Two-level control of photovoltaic systems using global perturbation-based extremum seeking control and model reference adaptive control

One of the main renewable energy sources for the future is photovoltaic (PV) energy. Hence, working of the PV systems at maximum efficiency is taken into consideration in recent years. In this paper, for improving the performance of the global maximum power point tracking under partial shading conditions and uncertainty in parameters of DC-DC converter, a two-level adaptive control scheme is proposed. The proposed controller is capable of efficiently handling the uncertainties in the PV systems and the perturbations in the environment. The first level is global perturbation-based extremum seeking control (GPESC), and the second level is model reference adaptive control (MRAC). GPESC is used to find global maximum power point and MRAC is utilized to handle the dynamics of the DC-DC converter. Adequate difference in the time constants of control levels, causes decoupled control levels, which in turn makes it easy to design the controller. The performance of the proposed control scheme is evaluated through simulation based on four indicators: tracking accuracy, tracking efficiency, tracking speed and searching resolution for different irradiance patterns. The results are compared with GPESC and GPESC with PID controller.