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The grid forming (GFM) converter may undesirably output a higher current during the recovery stage than fault duration due to its transient angle swing, which would cause the power devices to face the risk of overcurrent or even damage in both the fault stage and the recovery stage. In this letter, the current power angle plane is presented for the current trajectory description and the mechanism of the recovery overcurrent (ROC) issue is revealed through the proposed concept of critical recovery angle (CRA). On top of that, the power angle relationship in the critical ROC state is described in detail and the ROC boundary is further characterized accurately. Moreover, an analytical calculation method of CRA is proposed to identify whether the ROC phenomenon occurs, which is well validated by a series of experiments. The proposed method depicts the inherent relationship between the current behavior and power angle motion of GFM converters quantitatively and intuitively, and it may provide some new insights into the transient analysis and control optimization of GFM converters.

The islanding detection method (IDM) with current disturbance of selected frequency (CDSF) in dc microgrids is gaining extensive attention thanks to its small nondetection zone and good power quality. However, the CDSF is implemented through a positive feedback loop and thus will lead to instability issues for the dc microgrid even in the grid-connected mode. Conventional stabilization control is generally employed on the distributed generator (DG) side and usually requires an additional uninterrupted communication process, which therefore decreases system reliability. In this article, the impedance model of the dc microgrid is established first to reveal the interaction instability mechanism between the voltage source converter (VSC) and DG equipped with CDSF IDM. On top of that, the notch-filter-based active damping method is proposed on the VSC side to avoid amplitude intersection of impedance near the selected resonant frequency, which effectively mitigates the instability caused by the islanding detection loop without relying on communication. Moreover, the parameter design method is further summarized to provide guidance for the selection of notch bandwidth in the proposed damper. In this manner, the stability of the grid-connected system can be improved while the islanding detecting speed is enhanced. In the end, the effectiveness of the proposed stabilizing method is verified by the experiments.

The damping effect in grid forming (GFM) control is inherently large and thus has great impact on its transient stability. Although qualitative understanding of damping has been developed in recent studies, an analytical and intuitive method for quantitative assessment of damping is still needed to be developed to date. This article visualizes the transient damping energy through the concept of damping area on a tailored phase portrait to physically and intuitively understand the damping effect. On top of that, the damping energy approximation (DEA) method is further proposed to depict transient stability boundary more accurately and evaluate the critical clearing angle analytically. Moreover, the conservativeness of proposed DEA method for GFM converter with both constant terminal voltage control and reactive power-voltage droop control is analyzed in theory and verified in time-domain simulations and control hardware-in-loop experiments. This method quantitatively and visually evaluates the impact of damping on transient stability boundary and critical clearing angle, which avoids complex numerical iterations and may provide some insights into the transient stability analysis of GFM converter.

Islanding detection based on current disturbance of selected frequency (CDSF) is gaining widespread acceptance in dc microgrids due to its high detecting accuracy and good power quality. However, the selected static disturbance frequency at a specific operating state causes the expansion of the nondetection zone (NDZ) and the decrease of the detection speed under different system power conditions. In this article, the sensitivity model of current perturbation is developed to intuitively reveal the mechanism of oscillation frequency shift and the occurrence of the NDZ. Then, the theoretical resonant frequency is derived to analyze the frequency shift range with the consideration of system power changing, which provides the NDZ boundaries accurately. Moreover, an islanding detection method (IDM) with the adaptive resonant frequency is proposed to provide zero NDZ and fast detection speed by dynamically selecting the most sensitive frequency in different power operating cases. Thus, the conflict between the NDZ and detection speed is effectively addressed. Finally, the effectiveness of the proposed IDM is validated by both the simulations and experimental results.

Alzheimer’s disease (AD) is a neurodegenerative disease and a common cause of dementia among elderly individuals. The disease is characterized by progressive cognitive decline, accumulation of senile amyloid plaques and neurofibrillary tangles, oxidative stress, and inflammation. Human-derived cell models of AD are scarce, and over the years, non-human-derived models have been developed to recapitulate clinical AD, investigate the disease’s pathogenesis and develop therapies for the disease. Several pharmacological compounds have been developed for AD based on findings from non-human-derived cell models; however, these pharmacological compounds have failed at different phases of clinical trials. This necessitates the application of human-derived cell models, such as induced pluripotent stem cells (iPSCs) in their optimized form in AD mechanistic studies and preclinical drug testing. This review provides an overview of AD and iPSCs. The AD-relevant phenotypes of iPSC-derived AD brain cells and the usefulness of iPSCs in AD are highlighted. Finally, the various recommendations that have been made to enhance iPSC/AD modelling are discussed.