CONTROL ALGORITHMS MODELLING AND ANALYSIS FOR GRID-INTEGRATED SOLAR PV SYSTEM

Abstract

In order to achieve sustainable growth, the integration of renewable energy sources, such as solar photovoltaic (PV) energy, with conventional energy sources is necessary. This requires advanced power systems equipped with modern theories and approaches. By integrating solar PV energy generation with the grid, the growing energy demand can be met while also acting as a stabilizing factor for the grid. This integration reduces the burden on the grid, minimizes losses through transmission and distribution lines, mitigates congestion, and enhances the overall grid's efficiency. To ensure smooth integration, various components are employed, including the voltage source converter (VSC), which converts the DC power from the solar PV system into AC power for the grid. To prevent high-frequency switching ripples from being injected into the grid, filters are added at the output terminals of the VSC. Synchronization between the grid and VSC voltage in terms of frequency and phase angle is crucial. Loss of synchronization can have catastrophic effects on the entire grid system. Another important aspect that needs attention is power quality (PQ). To mitigate PQ issues and avoid grid malfunctioning, several control algorithms have been developed. In this thesis, a novel Modified Versoria based Zero Attraction-LMS (MVZA-LMS) control algorithm is proposed. This algorithm incorporates a penalty factor based on the Versoria function into the basic Least Mean Square (LMS) algorithm to enhance its zero-attraction capability. The enhanced zero-attraction capability of the proposed algorithm improves convergence rate and modeling accuracy. The zero-attraction topology offers reduced computational complexity, easy implementation, and enhanced steady-state performance compared to other control algorithms. Examples of zero attraction-based LMS techniques include the Robust ZA-LMS (RZA-LMS) technique, the polynomial zero-attraction (PZA)-LMS control algorithm, the l0-LMS technique, and the ZA-LMS technique. The proposed control scheme focuses on maximizing power extraction from the PV array while addressing power quality concerns, including harmonics elimination, load balancing, and power factor improvement under time-varying scenarios. The MVZA LMS algorithm enhances the dynamic performance, resulting in improved response vi time and system robustness. This control scheme effectively addresses power quality issues and conditions the current by adjusting its weight component, especially when working with an underdeveloped grid that exhibits inferior power quality due to voltage distortions and imbalances. The performance of the proposed control scheme is compared with other zero attraction-LMS techniques, and MATLAB-Simulink is utilized for simulation and analysis. The proposed algorithm demonstrates improved efficacy in various situations, thereby increasing the efficiency of grid-tied solar PV systems.