Regional Load Frequency Control of BP-PI Wind Power Generation Based on Particle Swarm Optimization

The large-scale integration of wind turbines (WTs) in renewable power generation induces oscillations, leading to frequency aberration due unbalance. Hence, this paper, a secondary control strategy called load (LFC) for systems with turbine participation is proposed. Specifically, backpropagation (BP)-trained neural network-based PI approach adopted optimize the conventional controller achieve better adaptiveness. proposed was developed realize timely adjustment parameters during unforeseen changes system operation, ensure mutual coordination among circuits. In meantime, improved particle swarm optimization (IPSO) algorithm utilized adjust initial neuron weights network, which can effectively improve convergence optimization. simulation results demonstrate that IPSO-BP-PI performed evidently than case random disturbance, significant reduction near 10 s regulation time and final stable error less 10?3 frequency. Additionally, compared counterpart, rate significantly improved. Furthermore, it achieves higher accuracy robustness, demonstrating energy into traditional systems.