光伏组件双二极管模型参数辨识混合方法研究

Research on hybrid method for parameter identification of the twodiode model of PV modules

精确建立光伏组件的数学模型是进行光伏发电系统理论研究的基础。针对单二极管模型精度低、双二极管模型参数过多求解困难的问题,在不做任何近似处理的前提下,以双二极管模型为基础,提出基于自适应混沌粒子群算法的混合求解方法,兼顾了模型精度和算法复杂度。该方法仅利用标准条件下的短路电流、开路电压、最大功率点电压、最大功率点电流、电压温度系数和电流温度系数这6个参数便可求解出一般工况下模型的各个参量。对不同类型的光伏组件,在不同的运行条件下进行光伏特性仿真,验证了所提出方法的有效性和精确性。

Accurately establishing the mathematical model of PV modules is the basis of theoretical research of PV power generation systems.Aiming at the problems that low accuracy of the single-diode model and difficult solution of the two-diode model because of its too many parameters,without any approximation,a hybrid method based on adaptive chaotic particle swarm optimization(ACPSO)was presented,which was based on the two-diode model and took into account both model accuracy and algorithm complexity.In this method,the parameters of the model can be obtained by using only six parameters at the standard test condition,namely the short-circuit current,the open-circuit voltage,the voltage and current at maximum power point,the temperature coefficients for open-circuit voltage and short-circuit current.The effectiveness and accuracy of the proposed method were verified by PV characteristic simulation for different types of PV modules at different conditions.