Sensitivity analysis to model parameter errors of MPPT by model predictive control for photovoltaic applications

Abstract

Due to variability of solar energy resources, maximum power point tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point (MPP) and maximize the energy harvest. This paper presents a digital model predictive control technique to employ the MPPT for flyback converter for photovoltaic applications. The MPP operating point is determined by using perturb and observe (P&O) technique. The proposed two-steps predictive model based MPPT presents significant advantages in dynamic response and power ripple at steady state. A characteristic of MPC is the use of system models for selecting optimal actuations, thus evaluating the effect of model parameter mismatch on control effectiveness is of interest. In this paper the load model is eliminated from the proposed MPC formulation by using an observer based technique. The sensitivity analysis results indicate a more robust controller to uncertainty and disturbances in the resistive load.I.

Effect of model parameter errors in model predictive control applications

“…Algunos trabajos relacionados al análisis de la incertidumbre de los valores de parámetros son: la evaluación de la sensibilidad para aplicaciones de sistemas fotovoltaicos [8], evaluación del desempeño del controlador [7], análisis de sensibilidad paramétrica en una máquina de inducción [9] y en una máquina síncrona de imanes permanentes [10], [11], análisis de sensibilidad por variación del valor de inductancia [12], entre otros. En [13] se propone un método de identificación de parámetros adaptivo basado en la optimización de descenso de gradiente para un sistema de convertidor conectado a la red.…”