Research on Dynamic Maintenance Model of Multi subsystem Wind Power Generation Based on SAPSO

A dynamic maintenance strategy based on Simulated Annealing and Particle Swarm Optimization (SAPSO) for Multiple subsystems of Wind Power Generation (MSWPG) is proposed to address the issues of high maintenance costs and low reliability in wind power generation under complex operating conditions. Firstly, a study was conducted on the nonhomogeneous Poisson continuous life distribution model based on reliability functions and life distribution functions, and the commonly used basic MSWPG maintenance models were analyzed. Then, based on the Markov decision model, the dynamic maintenance strategy of MSWPG was modeled, and the maintenance strategy of multiple subsystems was optimized based on SAPSO, improving maintenance efficiency and operational stability. Finally, the dynamic maintenance strategy of the proposed MSWPG was validated through experiments in the event of faults in the generator system, wind turbine system, pitch system, and frequency conversion system. The experimental results show that the average cost of the proposed optimization strategy is $\yen 3860 /$ day, $\yen 3620 /$ day, $\yen 2970 /$ day, and $\yen 3040 /$ day, respectively, which is lower compared to traditional methods. The average returns are $\yen 13750 /$ day, $\yen 14260 /$ day, $\yen 15320 /$ day, and $\yen 14720$ /day, respectively, with reliability rates of $92.63 \%$, $\mathbf{9 3. 5 6 \%}, \mathbf{9 2. 8 5 \%}$, and $\mathbf{9 3. 3 7 \%}$, which is a significant improvement compared to traditional methods.