This paper presents an adaptive linear neuron (Adaline) algorithm designed to extract resonance current from the supply current directly. It aims to reduce the computation burden while upholding efficacy in the extraction process. The approach involves establishing the primary power system, evaluating harmonic and resonance current impacts, formulating efficient extraction strategies based on current waveform characteristics, employing the Adaline algorithm for extraction, and constructing a single-phase shunt active power filter (SAPF) to address harmonic currents and parallel resonance effects. Comparative analysis demonstrates the Adaline algorithm’s precision in extracting current amplitudes pre- and post-SAPF implementation. However, observed disparities in extracted resonance current amplitude may stem from the algorithm’s limitations in capturing low-amplitude signals. While a gain adjustment effectively boosts amplitude. However, it introduces considerable ripple and inconsistency, likely linked to parallel resonance effects. Notably, the SAPF exhibits simultaneous harmonic compensation and resonance damping capabilities. Results affirm the SAPF’s effectiveness in reducing harmonic components across all frequencies, including resonance frequency. Furthermore, resonance damping is crucial for further improving SAPF performance and reducing resonance current. This results in significantly improved waveform quality and reduced total harmonic distortion (THD) and individual harmonic distortion (THDi) values of compensated supply current.
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