Application perturb and observe maximum power point tracking with interconnection and damping assignment passive-based control for photovoltaic system using boost converter

Introduction. Power generation from renewable sources, such as photovoltaic (PV) power, has become increasingly important in replacing fossil fuels. A PV system’s maximum power point (MPP) moves along its power-voltage curve in response to environmental changes. Despite the use of maximum power point tracking (MPPT) algorithms, the displacement of the MPP results in a decrease in PV system performance. Problem. Perturb & Observe (P&O) MPPT algorithm is a simple and effective algorithm, it can suffer from some drawbacks, such as oscillations around the MPP, slow tracking of rapid changes in irradiance, and reduced efficiency under temperature variation condition. The new MPPT control strategy for a solar PV system, based on passivity control, is presented. The goal of this study is to enhance the efficiency and stability of MPPT in PV systems by integrating the P&O algorithm with Interconnection and Damping Assignment Passivity-Based Control (IDA-PBC). Methodology. The new MPPT P&O PBC strategy aims to extract maximum power from the PV system in order to improve its efficiency under some conditions such as the variations of the temperature, the irradiation and the load. IDA-PBC is employed to design a Lyapunov asymptotically stable controller using the Hamiltonian structural properties of the open-loop model of the system. Also, with minimization of the energy dissipation in boost converter of the PV system to illustrate the modification of energy and generate a specify duty cycle applied to the converter. The results with MATLAB clearly demonstrate the advantages of the proposed MPPT P&O PBC, showcasing its high performance in effectively reducing oscillations in various steady states of the PV system, ensuring minimal overshoot and a faster response time. Scientific novelty. Key contributions include methodological improvements such as dynamic adjustment of the cycle for boost converter and a new approach to partner selection, which significantly optimizes the algorithm’s performance. Practical value. A comparative analysis of the proposed MPPT controller against conventional algorithms shows that it offers a fast dynamic response in finding the maximum power with significantly less oscillation around the MPP. References 46, tables 2, figures 13.