Journal of Electrical and Power System Engineering

Maximum Power Point Tracking for PV Systems Using a Buck-Boost Converter

Vinaya B. Koradoor, Harshitha H., Suhas Adiga, Yashas Gowda P. R. — Fri, 08 May 2026 00:00:00 +0000

One of the main challenges with solar photovoltaic systems is that their power output is never completely constant. It changes constantly with available sunlight and panel temperature. This means the point at which the panel delivers maximum power keeps shifting throughout the day. Without a system to track this point, a lot of energy is wasted. In this work, we address this issue by building and simulating a Buck-Boost DC-DC converter along with a particle swarm optimization (PSO) based maximum power point tracking (MPPT) controller. PSO is particularly effective here because it can quickly adjust when conditions change suddenly, like when a cloud blocks the sunlight. We implemented the entire system in simulation, using a nonlinear PV module model, averaged state-space equations for the converter, and a time-varying irradiance profile that reflects real weather patterns. We assessed the system based on how accurately it tracks the true maximum power point, how the duty cycle reacts during sudden changes, and how quickly it converges after a disturbance. Our results show that the PSO-MPPT approach achieves tracking efficiency of 85 to 92%, recovers quickly from sudden irradiance drops, and keeps the converter operating steadily. Overall, these findings support the use of optimization-based MPPT as a practical and reliable method for PV systems that operate in real-world, changing conditions.

Determination of Generator Angular Speed and Rotor Angle using Swing Equation, Runge-Kutta Fourth Order and State Variable Methods

Lawrence Ekeng, Christopher Ahiakwo, Braide Sepiribo, Hachimenum Amadi — Thu, 14 May 2026 00:00:00 +0000

This study investigated the transient response of the generators in the Nigerian 330 kV grid network when a three phase is applied to perturb the system to determine the impact on the rotor angle and angular speed deviations in the network under investigation in a view to describe the behaviour of the 330/132kV Adiabo/Odukpani network with particular emphasis on the characteristics of 593MW synchronous generators after a large disturbance on the power system. To overcome these incessant disturbances on the network, which often result in outages and blackouts that can damage or hinder certain components of the network, there is a need to conduct transient stability evaluations on the power system to determine various network parameter conditions. This study proposed the determination of generator angular speed and rotor angle using the state variable analysis method in comparison to the existing Runge-Kutta fourth order (RK4) method, while benchmarking it against traditional swing equations numerical techniques to model power system behavior following a transient condition. This approach enables the simulation and prediction of whether the system will return to normal operation or become unstable by analyzing rotor angles and speeds over time. This study provides a comprehensive analytical and numerical examination of the determination of angular speed and rotor angle of synchronous generators through three methodologies: the traditional swing equation method, the Fourth-Order Runge-Kutta (RK4) method, and the State Variable Approach (SVA). Numerical iterations, comparative performance assessments, and in-depth mathematical derivations are provided. The results show that while the traditional approach offers a straightforward baseline solution, RK4 greatly improves accuracy, and SVA enables scalability for multi-machine systems with improved accuracy and stability. The results offer insights into their usefulness in power system stability studies and enhance modeling and simulation techniques in power system dynamics.

Reliability Assessment of Radial Distribution System with Optimally Located DGs using ANN

Chaya Melagiri, Shekhappa Ankaliki, Manjula S. Sureban, Basavaraj S. Shalavadi — Mon, 29 Jun 2026 00:00:00 +0000

The study exhibits a PSO optimization approach to refine the reliability and operational efficiency of a radial delivery network (RDN) by optimizing the site and location of Distributed Generators (DGs). The IEEE 11-Bus System is chosen as a benchmark network for evaluating the effectiveness of distribution-level optimization techniques. First, information regarding the system parameters (bus data, line resistance and reactance, real and reactive power demands and voltage profiles) is collected and preprocessed. Once the base-case analysis is completed and the evaluation indices, such as active power loss, reactive power loss, voltage deviation, and reliability indices, are assessed, the optimal DG placement and suitable DG sizes are determined using Particle Swarm Optimization (PSO) subject to operational constraints. The multi-objective function minimizes power losses and voltage deviation while maximizing the Voltage Stability Index (VSI). The proposed optimization approach is found to significantly enhance the system voltage stability, reliability, and overall performance based on the comparative analysis. The active power loss was reduced from 725.533 kW to 121.0347 kW, and the minimum voltage after DG integration optimization was upgraded from 0.9038 p.u. to 0.9823 p.u.

Design and Implementation of a Hybrid Solar–Grid Wireless Electric Vehicle Charging Station with IoT-based Intelligent Energy Management

Yogita G. Bele, V. G. Puranik — Tue, 07 Jul 2026 00:00:00 +0000

The rapid growth of electric vehicles has significantly increased the demand for safe, efficient, and sustainable charging infrastructure. Conventional plug-in charging systems suffer from mechanical wear, safety risks in outdoor environments, and heavy dependence on grid electricity. This paper presents the design and implementation of a hybrid solar–grid wireless electric vehicle charging station integrated with IoT-based intelligent power management. The proposed system utilizes magnetic resonant coupling for contactless power transfer, ensuring enhanced user safety and reduced maintenance. Solar energy is employed as the primary power source to promote sustainability, while grid supply serves as a backup to ensure uninterrupted charging during low solar conditions. An ESP32 microcontroller performs real-time monitoring of voltage and current parameters, executes automatic source selection through relay-based switching, and transmits operational data to a cloud platform via Wi-Fi for remote supervision. Experimental validation of the prototype demonstrates stable wireless power transfer, seamless solar–grid transition, and reliable real-time monitoring. The developed system offers a smart, scalable, and environmentally friendly solution for next-generation EV charging infrastructure.