摘要
针对光伏阵列在实际应用过程中出现局部遮阴、输出特性P-U曲线呈现多峰值的情况,提出了一种混合算法,使用“两步走”策略来搜寻全局最大功率点。利用粒子群算法(PSO)和遗传算法(GA)相结合的算法通过少量的迭代次数搜寻至最大功率点附近;切换至模糊控制方法来搜寻最大功率点,并稳定。这种混合算法弥补了单个算法的不足,提高了系统的速度和精度。通过粒子群算法和遗传算法优缺点互补,避免陷入局部最优值和减少收敛时间。通过模糊控制方法可以使系统在最大功率点处稳定,避免振荡带来的能量损失。通过Simulink仿真验证了所提出的混合算法有较优的跟踪性能和响应速度。
In the practical application process of photovoltaic array,local shading occurs,and the output characteristic P-U curve presents multi peak situation.In this paper,a hybrid algorithm is proposed,which uses a"two-step"strategy to search the global maximum power point.Firstly,the particle swarm optimization(PSO)and genetic algorithm(GA)are used to search the maximum power point through a small number of iterations.Then switch to the fuzzy control method to search the maximum power point and stabilize.This hybrid algorithm makes up for the shortcomings of single algorithm and improves the speed and accuracy of the system.Through the complementary advantages and disadvantages of particle swarm optimization and genetic algorithm,it can avoid falling into the local optimal value and reduce the convergence time.The fuzzy control method can make the system stable at the maximum power point and avoid the energy loss caused by oscillation.Finally,the Simulink simulation results show that the proposed hybrid algorithm has better tracking performance and response speed.
作者
郭昆丽
刘璐雨
蔡维正
GUO Kunli;LIU Luyu;CAI Weizheng(College of Electronics and Information,Xi'an Polytechnic University,Xi'an Shaanxi 710048,China)
出处
《电源技术》
CAS
北大核心
2021年第8期1040-1043,共4页
Chinese Journal of Power Sources
关键词
光伏发电
模糊控制
最大功率点跟踪
粒子群优化
遗传算法
photovoltaic
fuzzy control
maximum power point tracking
particle swarm optimization
genetic algorithm