A Robust Optimization Technique Based on First Order Sliding Mode Approach for Photovoltaic Power Systems

This paper deals with the problem of the energy system optimization for photovoltaic generators. A great necessity of optimizing the output energy appears as a result of the nonlinearity of the photovoltaic generator operation besides its variable output characteristic under different climatic conditions. As a consequence for the big need to extract maximum energy, many solutions have been proposed in order to have a good operation at the optimum power for photovoltaic systems. In this paper, we further extend this work by using a robust optimization technique based on the first order sliding mode approach to cope with the uncertainty in photovoltaic power generation caused by weather variability and load change. Indeed, we examine by using this control approach the effectiveness of this method and we note the different performance that affects to the system operation. The first order sliding mode maximum power point tracking controller is presented in detail in this paper. Then, a detailed study of algorithm stability has been carried out. The robustness and stability of the proposed sliding mode controller are investigated against load variations and weather changes. The simulation results confirm the effectiveness, the good and improved performance of the proposed sliding mode method in the presence of load variations and environment changes for direct current/direct current (DC/DC) boost converter.