并网光伏系统通常以最大功率模式运行,无法全面响应电网调节需求,因此需要研究功率备用控制(power reserve control,PRC).基于最大功率点估计(maximum power point estimation,MPPE)的 PRC 利用光伏等效模型,通过数据拟合实现MPPE,从而实现光伏功率备用.然而,随着光伏组件老化,MPPE估计误差增大,可能影响系统安全稳定运行.文中提出考虑光伏组件老化时MPPE模型参数校准的光伏系统PRC.首先提出基于麻雀搜索算法的MPPE模型参数校准方法,然后根据光伏组件老化特性和MPPE误差演变趋势,提出MPPE模型校准的改进评价指标和校准周期整定原则,最后将其应用于基于MPPE的PRC中.仿真结果表明,该方法能够实现光伏组件老化后MPPE模型参数自动校准,并且显著提高了 MPPE精度,增强了 PRC在实际应用中的可靠性.
Power reserve control of photovoltaic system considering parameter correction in maximum power point estimation
The grid-connected photovoltaic(PV)systems generally operate in the maximum power mode,where they are unable to fully respond to the adjustment requirements of the power grid.Therefore,research on power reserve control(PRC)for PV systems is needed.The maximum power point estimation(MPPE)-based PRC applies the equivalent model of a PV module to realize power reserve in the PV system,where the MPPE is conducted based on curve fitting.However,with the aging of PV modules,the error in MPPE increases,potentially impacting the stability and security of the system.A PRC method for PV systems that considers the correction of model parameters in MPPE as PV modules age is proposed in this paper.Firstly,a correction method for model parameters in MPPE is proposed based on the sparrow search algorithm.Then,considering the aging characteristics of PV modules and the evolution trend of MPPE error,an improved assessment criterion for the correction of MPPE model and the tuning principle of correction periods are proposed and finally applied to the MPPE-PRC method.Simulation results show that the proposed method can automatically correct the model parameters in MPPE as PV modules age.It can significantly improve the MPPE accuracy and enhance the reliability of PRC in practical applications.
photovoltaic(PV)systempower reserve control(PRC)photovoltaic single-diode modelmaximum power point estimation(MPPE)model parameter correctionsparrow search algorithm
万方数据
维普
