Frequency Control Method for Distributed Energy Systems Based on Nash Equilibrium Quantum Particle Swarm Optimization

Distributed energy systems relying on renewable energy sources such as wind and solar energies are faced with challenges, including excessive frequency fluctuations and the complexity of hybrid energy storage control. To address these issues, the paper proposes a frequency control method based on Nash equilibrium quantum particle swarm optimization (NEQPSO) for distributed energy systems. Initially, a model is established to simulate distributed energy systems containing renewable energy sources and featuring hybrid energy storage. Subsequently, the outputs from both the slide mode controller (SMC) and the linear active disturbance rejection controller (LADRC) observer are integrated into the proportional derivative (PD) controller of the LADRC, leading to an improved slide mode-linear active disturbance rejection controller (SM-LADRC). Following this, NEQPSO is utilized to optimize the controller parameters to secure optimal configurations. Finally, comparative validation experiments are conducted under different settings, demonstrating that the optimized controller significantly outperformed conventional proportional integral derivative (PID) and proportional integral (PI) controllers. The optimization capability of NEQPSO proved clearly superior to that of particle swarm algorithm (PSO) and genetic algorithm (GA). Moreover, in subsequent on-load experiments and sensitivity validation experiments, distributed energy systems employing SM-LADRC based on NEQPSO exhibited swift responsiveness, strong disturbance rejection, improved frequency stability, and enhanced steady-state performance.