Power quality assessment using signal periodicity independent algorithms – A shipboard microgrid case study. (1st February 2022) - Terriche, Yacine; Lashab, Abderezak; Çimen, Halil; Guerrero, Josep M.; Su, Chun-Lien; Vasquez, Juan C.
Highlights: Investigating and revealing potential risks of poor energy quality for shipboard microgrids. Providing a clear view of the importance of selecting the accurate algorithms for analyzing the quality of energy and delivering a comparative study. Proposing a developed algorithm, which is an offline-based energy quality analyzing technique developed for the short-term protective action stage to assess the energy quality of shipboard microgrids. Proposing an enhanced algorithm, which is an online-based energy quality assessing technique, Which is very suitable for the long-term preventive action stage. Abstract: Retrofitting of shipboard microgrids is receiving much attention nowadays due to the flexibility it offers to adapt existing ships with rapid market variations to move towards all-electric ships (A-ESs). This modernity mainly relies on incorporating the power electronics converters that unfortunately draw a large number of harmonics, which affect the energy quality and threaten the system stability and crew/passengers safety. The contribution of this paper lies in proposing two developed open-loop algorithms to assess the harmonics distortion of A-ESs without relying on signal periodicity. The first algorithm is an offline-based analyzing technique developed for the short-term protective action stage, which incorporates the eigenvalue solution inside the short-time fast Fourier transform (ST-FFT) to adapt its window size. Consequently, this algorithm can provide a comprehensive harmonics analysis with a fast transient response even under large system frequency drifts. The second algorithm is an online-based assessing technique, which is very suitable for the long-term preventive action stage to provide accurate harmonics distortion assessment with the fast transient response and efficient computation burden. This approach relies on cascading three moving average filters (MAFs) with particular window sizes to filter and estimate the mean value inside the discrete Fourier transform and the true RMS blocks without the need of frequency information. Hence, it results in enhancing the harmonics rejection capability of the algorithm even under the existence of non-characteristic harmonics and frequency drifts. Simulation and experimental results are provided to validate the efficacy of the proposed algorithms and the results are compared with traditional methods.