in real-world scenarios. This improved AGV system offers significant advantages in terms of operational efficiency, energy savings, and safety. It is highly suitable for applications in automated factories, warehouses, hospitals, and research labs, where dynamic conditions and efficient routing are critical. The integration of adaptive path planning, sensor-based obstacle detection, and intelligent decision-making makes this solution a step forward in achieving flexible, autonomous, and sustainable transportation in Industry 4.0 environments.