105 research outputs found
Modular multilevel converter with modified half-bridge submodule and arm filter for dc transmission systems with DC fault blocking capability
Although a modular multilevel converter (MMC) is universally accepted as a suitable converter topology for the high voltage dc transmission systems, its dc fault ride performance requires substantial improvement in order to be used in critical infrastructures such as transnational multi-terminal dc (MTDC) networks. Therefore, this paper proposes a modified submodule circuit for modular multilevel converter that offers an improved dc fault ride through performance with reduced semiconductor losses and enhanced control flexibility compared to that achievable with full-bridge submodules. The use of the proposed submodules allows MMC to retain its modularity; with semiconductor loss similar to that of the mixed submodules MMC, but higher than that of the half-bridge submodules. Besides dc fault blocking, the proposed submodule offers the possibility of controlling ac current in-feed during pole-to-pole dc short circuit fault, and this makes such submodule increasingly attractive and useful for continued operation of MTDC networks during dc faults. The aforesaid attributes are validated using simulations performed in MATLAB/SIMULINK, and substantiated experimentally using the proposed submodule topology on a 4-level small-scale MMC prototype
A PWM current source-based DC transmission system for multiple wind turbine interfacing
A pulsewidth modulation (PWM) current source wind energy conversion system based on a parallel configuration for high voltage direct current application is proposed. A comparison between the parallel and series configurations for current source-based systems is investigated, which shows the merits of the proposed system. A new control technique for the PWM current source inverter is proposed. It can effectively control the average dc-link voltage with a feed-forward loop, while independently controlling reactive power according to grid code requirements. The system simulation confirms the performance of the proposed system with no interaction between wind turbine modules and satisfying performance with grid integration. Practical implementation further verifies the proposed inverter control. Finally, a brief comparison between conventional line-commutated converter-based systems and the proposed PWM current source converter-based system is presented
Lyapunov-based high-performance controller for modular resonant DC/DC converters for medium-voltage DC grids
This study presents a high-performance controller based on the Lyapunov stability criterion that enhances the dynamic performance and disturbance rejection capability of resonant DC/DC converters when compared with classical PI control. The series–parallel resonant converter (SPRC) is used as the candidate converter to which this controller design is applied but the design can be generalised to other types of resonant DC/DC converters. By using a multiple module approach, low-power modules of this resonant converter are stacked to enable operation at medium-voltage DC (MVDC). The proposed controller design is applied to modular structure of the SPRC to verify its high-performance output in conjunction with active sharing control loops that ensure uniform current/voltage distribution across the multiple interconnected modules. Detailed controller design, closed-loop stability criteria, robustness and parameter sensitivity are investigated and controller performance is compared and verified against the classical PI control in simulation and low-scaled experimental prototype. Operations in single-module and two-module input-series output-parallel modes are both studied. The study affirms the selection of the modular DC/DC converter architecture and its associated proposed controls for high-performance MVDC applications
Hybrid multilevel converter with cascaded H-bridge cells for HVDC applications : operating principle and scalability
Hybrid multilevel converters are contemplated in an attempt to optimize the performance of voltage source converters in terms of magnitude of semiconductor losses and converter footprint, and to achieve additional features such as dc short circuit proof, which is essential for a high integrity multiterminal HVDC grid. Therefore, this paper considers an emerging hybrid cascaded converter that offers the dc side short circuit proof feature at reduced loss and footprint compared to the existing multilevel and other hybrid converters. Its operating principle, modulation, and capacitor voltage balancing strategies are described in detail. Furthermore, hybrid converter scalability to high voltage applications is investigated. The validity of the modulation and capacitor voltage strategy presented are confirmed using simulation and experimentation. The hybrid cascaded converter is extendable to a large number of cells, making it applicable to high voltage applications, and operation is independent of modulation index and power factor. On these ground, the converter is expected to be applicable for both real and reactive power applications
Generalised dq-dynamic phasor modelling of STATCOM connected to a grid for stability analysis
The synchronous dq based small-signal stability using the eigenvalue analysis and impedance methods is widely employed to assess system stability. Generally, the harmonics are ignoredin stability analysis which may lead to inaccuracies in stability predictions, particularly, when the system operates in a harmonic-richenvironment. Typically, the harmonic state-space method (HSS) facilitates stability studies of linear time-periodic (LTP) systems, which considersthe impact of harmonics. The use of the dq-dynamic phasor state space and impedance method offers significant advantages over the HSS counterpart, as it reduces system order, is more suitable for studying control systems, retains mutual coupling of harmonics, and simplifies the stability study under unbalanced conditions. This paper extends dynamic phasor modelling for studying stability of modern power systems that include power converters. It is shown that the proposed method reproduces the typical response of STATCOM at the fundamental frequency as well as at significant low-order harmonics using both eigenvalues and impedance analysis. Quantitative validations of the proposed extended models against synchronous dq small signal models confirm their validity
A new model predictive current controller for grid connected converters in unbalanced grids
Distributed energy resources are often connected to low-voltage distribution networks where the grid voltages may be unbalanced. This leads to an unwanted ripple in the output active power at twice the fundamental grid frequency. In this article, a new model predictive current controller is proposed for unbalanced grids. The variable switching frequency of existing model predictive controllers is fixed and the power quality is improved. A Kalman filter estimator is used to extract the positive and negative sequence components. A new calculation time compensation technique is proposed, which offers superior accuracy to existing approaches. A grid voltage discretization compensation strategy is outlined, and its effectiveness is demonstrated. Finally, the system stability is verified theoretically. Simulation and laboratory results are included to prove the robustness of the proposed controller and support the theoretical analysis
Comprehensive assessment of fault-resilient schemes based on energy storage integrated modular converters for AC-DC conversion systems
Due to the scalability and flexibility of various modular power electronic converters, integrating split energy storage components (such as batteries and supercapacitors) is feasible and attractive. This paper investigates the operational and economic characteristics of different ac/dc fault-resilient schemes using energy storage integrated modular converters in ac-dc conversion applications. Based on the topological features between the energy storage system (ESS) and the ac and/or dc system, four energy storage based modular converter deployment schemes are presented. Through a case study, operational performance including fault isolation and power compensation under extreme ac/dc fault conditions are verified using time-domain simulation. System losses are evaluated, whereas detailed design considerations, major component usage and estimated capital costs are articulated. The four schemes are compared and selection guidelines are presented. In general, the schemes with independent ESSs would be preferable for such ac-dc conversion applications due to their high operational flexibility
Applications of Artificial Intelligence in Thrombocytopenia
Thrombocytopenia is a medical condition where blood platelet count drops very low. This drop in platelet count can be attributed to many causes including medication, sepsis, viral infections, and autoimmunity. Clinically, the presence of thrombocytopenia might be very dangerous and is associated with poor outcomes of patients due to excessive bleeding if not addressed quickly enough. Hence, early detection and evaluation of thrombocytopenia is essential for rapid and appropriate intervention for these patients. Since artificial intelligence is able to combine and evaluate many linear and nonlinear variables simultaneously, it has shown great potential in its application in the early diagnosis, assessing the prognosis and predicting the distribution of patients with thrombocytopenia. In this review, we conducted a search across four databases and identified a total of 13 original articles that looked at the use of many machine learning algorithms in the diagnosis, prognosis, and distribution of various types of thrombocytopenia. We summarized the methods and findings of each article in this review. The included studies showed that artificial intelligence can potentially enhance the clinical approaches used in the diagnosis, prognosis, and treatment of thrombocytopenia
Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis
BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London
Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey
Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020
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