Correlation Analysis of Power Quality and Power Spectrum in Wind Power Hybrid Energy Storage Systems

Abstract

Power quality is a crucial area of research in contemporary power systems, particularly given the rapid proliferation of intermittent renewable energy sources such as wind power. This study investigated the relationships between power quality indices of system output and PSD by utilizing theories related to spectra, PSD, and random signal power spectra. The relationship was derived, validated through experiments and simulations, and subsequently applied to multi-objective optimization. Various optimization algorithms were compared to achieve optimal system power quality. The findings revealed that the relationships between power quality indices and PSD were influenced by variations in the order of the power spectral estimation model. An increase in the order of the AR model resulted in a 36% improvement in the number of optimal solutions. Regarding optimal solution distribution, NSGA-II demonstrated superior diversity, while MOEA/D exhibited better convergence. However, practical applications showed that while MOEA/D had higher convergence, NSGA-II produced superior optimal solutions, achieving the best power quality indices (THDi at 4.62%, d% at 3.51%, and cos φ at 96%). These results suggest that the proposed method holds significant potential for optimizing power quality in practical applications.