光伏并网发电系统MPPT技术的研究

Research on MPPT Technology for Photovoltaic Grid-connected Generation Systems

光伏电池的发电性能易受外界环境的影响。为使光伏系统输出功率最大化,多种最大功率点跟踪技术用于解决该问题。在不同的环境条件下,这些方法的性能在响应时间和稳定性方面有所不同。在MATLAB/Simulink环境下对增量电导法、改进的扰动观测法和人工神经网络三种最大功率点跟踪算法进行比较分析,对应用不同算法的三相光伏并网发电系统进行仿真,仿真结果表明,与其他方法相比,人工神经网络最大功率点跟踪技术的响应速度更快,稳态振荡更小,低至0.47%。

The power generation performance of photovoltaic cells is easily affected by the external environment.To maximize the output power of a PV system,multiple maximum power point tracking techniques are used to solve this problem.The performance of these methods varies in response time and stability under different environmental conditions.In the MATLAB/Simulink environment,the three maximum power point tracking algorithms of incremental conductivity method,improved disturbance observation method and artificial neural network are compared and analyzed,and the three-phase photovoltaic grid-connected power generation system using different algorithms is simulated.The simulation results show that compared with other methods,the maximum power point tracking technology of artificial neural network has a faster response speed and smaller steady-state oscillation,as low as 0.47%.