基于PSO-PSA的光伏系统最大功率点跟踪技术

Maximum power point tracking technology based on hybrid algorithm of PSO and PSA for photovoltaic systems

为弥补恒定电压法实现最大功率点跟踪时忽略外界条件变化的缺陷,提高其跟踪精度和光伏系统的发电效率,本文提出了基于混合粒子群-模式搜索算法(PSO-PSA)的光伏发电最大功率点跟踪方法。对光伏电池模型进行仿真分析,绘制其在外界条件变化的情况下的输出特性曲线,分析环境变化对最大功率点的影响;通过对比PSO-PSA与粒子群算法,对基准测试函数的求解速度、精度与稳定性,验证本文算法的有效性,进而在不同环境条件下将混合算法优化输出结果与模型输出结果进行对比;将PSO-PSA与光伏阵列结合应用到Boost电路,实现模型动态输出结果与理论计算值匹配,从而实现最大功率点的有效跟踪。结果表明:基于PSO-PSA的光伏系统最大功率点跟踪技术合理,跟踪精度较高,弥补了使用固定电压值时无法适应环境改变而造成能源浪费的不足。

The constant voltage tracking（CVT） method usually neglects the change of external conditions during the maximum power point tracking（MPPT） process, to enhance the tracking accuracy and electricity generation efficiency of the photovoltaic systems, an MPPT method for photovoltaic（PV） system based on the hybrid algorithm using particle swarm optimization（PSO） algorithm and pattern search algorithm（PSA） was proposed. Simulation and analysis on the PV cell model were carried out, and the output characteristic curves under the change of external conditions were plotted to observe the effects of environmental condition change on the maximum power point. The convergence rate, accuracy and stability in the process of solving benchmark function were compared with that of the PSO algorithm, to verify the effectiveness of the PSO-PSA method. Then the outputs of the simulation model and hybrid algorithm optimization in different environments were compared, which verified that the latter has a higher accuracy. Finally, to match the dynamic output of the model and the theoretical calculating value, the control structure based on the PSO-PSA and PV array was combined and applied to the Boost circuit, which achieved the maximum power point tracking effectively. The results show the PSO-PSA-based MPPT technology for PV system has reasonable technology basis and high tracking accuracy, which compensates the lack of energy waste when using the CVT method.