Model-Free Tracking Control of PV Grid-Connected Systems

Solar energy is one of the most popular renewable energy sources used to address the energy crisis and decrease the amount of pollution resulting from the extensive use of fossil fuels. Photovoltaic (PV) systems are used to effectively convert sunlight energy to electricity [1]. The PV systems are categorized as either independent (standalone) or grid-connected systems. Due to the massive potential market on integrating solar energy into the distribution networks, the PV grid-connected systems have attracted more attention in the power and energy sector than the autonomous standalone PV systems. Various power electronic components are currently being added to the power network infrastructure that is required to ensure the stability and robustness of the power system while maximizing the penetration of PV renewable energy systems. This results in complex dynamical systems that are highly nonlinear and with various unknown parameters. Additionally, with the advances in data-driven systems, various components in the power system will be represented by black-box functions and thus classical model-based control techniques might not apply. In this research project, we propose a Model-Free Tracking Controller (MFTC) to match a predicted output of a PV grid-connected system to a target reference signal. The main idea is to incorporate real-time derivative-free optimization algorithms in the control loop with the purpose of optimizing a desired tracking objective function. The use of derivative-free control algorithms will enable the design of objective functions that rely on black-box functions obtained by data-driven systems.