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Recent research has shown that operating grid-connected converters using the grid-forming vector current control (GFVCC) scheme offers significant benefits, including the simplicity and modularity of the control architecture, as well as enabling a seamless transition from PLL-based grid-following control to grid-forming. An important aspect of any grid-connected converter control strategy is the handling of grid-fault scenarios such as symmetrical and asymmetrical short-circuit faults. This paper presents several fault ride-through (FRT) strategies for GFVCC that enable the converter to provide fault current and stay synchronized to the grid while respecting the converter hardware limitations and retaining grid-forming behavior. The converter control scheme is extended in a modular manner to include negative-sequence loops, and the proposed FRT strategies address both symmetrical and asymmetrical faults. The proposed FRT strategies are analyzed through case studies, including infinite-bus setups and multi-unit grids.

Thyristor rectifiers are a well-established and cost-effective solution for controlled high-power rectification, commonly used for hydrogen electrolysis and HVDC transmission. However, small-signal modeling and analysis of thyristor rectifiers remain challenging due to their line-commutated operation and nonlinear switching dynamics. This paper first revisits conventional RMS-based modeling of thyristor rectifiers and subsequently proposes a novel nonlinear state-space EMT model in the dq domain that can be linearized for small-signal analysis. The proposed model accurately captures all the relevant dynamic phenomena, including PLL dynamics, the commutation process, and switching delays. It is derived in polar coordinates, offering novel insights into the impact of the PLL and commutation angle on the thyristor rectifier dynamics. We verify the RMS and EMT models against a detailed switching model and demonstrate their applicability through small-signal stability analysis of a modified IEEE 39-bus test system that incorporates thyristor rectifier-interfaced hydrogen electrolyzers, synchronous generators, and grid-forming converters.

We derive a small-signal transfer function for a system comprising a virtual synchronous generator (VSG), a synchronous generator (SG), and a load, capturing voltage and frequency dynamics. Using this model, we analyze the sensitivity of SG dynamics to VSG parameters, highlighting trade-offs in choosing virtual inertia and governor lag, the limited effect of damper-winding emulation, and several others.

This paper introduces a universal power synchronization controller for grid-side control of the wind turbine conversion systems in an offshore wind farm with a diode rectifier in the offshore substation of the HVDC link. The controller incorporates voltage-power droop controllers in the outer loop to enable the operation of this setup. To effectively handle the impact of large delays during black start and power ramp phases, virtual active and reactive power quantities are defined. These quantities are computed based on the current references prior to any modifications that might be needed to meet converter current and voltage limits or source constraints. Utilizing them in the outer loop ensures a balanced power sharing and a stable operation whenever the original (unmodified) current references are not realized. Case studies confirm the robustness of the proposed controller.

DC microgrids are converter-based electrical networks that are increasingly being used in various applications, including data centers and industrial distribution systems. A central challenge in their operation is maintaining the DC-bus voltage within predefined limits while ensuring overall system stability. Although a wide variety of converter control algorithms has been proposed to achieve these objectives, the literature lacks a clear and physically interpretable framework for evaluating their effectiveness and for classifying and comparing them. Moreover, the grid-forming versus grid-following distinction that exists in AC systems has largely been unexplored in DC microgrids. To address this gap, this paper introduces three novel impedance-based indices that can be used to quantify the voltage-forming and current-forming behavior of a converter. The indices also provide a basis for defining the desired converter behavior that yields superior DC-bus voltage regulation performance. Simulation results illustrate the application of the framework to several representative control strategies and highlight the strengths and limitations of these control algorithms.

Power electronic converters are fundamental building blocks of both AC and DC microgrids, enabling the integration of renewable energy sources, energy storage systems, electronic loads, and electric vehicles. In contrast, converter control in DC microgrids has developed along the path of droop control, which is widely adopted for decentralized DC-bus voltage regulation and power sharing. Although these control strategies share certain characteristics, their similarities remain largely unexplored due to the distinct physical domains in which they operate. To bridge this gap, we introduce a novel perspective based on the concept of duality to reveal the underlying isomorphism between the two control approaches. We show that AC grid-forming and DC I--V droop control are duals of each other in several aspects, including: (i) the small-signal model of the converter; (ii) the inner current control structure; (iii) power-sharing mechanisms based on the AC swing equation and DC capacitor power balance; and (iv) disturbance signals and dynamic response. Theoretical analysis, validated through simulations on simple converter setups, illustrates these dualities and provides new insights towards a unified control design.

DC microgrids are getting more and more applications due to simple converters, only voltage control and higher efficiencies compared to conventional AC grids. Droop control is a well know decentralized control strategy for power sharing among converter interfaced sources and loads in a DC microgrid. This work compares the stability assessment and control of four types of droops for boost converters using the concept of passivity. EN standard 50388-2 for railway systems provides a reference to ensure system stability in perspectives of converters and system integration. Low pass filter (LPF) in the feedback of the droop control is used to ensure converter passivity. Bus impedance is derived to ensure system passivity with less conservativeness. Analytical approach for design of passive controller for all four types of droops is verified through time domain simulations of a single boost converter based microgrid feeding a Constant Power Load (CPL).

Prostate cancer that progresses after enzalutamide treatment is poorly responsive to further antiandrogen therapy, and paradoxically, rapid cycling between high and low serum testosterone concentrations (bipolar androgen therapy [BAT]) in this setting might induce tumour responses. We aimed to evaluate BAT in patients with metastatic castration-resistant prostate cancer that progressed after enzalutamide. We did this single-centre, open-label, phase 2, multicohort study in the USA. We included patients aged 18 years or older who had histologically confirmed and radiographically documented metastatic castration-resistant prostate cancer, with no more than two previous second-line hormonal therapies, and a castrate concentration of testosterone. Patients were asymptomatic, with Eastern Cooperative Oncology Group performance status of 0–2, and did not have high-risk lesions for tumour flare (eg, >5 sites of visceral disease or bone lesions with impending fracture). For the cohort reported here, we required patients to have had progression on enzalutamide with a continued prostate-specific antigen (PSA) rise after enzalutamide treatment discontinuation. Patients received BAT, which consisted of intramuscular testosterone cipionate 400 mg every 28 days until progression and continued luteinising hormone-releasing hormone agonist therapy. Upon progression after BAT, men were rechallenged with oral enzalutamide 160 mg daily. The co-primary endpoints were investigator-assessed 50% decline in PSA concentration from baseline (PSA50) for BAT (for all patients who received at least one dose) and for enzalutamide rechallenge (based on intention-to-treat analysis). These data represent the final analysis for the post-enzalutamide cohort, while two additional cohorts (post-abiraterone and newly castration-resistant prostate cancer) are ongoing. The trial is registered with ClinicalTrials.gov, number NCT02090114. Between Aug 28, 2014, and May 18, 2016, we accrued 30 eligible patients and treated them with BAT. Nine (30%; 95% CI 15–49; p<0·0001) of 30 patients achieved a PSA50 to BAT. 29 patients completed BAT and 21 proceeded to enzalutamide rechallenge, of whom 15 (52%; 95% CI 33–71; p<0·0001) achieved a PSA50 response. During BAT, the only grade 3–4 adverse event occurring in more than one patient was hypertension (three [10%] patients). Other grade 3 or worse adverse events occurring during BAT in one [3%] patient each were pulmonary embolism, myocardial infarction, urinary obstruction, gallstone, and sepsis. During enzalutamide retreatment, no grade 3–4 toxicities occurred in more than one patient. No treatment-related deaths were reported during either BAT or enzalutamide retreatment. BAT is a safe therapy that resulted in responses in asymptomatic men with metastatic castration-resistant prostate cancer and also resensitisation to enzalutamide in most patients undergoing rechallenge. Further studies with BAT are needed to define the potential clinical role for BAT in the management of metastatic castration-resistant prostate cancer and the optimal strategy for sequencing between androgen and antiandrogen therapies in metastatic castration-resistant prostate cancer to maximise therapeutic benefit to patients. National Institutes of Health and National Cancer Institute.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. This study utilised genetic and clinical data ( = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. The best performing linear model explained 5.1% ( = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% ( = 0.0001) of variance in lithium response. genomic stratification improved non-linear model performance to 13.7% ( = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.