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.

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.

Journal of Electrical and Power System Engineering

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

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