Filtered X least mean fourth‐driven intelligent control for power quality augmentation and dynamic stability reinforcement of grid intertie wind–photovoltaic systems

Abstract

SummaryAn advanced topology comprising a wind‐turbine driven synchronous generator (SG) and solar photovoltaic (PV) array to address the power quality (PQ) concerns and the uncertainty in renewable energy generation is proposed in this paper. The fluctuations in wind speed and insolation are soaked up by utilizing successively interfaced power electronic converters (PECs), namely, SG side converter (SGC) and utility grid side converter (UGC) integrated with a DC link capacitor and a PV array. SGC is controlled by estimating the rotor position from the stator voltage and current measurement data and maintains unity power factor (UPF) at stator terminals. UGC is controlled by employing filtered X least mean fourth (FXLMF) control, which ensures superior convergence performance and reduced computational complexity. Besides, it performs operations like reactive power compensation, enhancement of PQ, load and power balancing during steady‐state and dynamic conditions. The notion of optimal fuzzy reasoning is instilled which generates a fuzzy scheme with inherent optimal‐tuning characteristics to bring about considerable improvement in system performance. A water cycle algorithm (WCA) tuned fuzzy logic controller (FLC) is employed for dynamic stability enhancement leading to the generation of accurate loss component, , which bolsters the ability of VSC to accurately extricate weight signals and the fundamental load current component. This improves regulation of DC link voltage during dynamic load, insolation and wind conditions. The veracity of the proposed model is verified under wind gusts and the bell‐shaped irradiance curve. Extensive simulation results obtained in MATLAB corroborate the efficacy of the system.