基于改进粒子群算法的光伏MPPT控制研究
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摘要
针对局部阴影使光伏阵列呈现多峰值的现象,提出了一种基于改进粒子群的全局MPPT寻优算法。该算法首先采用大步长扰动观察法进行一次寻优,然后通过非线性动态改进惯性权重策略对粒子群算法改进,用改进粒子群算法进行二次全局寻优,最后使用变步长扰动观察法进行三次迭代寻优。仿真结果表明,混合算法能够在不同阴影条件下快速、准确地跟踪最大功率点,避免系统陷入局部最优值,具有良好的动态性、稳定性和高效性。
Aiming at the phenomenon that the PV array exhibits multiple peaks for local shadows, a global MPPT optimization algorithm based on improved particle swarm optimization was proposed. The maximum power tracking of photovoltaic array under local shadow was studied. The algorithm utilizes a large step perturbation observation method to perform a search optimizationfirstly. Secondly, it improves the particle swarm optimization algorithm by using a non-linear dynamic inertia weight improvement strategy, and uses the improved particle swarm algorithm to perform a second global optimization. Finally, it uses variable step length perturbation observation to perform three iterations. The simulation results show that the hybrid algorithm can quickly and accurately track the maximum power point under different shadow conditions to avoid the system falling into a local optimal value and have good dynamic performance, stability, and high efficiency.
Aiming at the phenomenon that the PV array exhibits multiple peaks for local shadows, a global MPPT optimization algorithm based on improved particle swarm optimization was proposed. The maximum power tracking of photovoltaic array under local shadow was studied. The algorithm utilizes a large step perturbation observation method to perform a search optimizationfirstly. Secondly, it improves the particle swarm optimization algorithm by using a non-linear dynamic inertia weight improvement strategy, and uses the improved particle swarm algorithm to perform a second global optimization. Finally, it uses variable step length perturbation observation to perform three iterations. The simulation results show that the hybrid algorithm can quickly and accurately track the maximum power point under different shadow conditions to avoid the system falling into a local optimal value and have good dynamic performance, stability, and high efficiency.
引文
[1]吴志程,江智军,杨晓辉.一种基于功率闭环控制的改进全局MPPT方法[J].电力系统保护与控制,2018,46(1):57-42.
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[15] ISHAQUE K,SALAM Z,SHAMSUDIN A,et al. A di-rect control based maximum power point tracking meth-od for photovoltaic system under partial shading condi-tions using particle swarm optimization algorithm[J].Applied Energy,2012,99(99):414-422.
[16] CHOWDHURY S R,SAHA H. Maximum power pointtracking of partially shaded solar photovoltaic arrays[J]. Solar Energy Materials and Solar Cells,2010,94(9):1441-1447.
[17]王秀云,赵宇,马万明,等.改进粒子群算法在无功优化中的应用[J].电测与仪表,2015,52(15):108-112.
[18]唐浩,杨国华,王鹏珍,等.基于改进粒子群算法的风光蓄互补发电系统容量优化[J].电测与仪表,2017,54(16):50-55.
[19] PATEL H,AGARWAL V. Maximum Power Point Track-ing Scheme for PV Systems Operating Under PartiallyShaded Conditions[J]. Control Engineering of China,2014,55(4):1689-1698.
[20]代相波,赵志刚.基于滞环比较的扰动观察法在光伏MPPT中的研究[J].沈阳工程学院学报:自然科学版,2018,14(1):5-10.
[2]张兴,曹仁贤.太阳能光伏并网发电及其逆变控制[M].北京:机械工业出版社,2011.
[3]刘云,应康,辛焕海,等.基于二次插值法的光伏发电系统控制策略[J].电力系统自动化,2012,36(21):29-35.
[4]唐磊,曾成碧,苗虹,等.基于切线角的光伏变步长最大功率跟踪控制策略[J].电力系统自动化,2013,37(20):28-33.
[5]张开,石季英,林济铿,等.基于自适应滑模层极值搜索的光伏发电最大功率跟踪方法[J].电力系统自动化,2015,39(12):33-37.
[6]孙航,杜海江,季迎旭,等.光伏分布式MPPT机理分析与仿真研究[J].电力系统保护与控制,2015,43(2):48-54.
[7]刘邦银,段善旭,康勇.局部阴影条件下光伏模组特性的建模与分析[J].太阳能学报,2008,29(2):188-192.
[8]杨元培,杨奕,王建山,等.光伏发电传输最大功率储能优化建模仿真[J].计算机仿真,2017,34(9):103-108.
[9]李文强,黎英,张轩.改进基于INC算法的光伏发电系统最大功率跟踪[J].电源技术,2017,41(12):1737-1740.
[10] DABRA V,PALIWAL K K,SHARMA P,et al. Optimi-zation of photovoltaic power system:a comparativestudy[J]. Protection and Control of Modern Power Sys-tems,2017,2(2):29-39.
[13]赵阳,张军朝,陶亚男,等.基于粒子群优化变步长扰动观察MPPT算法[J].计算机仿真,2017,34(11):78-83.
[14] ISHAQUE K,SALAM Z,AMJAD M,et al. An im-proved particle swarm optimization(PSO)-basedMPPT for PV with reduced steady state oscillation[J].IEEE Transactions on Power Electronics,2012,27(8):3627-3638.
[15] ISHAQUE K,SALAM Z,SHAMSUDIN A,et al. A di-rect control based maximum power point tracking meth-od for photovoltaic system under partial shading condi-tions using particle swarm optimization algorithm[J].Applied Energy,2012,99(99):414-422.
[16] CHOWDHURY S R,SAHA H. Maximum power pointtracking of partially shaded solar photovoltaic arrays[J]. Solar Energy Materials and Solar Cells,2010,94(9):1441-1447.
[17]王秀云,赵宇,马万明,等.改进粒子群算法在无功优化中的应用[J].电测与仪表,2015,52(15):108-112.
[18]唐浩,杨国华,王鹏珍,等.基于改进粒子群算法的风光蓄互补发电系统容量优化[J].电测与仪表,2017,54(16):50-55.
[19] PATEL H,AGARWAL V. Maximum Power Point Track-ing Scheme for PV Systems Operating Under PartiallyShaded Conditions[J]. Control Engineering of China,2014,55(4):1689-1698.
[20]代相波,赵志刚.基于滞环比较的扰动观察法在光伏MPPT中的研究[J].沈阳工程学院学报:自然科学版,2018,14(1):5-10.