基于LabVIEW的光伏发电系统MPPT算法研究
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摘要
针对光伏阵列的非线性问题,提出了一种快速、稳定且能够全局寻优的最大功率点跟踪算法。该算法首先将粒子群优化算法改进,使其能够在一定的迭代次数下稳定、全局地更新所有粒子的速度和位置,接近最大功率点;第二步采用以Fibonacci数列作为步长改变依据的变步长扰动观察法并将其优化,使其快速得到功率的最佳解。利用LabVIEW软件搭建了模型并仿真,验证了算法在精度与速度上的大幅度提升,确定了算法的先进性和可行性。
The output power of photovoltaic array is strongly influenced by ambient temperature and illumination,also often patially shaded by clouds,leading to unstable curve of power.In order to solve this problem,this paper puts forward a Maximum Power Point Tracking algorithm with the ability of rapid and global optimization.The algorithm uses improved particle swarm optimization algorithm to update the velocity and position of all particles under a certain number of iterations,making output power close to the location of maximum power point,and then uses the method of variable step perturbation and observation whose step length is decided by sequence of Fibonacci number,to obtain the optimal solution of power.Model was established and simulation was conducted on Labview.It was shown that the algorithm's precision and speed are greatly improved.It is verified that the algorithm is of advance and feasibility.
The output power of photovoltaic array is strongly influenced by ambient temperature and illumination,also often patially shaded by clouds,leading to unstable curve of power.In order to solve this problem,this paper puts forward a Maximum Power Point Tracking algorithm with the ability of rapid and global optimization.The algorithm uses improved particle swarm optimization algorithm to update the velocity and position of all particles under a certain number of iterations,making output power close to the location of maximum power point,and then uses the method of variable step perturbation and observation whose step length is decided by sequence of Fibonacci number,to obtain the optimal solution of power.Model was established and simulation was conducted on Labview.It was shown that the algorithm's precision and speed are greatly improved.It is verified that the algorithm is of advance and feasibility.
引文
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[9]PATEL H,AGARWAL V.MATLAB-based modeling to study the effects of partial shading on PV array characteristics[J].IEEE Transactions on Energy Conversion,2008,23(1):302-310.
[10]ISHAQUE K,SALAM Z,AMJAD M,et al.An improved particle swarm optimization(PSO)-based MPPT for PV with reduced steady-state oscillation[J].IEEE Transactions on Power Electronics,2012,27(8):3627-3638.
[11]张军朝.路灯、景观灯照明控制系统节能技术研究[D].太原:太原理工大学,2012.
[12]李江,韩海霞,王晓倩,等.局部阴影下的光伏阵列MPPT算法研究[J].控制工程,2014,21(3):419-424.LI J,HAN H X,WANG X Q,et al.Maximum power point tracking scheme for PV systems operating under partially shaded conditions[J].Control Engineering of China,2014,21(3):419-423.
[13]KOUTROULIS E,BLAABJERG F.Overview of maximum power point tracking techniques for photovoltaic energy production systems[J].Electric Power Components and Systems,2015,43(12):1329-1351.
[2]吴雨薇,时斌,朱海勇,等.基于变步长扰动观察法的光伏电池最大功率点跟踪[J].电气技术,2014(6):23-25.WU Y W,SHI B,ZHU H Y,et al.Photovoltaic array maximum power point tracking based on improved variable step P&O[J].Electrical Engineering,2014(6):23-25.
[3]朱艳伟,石新春,但扬清,等.粒子群优化算法在光伏阵列多峰最大功率点跟踪中的应用[J].中国电机工程学报,2012,32(4):42-48.ZHU Y W,SHI X C,DAN Y Q,et al.Application of pso algorithm in global mppt for PV array[J].Proceedings of the CSEE,2012,32(4):42-48.
[4]胡克用,胥芳,艾青林,等.适用于光伏多峰功率跟踪的改进型粒子群优化算法[J].西安交通大学学报,2015,49(4):140-148.HU K Y,XU F,AI Q L,et al.Improved particle swarm optimization for photovoltaic multi-peak power tracking[J].Journal of Xi'an Jiaotong University,2015,49(4):140-148.
[5]ALTAS I H,SHARAF A M.A novel maximum power fuzzy logic controller for photovoltaic solar energy systems[J].Renewable Energy,2008,33(3):388-399.
[6]杨建青,高晓阳,李红岭,等.农田独立光伏供电系统的MPPT模糊自寻优控制[J].太阳能学报,2016,37(2):361-365.YANG J Q,GAO X Y,LI H L,et al.Adaptive fuzzy self-optimizing control of mppt in stand alone pv power system for farmland[J].Acta Energiae Solaris Sinica,2016,37(2):361-365.
[7]KUMARAPPAN N,MOHAN M R.Comparison of classical methods and lambda based economic and emission dispatch using a hybrid genetic algorithm[J].Engineering Intelligent Systems,2006(2):71-77.
[8]DE LA O D,CASTILLO O,MELENDEZ A.Optimization of fuzzy control systems for mobile robots based on PSO[J].Studies in Computational Intelligence,2014,547:191-208.
[9]PATEL H,AGARWAL V.MATLAB-based modeling to study the effects of partial shading on PV array characteristics[J].IEEE Transactions on Energy Conversion,2008,23(1):302-310.
[10]ISHAQUE K,SALAM Z,AMJAD M,et al.An improved particle swarm optimization(PSO)-based MPPT for PV with reduced steady-state oscillation[J].IEEE Transactions on Power Electronics,2012,27(8):3627-3638.
[11]张军朝.路灯、景观灯照明控制系统节能技术研究[D].太原:太原理工大学,2012.
[12]李江,韩海霞,王晓倩,等.局部阴影下的光伏阵列MPPT算法研究[J].控制工程,2014,21(3):419-424.LI J,HAN H X,WANG X Q,et al.Maximum power point tracking scheme for PV systems operating under partially shaded conditions[J].Control Engineering of China,2014,21(3):419-423.
[13]KOUTROULIS E,BLAABJERG F.Overview of maximum power point tracking techniques for photovoltaic energy production systems[J].Electric Power Components and Systems,2015,43(12):1329-1351.