基于改进粒子群和变步长扰动的复合MPPT算法
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摘要
光伏阵列在局部阴影条件下的功率-电压(P-U)曲线呈阶梯状,由于多峰特性的存在,传统MPPT(Maximum Gower Point Tracking)算法失效,无法寻找到真正的最大功率点。针对这一问题提出了改进粒子群结合变步长扰动的复合MPPT算法。在算法的第一阶段,针对传统PSO算法的缺陷和不足,对权重因子w、最大搜索速度Vmax、粒子数目Np和粒子搜索顺序进行设计和改进,使系统快速找到最大功率点(GMPP)的大概位置;第二阶段,利用改进的Fibonacci数列作为变步长扰动观察步长改变的依据,准确快速地跟踪到最大功率点。该方法以Boost变换器为研究对象,利用Saber和Matlab进行协同仿真,仿真结果证明:在局部阴影条件下,相比传统的粒子群算法和扰动观察法,该算法收敛速度更快,精度更高,系统的静态和动态性能更好。
The power-voltage( P-U) curve of photovoltaic arrays under local shadow conditions is ladder-like. Due to the existence of multi-peak characteristics,the traditional MPPT algorithm fails and the true maximum power point cannot be traced. To solve this problem,this paper proposes an improved hybrid MPPT algorithm that combines particle swarm optimization with variable step disturbance. In the first stage,as for the deficiencies of the traditional pso algorithm,the weighting factor w,the maximum search speed Vmax,the number of particles Npand the particle search sequence were designed and improved to quickly find the approximate position of the maximum power point( MPP). In the second stage,the Fibonacci sequence serves as the basis for the change of the step the variable-step perturbation observation method,to accurately and quickly track the maximum power point. The method used the co-simulation of Saber and Matlab. The simulation results show that the hybrid MPPT algorithm has faster convergence speed,higher precision and better static and dynamic performance of the system.
The power-voltage( P-U) curve of photovoltaic arrays under local shadow conditions is ladder-like. Due to the existence of multi-peak characteristics,the traditional MPPT algorithm fails and the true maximum power point cannot be traced. To solve this problem,this paper proposes an improved hybrid MPPT algorithm that combines particle swarm optimization with variable step disturbance. In the first stage,as for the deficiencies of the traditional pso algorithm,the weighting factor w,the maximum search speed Vmax,the number of particles Npand the particle search sequence were designed and improved to quickly find the approximate position of the maximum power point( MPP). In the second stage,the Fibonacci sequence serves as the basis for the change of the step the variable-step perturbation observation method,to accurately and quickly track the maximum power point. The method used the co-simulation of Saber and Matlab. The simulation results show that the hybrid MPPT algorithm has faster convergence speed,higher precision and better static and dynamic performance of the system.
引文
[1] 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.
[2] MIYATAKE M,TORIUMI F,ENDO T,et al. A Novel maximum power point tracker controlling several converters connected to photovoltaic arrays with particle swarm optimization technique[C]//2007 European Conference on Power Electronics and Applications. USA:IEEE,2007:1-10.
[3]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(11):78-83.
[4]王雨,胡仁杰.基于粒子群优化和爬山法的MPPT算法[J].太阳能学报,2014,35(1):149-153.
[5]马昊,张庆超.基于粒子群优化算法和变步长扰动观察法的局部阴影情况下MPPT控制[J].电源学报,2016,14(3):94-101.
[6]周航.基于粒子群算法的局部遮阴光伏发电系统MPPT控制的研究[D].天津:天津大学,2009.
[7]杨铎.基于粒子群优化算法的高性能功率优化器的研究[D].北京:北京交通大学,2017.
[8] PHIMMASONE V,ENDO T,KONDO Y,et al. Improvement of the maximum power point tracker for photovoltaic generators with particle swarm optimization technique by adding repulsive force among agents[C]//2009 International Conference on Electrical Machines and Systems.[S. l.]:IEEE,2009:1-6.
[9] ISHAQUE K,SALAM Z. A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition[J]. IEEE Transactions on Industrial Electronics,2012,60(8):3195-3206.
[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]张永革,石季英,张文,等.复杂遮阴条件下光伏系统MPPT控制改进PSO算法仿真研究[J].中国电机工程学报,2014,34(S1):39-46.
[12] PATEL H,AGARWAL V. Maximum power point tracking scheme for PV systems operating under partially shaded conditions[J]. IEEE Transactions on Industrial Electronics,2008,55(4):1689-1698.
[2] MIYATAKE M,TORIUMI F,ENDO T,et al. A Novel maximum power point tracker controlling several converters connected to photovoltaic arrays with particle swarm optimization technique[C]//2007 European Conference on Power Electronics and Applications. USA:IEEE,2007:1-10.
[3]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(11):78-83.
[4]王雨,胡仁杰.基于粒子群优化和爬山法的MPPT算法[J].太阳能学报,2014,35(1):149-153.
[5]马昊,张庆超.基于粒子群优化算法和变步长扰动观察法的局部阴影情况下MPPT控制[J].电源学报,2016,14(3):94-101.
[6]周航.基于粒子群算法的局部遮阴光伏发电系统MPPT控制的研究[D].天津:天津大学,2009.
[7]杨铎.基于粒子群优化算法的高性能功率优化器的研究[D].北京:北京交通大学,2017.
[8] PHIMMASONE V,ENDO T,KONDO Y,et al. Improvement of the maximum power point tracker for photovoltaic generators with particle swarm optimization technique by adding repulsive force among agents[C]//2009 International Conference on Electrical Machines and Systems.[S. l.]:IEEE,2009:1-6.
[9] ISHAQUE K,SALAM Z. A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition[J]. IEEE Transactions on Industrial Electronics,2012,60(8):3195-3206.
[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]张永革,石季英,张文,等.复杂遮阴条件下光伏系统MPPT控制改进PSO算法仿真研究[J].中国电机工程学报,2014,34(S1):39-46.
[12] PATEL H,AGARWAL V. Maximum power point tracking scheme for PV systems operating under partially shaded conditions[J]. IEEE Transactions on Industrial Electronics,2008,55(4):1689-1698.