Abstract
The adoption of Distributed Generation (DG) systems, such as photovoltaic (PV) panels, is increasing due to their environmental advantages and potential to lessen reliance on fossil fuels. However, Renewable Energy Sources (RES) like PV can cause Power Quality (PQ) issues, including voltage and current harmonics, which negatively impact grid stability and efficiency. To mitigate these problems, this study introduces a Hybrid Active Power Filter (HAPF). This filter, powered by a high-gain Interleaved Luo (I-Luo) Converter fed by a PV system, effectively reduces harmonic distortions, addresses reactive power issues, and stabilizes voltage in the distribution network. To further enhance the converter's performance, a Modified Squirrel Search-based PI controller is implemented. Known for its robust and efficient convergence, this optimization algorithm adjusts the PI controller settings to improve dynamic response and ensure precise harmonic compensation. Additionally, a Recurrent Neural Network (RNN)-based harmonic extraction technique is employed to accurately identify and quantify harmonic components in voltage and current waveforms, enabling precise HAPF control. Simulations conducted in MATLAB demonstrate that the integration of RNN-based harmonic extraction, HAPF, and the I-Luo Converter with Modified Squirrel Search optimization significantly enhances Power Quality in DG systems.
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