Robust low-frequency oscillations damping in hybrid renewable energy systems using advanced controller and optimization

Abstract Integrating renewable energy sources into modern power networks presents challenges like reduced grid inertia and low-frequency oscillations. The displacement of conventional synchronous generators weakens system inertia, making grids more susceptible to disturbances. Additionally, variable output from renewables can trigger low-frequency oscillations, threaten overall stability and require advanced control strategies for mitigation. Promising alternatives include pumped storage hydro power generation and advanced control algorithms like fuzzy logic, neural networks, and hybrid optimization techniques, though these still require further research and development. This research suggests a coordinated control approach that combines wind, Solar Photovoltaic (SPV), and pumped storage hydro generators with a turbine governor and unified power flow controller to efficiently mitigate issues. The primary goals are to: (a) Optimize the coordination between the unified power flow controller and the pumped storage governor in order to generate an efficient damping torque for problems during changeable solar and wind inputs. (b) To increase the pumped storage governor’s controllability while making sure it offers sufficient dampening for power system problems. The control systems aim to minimize deviations from desired operating points, focusing on both speed and real power deviations. This is accomplished by combining Linear Quadratic Regulator (LQR) and Proportional Derivative (PD) controllers, which increase the hybrid system’s efficacy. To fine-tune the suggested controller, a novel optimization technique: the Dynamic Opposite Learning-based Enhanced Osprey Optimization Algorithm (DOLOA) is proposed. This approach enhances the coordinated control strategy, enabling it to effectively mitigate low-frequency oscillations and maintain power system stability, even under significant disturbances, such as sudden fluctuations in solar photovoltaic and wind energy penetration. Simulations on the MATLAB/Simulink platform are used to test the performance of the suggested technique and compared to Tilt Integral Derivative (TID) and Fractional Order Proportional Integral Derivative (FOPID). The proposed control strategy achieves optimal performance, reducing frequency variations to within ±0.0001 p.u. over 15 s, outperforming TID and FOPID controllers.