光伏系统在部分遮挡条件下的输出功率-电压(P-V)特性曲线呈多峰状,此时传统的最大功率点跟踪(Maximum Power Point Tracking,MPPT)算法失效,极大地降低了光伏系统能量转换效率。通过对光伏阵列在部分遮挡条件下的P-V特性进行较为深入的...光伏系统在部分遮挡条件下的输出功率-电压(P-V)特性曲线呈多峰状,此时传统的最大功率点跟踪(Maximum Power Point Tracking,MPPT)算法失效,极大地降低了光伏系统能量转换效率。通过对光伏阵列在部分遮挡条件下的P-V特性进行较为深入的实验分析及研究,基于实验分析及研究结果,设计并提出一种全局最大功率点跟踪(Global Maximum Power Point Tracking,GMPPT)算法以弥补传统M PPT算法的缺陷和不足。测试结果表明该算法可以快速实现在部分遮挡条件下全局最大功率点的追踪。展开更多
针对局部阴影条件下光伏阵列的P-V曲线呈现多峰值的情况,在研究光伏阵列输出特性的基础上提出了一种全局最大功率点追踪GMPPT(global maximum power point tracking)算法。该算法由均匀光照和局部阴影条件下的两个最大功率点追踪算法构...针对局部阴影条件下光伏阵列的P-V曲线呈现多峰值的情况,在研究光伏阵列输出特性的基础上提出了一种全局最大功率点追踪GMPPT(global maximum power point tracking)算法。该算法由均匀光照和局部阴影条件下的两个最大功率点追踪算法构成。通过所提出的局部阴影检测手段判别光伏阵列所处的光照条件,从而决定使用哪个子算法。最后将该算法在Matlab中进行仿真验证。仿真结果表明在局部阴影条件下该算法能快速地追踪到全局最大功率点,且避免了对整条P-V曲线的扫描。在均匀光照条件下要比传统的最大功率点追踪算法(扰动观察法)更快地定位到最大功率点。展开更多
A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there ...A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.展开更多
针对光伏系统在部分遮挡条件下的输出功率-电压(P-V)特性曲线具有的多峰性及极值点的分布规律,提出基于改进的扰动观察法和自适应法相结合的GMPPT(Global Maximum Power Point Tracking)方法,重点阐述以TI的TMS320F28027芯片为控制核心...针对光伏系统在部分遮挡条件下的输出功率-电压(P-V)特性曲线具有的多峰性及极值点的分布规律,提出基于改进的扰动观察法和自适应法相结合的GMPPT(Global Maximum Power Point Tracking)方法,重点阐述以TI的TMS320F28027芯片为控制核心的控制方案及实现方法。测试结果表明该系统弥补传统MPPT算法的缺陷和不足,可以快速实现在部分遮挡条件下全局最大功率点的追踪。展开更多
基于对现有多峰值最大功率点跟踪(maximum power point tracking,MPPT)方法不足的分析,提出一种基于功率闭环控制的动态MPPT跟踪策略。该方法采用功率闭环方式实现全局最大功率点的定位,利用功率闭环控制在P-U曲线上的局部不稳定现象实...基于对现有多峰值最大功率点跟踪(maximum power point tracking,MPPT)方法不足的分析,提出一种基于功率闭环控制的动态MPPT跟踪策略。该方法采用功率闭环方式实现全局最大功率点的定位,利用功率闭环控制在P-U曲线上的局部不稳定现象实现P-U曲线的快速全局扫描,克服了峰值点分布及算法参数取值对MPPT动态过程的影响。同时采用电压截止控制克服了功率闭环控制对系统整体稳定性的影响。采用基于粒子群(particle swarm optimization,PSO)算法的变步长跟踪策略消除了最大功率点跟踪的稳态功率震荡问题。最后,通过仿真与实验验证该方法的可行性和有效性,结果表明,该方法不依赖光伏阵列的已知信息,便可实现静态和动态环境下全局最大功率点跟踪,提高多峰值最大功率点跟踪的动态速度和稳态跟踪精度。展开更多
Maximum power point tracking(MPPT) techniques are used to maintain photovoltaic modules operating points at the local maximum power points under non-uniform irradiance conditions(NUIC). For global maximum power point ...Maximum power point tracking(MPPT) techniques are used to maintain photovoltaic modules operating points at the local maximum power points under non-uniform irradiance conditions(NUIC). For global maximum power point tracking(GMPPT) within an appropriate period, a hybrid artificial fish swarm algorithm(HAFSA) is proposed in this paper, which was developed using particle swarm optimization(PSO) to reformulate AFSA and improve its principal parameters. Simulation results show that under NUIC, compared with PSO and AFSA, the proposed algorithm has better performance with respect to convergence speed and convergence accuracy. Under NUIC, the average convergence times for 1000 simulation experiments completed with PSO, AFSA, and HAFSA are 0.4830 s, 0.4003 s and 0.3152 s respectively, and the average tracking time of the HAFSA algorithm is reduced by 34.74% and 21.26% compared with PSO and AFSA, respectively. The convergence times of the velocity inertia ω relative constant and linear decrement method decreased by 35.48% and 8.19%, the convergence time of the Visual relative constant mode decreased by 10.16%, and the convergence time of the Step relative constant mode decreased by 17.88%. The proposed GMPPT algorithm is simulated in MATLAB, and the algorithm tracks GMPP with excellent efficiency and fast speed.展开更多
文摘光伏系统在部分遮挡条件下的输出功率-电压(P-V)特性曲线呈多峰状,此时传统的最大功率点跟踪(Maximum Power Point Tracking,MPPT)算法失效,极大地降低了光伏系统能量转换效率。通过对光伏阵列在部分遮挡条件下的P-V特性进行较为深入的实验分析及研究,基于实验分析及研究结果,设计并提出一种全局最大功率点跟踪(Global Maximum Power Point Tracking,GMPPT)算法以弥补传统M PPT算法的缺陷和不足。测试结果表明该算法可以快速实现在部分遮挡条件下全局最大功率点的追踪。
文摘针对局部阴影条件下光伏阵列的P-V曲线呈现多峰值的情况,在研究光伏阵列输出特性的基础上提出了一种全局最大功率点追踪GMPPT(global maximum power point tracking)算法。该算法由均匀光照和局部阴影条件下的两个最大功率点追踪算法构成。通过所提出的局部阴影检测手段判别光伏阵列所处的光照条件,从而决定使用哪个子算法。最后将该算法在Matlab中进行仿真验证。仿真结果表明在局部阴影条件下该算法能快速地追踪到全局最大功率点,且避免了对整条P-V曲线的扫描。在均匀光照条件下要比传统的最大功率点追踪算法(扰动观察法)更快地定位到最大功率点。
文摘A photovoltaic (PV) string with multiple modules with bypass diodes frequently deployed on a variety of autonomous PV systems may present multiple power peaks under uneven shading. For optimal solar harvesting, there is a need for a control schema to force the PV string to operate at global maximum power point (GMPP). While a lot of tracking methods have been proposed in the literature, they are usually complex and do not fully take advantage of the available characteristics of the PV array. This work highlights how the voltage at operating point and the forward voltage of the bypass diode are considered to design a global maximum power point tracking (GMPPT) algorithm with a very limited global search phase called Fast GMPPT. This algorithm successfully tracks GMPP between 94% and 98% of the time under a theoretical evaluation. It is then compared against Perturb and Observe, Deterministic Particle Swarm Optimization, and Grey Wolf Optimization under a sequence of irradiance steps as well as a power-over-voltage characteristics profile that mimics the electrical characteristics of a PV string under varying partial shading conditions. Overall, the simulation with the sequence of irradiance steps shows that while Fast GMPPT does not have the best convergence time, it has an excellent convergence rate as well as causes the least amount of power loss during the global search phase. Experimental test under varying partial shading conditions shows that while the GMPPT proposal is simple and lightweight, it is very performant under a wide range of dynamically varying partial shading conditions and boasts the best energy efficiency (94.74%) out of the 4 tested algorithms.
文摘针对光伏系统在部分遮挡条件下的输出功率-电压(P-V)特性曲线具有的多峰性及极值点的分布规律,提出基于改进的扰动观察法和自适应法相结合的GMPPT(Global Maximum Power Point Tracking)方法,重点阐述以TI的TMS320F28027芯片为控制核心的控制方案及实现方法。测试结果表明该系统弥补传统MPPT算法的缺陷和不足,可以快速实现在部分遮挡条件下全局最大功率点的追踪。
文摘基于对现有多峰值最大功率点跟踪(maximum power point tracking,MPPT)方法不足的分析,提出一种基于功率闭环控制的动态MPPT跟踪策略。该方法采用功率闭环方式实现全局最大功率点的定位,利用功率闭环控制在P-U曲线上的局部不稳定现象实现P-U曲线的快速全局扫描,克服了峰值点分布及算法参数取值对MPPT动态过程的影响。同时采用电压截止控制克服了功率闭环控制对系统整体稳定性的影响。采用基于粒子群(particle swarm optimization,PSO)算法的变步长跟踪策略消除了最大功率点跟踪的稳态功率震荡问题。最后,通过仿真与实验验证该方法的可行性和有效性,结果表明,该方法不依赖光伏阵列的已知信息,便可实现静态和动态环境下全局最大功率点跟踪,提高多峰值最大功率点跟踪的动态速度和稳态跟踪精度。
基金supported by National Natural Science Foundation of China (No.61501106)Science and Technology Foundation of Jilin Province (No. 20180101039JC and JJKH20170102KJ)
文摘Maximum power point tracking(MPPT) techniques are used to maintain photovoltaic modules operating points at the local maximum power points under non-uniform irradiance conditions(NUIC). For global maximum power point tracking(GMPPT) within an appropriate period, a hybrid artificial fish swarm algorithm(HAFSA) is proposed in this paper, which was developed using particle swarm optimization(PSO) to reformulate AFSA and improve its principal parameters. Simulation results show that under NUIC, compared with PSO and AFSA, the proposed algorithm has better performance with respect to convergence speed and convergence accuracy. Under NUIC, the average convergence times for 1000 simulation experiments completed with PSO, AFSA, and HAFSA are 0.4830 s, 0.4003 s and 0.3152 s respectively, and the average tracking time of the HAFSA algorithm is reduced by 34.74% and 21.26% compared with PSO and AFSA, respectively. The convergence times of the velocity inertia ω relative constant and linear decrement method decreased by 35.48% and 8.19%, the convergence time of the Visual relative constant mode decreased by 10.16%, and the convergence time of the Step relative constant mode decreased by 17.88%. The proposed GMPPT algorithm is simulated in MATLAB, and the algorithm tracks GMPP with excellent efficiency and fast speed.
