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Improvement of power plant controller design for emergency reserve services
Author(s)
Tshinavhe, Ntanganedzeni
Date Issued
2026
Type
master thesis
Publisher
Cape Peninsula University of Technology
Abstract
The increasing global demand for clean, sustainable energy has seen a growth in the integration of renewable energy sources (RES) such as photovoltaic (PV) systems and wind into the power grid. While RES offer economic and environmental benefits, their variability and intermittency introduce major challenges to frequency stability, particularly in low synchronous inertia systems. As these variations can potentially cause frequency deviation, traditional load frequency control (LFC) techniques would often struggle to maintain the system’s stability during high levels of penetration of renewables. To address these problems, this research focuses on improving controller design for emergency reserve services through advanced optimisationbased LFC. The study develops, models, and simulates a single-area and two-area power system with PV generation and a battery energy storage system (BESS) based on MATLAB/Simulink. A baseline performance test is conducted in a single-area system to understand the behaviour of the system due to different disturbances. This test is first conducted without a controller and then followed by a standard proportional-integral-derivative (PID) control tuning through the Ziegler-Nichols technique. The recently proposed algorithm, which is the Zebra Optimisation Algorithm (ZOA) is used to tune the PID parameters. This algorithm is validated under different operating conditions, such as load changes, varying PV generation, different levels of renewable penetration (0.3 pu and 0.7 pu), the effect of BESS, and generation loss. Performance indicators like overshoot, undershoot, settling time, steady-state error, and frequency deviation are used to quantify the results. The simulation results show that the PID controller makes the system more stable compared to the baseline. However, its static gain reduces flexibility when conditions change. When the ZOA is applied, results showed improvement in reducing frequency deviation, reducing settling time and eliminating steady-state error and oscillations. A comparison study was conducted with the Particle Swarm Optimisation (PSO), in which the results showed that the ZOA is superior in reducing the overshoot and undershoot, while the PSO is superior in settling time. The ZOA was further implemented in a two-area system, and results show better performance in a higherorder system.
Additional information
Thesis (MEng (Electrical Engineering))--Cape Peninsula University of Technology, 2025
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Tshinavhe, N_220435413 (1).pdf
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