基于自适应布谷鸟搜索和扰动观察法的光伏最大功率点跟踪  

PV power point tracking based on adaptive cuckoo search and perturbation observation method

作　　者：商立群[1] 李帆[1] SHANG Liqun;LI Fan(School of Electrical and Control Engineering,Xi’an University of Science and Technology,Xi'an 710054,China)

机构地区：[1]西安科技大学电气与控制工程学院,陕西西安710054

出　　处：《电力系统保护与控制》2022年第8期99-107,共9页Power System Protection and Control

基　　金：陕西省自然科学基金项目资助(2021JM-393)。

摘　　要：当光伏阵列板暴露在不均匀的光线下时,功率电压(P-V)特性曲线会变为多峰,在这种情况下,传统的最大功率点跟踪(MPPT)算法将无法跟踪到正确的全局最大功率点(GMPP),而具有全局搜索能力的人工智能算法通常是高度参数化和复杂的。为了解决上述问题,提出了一种结合自适应布谷鸟搜索算法和扰动观察方法(ACS-P&O)的复合跟踪算法。该方法将布谷鸟搜索(CS)算法中的切换概率和Lévy飞行步长系数通过自适应调整,在跟踪早期,扩大算法的搜索范围。引入边界个体的处理策略,可进一步减少算法的迭代次数。该算法使系统更容易跳出局部最大功率点(LMPP),而在跟踪后期,算法精确运行在小范围内,提高了局部开发能力。扰动观察法(P&O)的加入缓解了系统位于GMPP附近时的功率振荡,稳定了输出。仿真结果表明,ACS-P&O复合算法能够适应环境变化的影响,并快速准确地跟踪GMPP。When a photovoltaic array panel is exposed to uneven light,the power-voltage(P-V)characteristic curve becomes multi-peaked,and conventional maximum power point tracking(MPPT)algorithms will not be able to track the correct global maximum power point(GMPP),and artificial intelligence algorithms with global search capabilities are usually highly parameterized and complex.To address the above problems this paper proposes a composite tracking algorithm combining the adaptive cuckoo algorithm and perturbation observation method(ACS-P&O).This improved method takes the switching probabilities and Lévy flight step coefficients from the cuckoo search(CS)algorithm and adaptively adjusts them to extend the search range of the algorithm at an early stage.The introduction of a processing strategy for bounding individuals further reduces the number of algorithm iterations.The improved algorithm makes it easier for the system to jump out of the local maximum power point(LMPP),while at a later stage the algorithm operates precisely in a small area,improving the local exploitation capability.The addition of the perturbation and observation(P&O)method mitigates power oscillations when the system is located near the GMPP and stabilizes the output.Simulation results show that the ACS-P&O composite algorithm can adapt to the effects of environmental changes and track the GMPP quickly and accurately.

关 键 词：光伏 MPPT 自适应布谷鸟搜索算法 扰动观察法 Lévy飞行 边界个体 

分 类 号：TM615[电气工程—电力系统及自动化] TP18[自动化与计算机技术—控制理论与控制工程]