PowerELab (China)

Power converters generate noise signals during switching transient and this kind of noise signal is considered as electromagnetic interference (EMI). It is general to use passive EMI filter to block the propagation of EMI noise. Though, this method is feasible for different kinds of applications, it suffers from the intrinsic drawbacks of passive filtering components. To cope with this problem, active EMI filter is a good alternative considering size reduction and good noise attenuation. During the usage and testing of active EMI filter, the noise attenuation performance of active EMI filter is highly related with the impedance relationship close to active EMI filter. To find out the universal design principle of active EMI filter, this paper studies the equivalent noise model considering active EMI filter and the impedance of noise propagation path. Based on the theoretical analysis, when impedance mismatch is built, the noise attenuation achieved by active EMI filter is obvious. Experimental verification shows that when active EMI filter works under impedance mismatch situation, the noise attenuation and frequency response could be much better.

Supplying 80% of Hong Kong’s population with electricity, CLP Power Hong Kong Limited (CLP Power) strives for excellence in reliability and safety despite challenges such as increasing adverse weather events. While protection systems are the foundation for the safe operation in the case of system disturbance, CLP Power implements a holistic approach to minimise the emergence of a disturbance and, if it does occur, to accelerate supply restoration time. This paper therefore introduces four initiatives as examples for this holistic approach. In the pre-disturbance phase, the Asset Health Management System (AHMS) and AI-supported drone-based condition monitoring allow condition-based maintenance to prevent potential disturbances. Post-disturbance, to quickly return to normal operation and restore supply, CLP Power has deployed an automatic restoration system and solutions using the Advanced Metering Infrastructure (AMI). These solutions increase supply reliability and safety, enhance operational efficiency and resources allocation.

The reliability and efficiency of wind turbines are crucial for maximizing energy production and ensuring the economic viability of wind farms. This study introduces a machine learning-based predictive maintenance pipeline designed to monitor and forecast critical faults within wind turbine systems. By leveraging Supervisory Control and Data Acquisition (SCADA) systems and comprehensive event log datasets, the pipeline incorporates advanced feature engineering techniques, along with Mutual Information and Lasso Regression, to identify and select the most relevant operational parameters. Four sophisticated classifiers LightGBM, XGBoost, Random Forest, and Multilayer Perceptron (MLP) are employed and optimized using Genetic Algorithms (GAs), ensuring high predictive accuracy and robustness. The models address five different fault types, including generator overheating, gearbox oil issues, and fan failures. Compared to a majority-class baseline, the optimized models achieved macro-averaged accuracy exceeding 97 percent and $\mathbf{F 1}$-scores ranging from $\mathbf{8 5 \%}$ to $\mathbf{9 7 \%}$ across the five fault types, demonstrating their capability to capture complex, nonlinear relationships inherent in SCADA data. The multi-class, time-aware classification framework categorizes faults into distinct time intervals ($0-24$ hours, 24-48 hours, 2-7 days, 1-4 weeks, and over 1 month), providing actionable time-to-failure predictions. By accurately predicting faults, the system facilitates proactive maintenance interventions, optimizing maintenance scheduling and resource allocation, and extending the lifespan of critical turbine components. This shift from reactive to proactive maintenance not only maximizes energy production but also enhances asset reliability and operational cost efficiency.

Large diameter driven steel tubular piles have been used as the foundations for the recently completed Hong Kong Offshore LNG Terminal located in the southern waters of Hong Kong to the east of Soko Islands. A large number of PDA tests have been conducted for assessing the pile capacity of the offshore piles and gauging the development of pile resistance with time. This has provided a good opportunity to better understand the behaviour of offshore piles in Hong Kong. Analyses of the PDA test data are presented to explore the relationship of pile capacity predicted by the Case method and CAPWAP method and also variation of energy transfer and development of pile resistance over time after the end of initial driving. A simpler approach for describing the set-up curve of pile capacity is also proposed.

Abstract Due to intermittent renewable energy and fluctuating load demand, distribution networks with renewable distributed generation (DG) installations are more likely to suffer voltage issues and significant power losses. The performance of conservation voltage regulation (CVR) schemes may be adversely affected by the undesirable voltage profile at specific nodes. This paper aims to reduce power losses in CVR‐implemented networks by optimally planning new renewable DGs without changing the existing ones. A scenario‐based optimal renewable DG planning model is proposed with a novel scenario formation method. The uncertainties of load demand and renewables are captured jointly and formed into a finite number of scenarios based on a multivariate Gaussian mixture model (MultiGMM). The locations and capacities of different types of new renewable DGs are optimally planned for CVR performance improvements on power loss saving by aggregating the operation status and probabilities of the scenarios using mixed‐integer non‐linear programming (MINLP). A time‐series simulation is formulated for accuracy verification. The results of case studies show that the proposed model can significantly reduce power losses, active load demand, and reactive load demand. The accuracy of the planning results can be guaranteed with fewer scenarios compared to a widely used classical scenario‐based planning method.

Physical activity (PA) and obesity may alter the risks of cardiac conduction disease. Participants from the Kailuan cohort, who were free of cardiac conduction disease and with repeated measurements of electrocardiogram from 2006 to 2019, were included. The primary outcome was cardiac conduction disease. The secondary outcomes were atrioventricular block and intraventricular block. Cox regression was used to assess the association between obesity, PA, and the risks of the outcomes. Influences of PA on the associations between BMI and incident outcomes were evaluated. A total of 84,022 participants (mean age 50.15 years, SD 11.69; 80.3% male) were included. Over a median follow-up of 11.83 years (IQR 8.87–13.04), 3236 participants developed the primary outcome. After multivariable adjustment, a higher body mass index (BMI) and a higher waist circumference (WC) were associated with increased risks of conduction disease, but more PA was associated with a lower risk. For obese patients defined by BMI with low PA, the risk of conduction disease was higher than that of obese patients with high PA (HR: 1.42, CI: 1.21-1.66 vs. HR: 1.16, CI: 1.03–1.31). For central obese patients defined by WC with low PA, the risk of conduction disease was also higher compared to central obese patients with high PA (HR: 1.31, CI: 1.17–1.48 vs. HR: 1.12, CI: 1.03–1.23). Besides, compared to obesity with high PA, obesity with low PA was associated with a higher risk of atrioventricular block (HR: 1.70, CI: 1.28-2.27 vs. HR: 1.45, CI: 1.16-1.81) and intraventricular block (HR: 1.37, CI: 1.13-1.65 vs. HR: 1.03, CI: 0.92–1.15). Higher PA can reduce the risks of developing cardiac conduction disease, both in the obese and non-obese groups. (Clinical Trial Registration URL: https://www.chictr.org. Unique identifier: ChiCTRTNC-11001489).

This study investigates the feasibility of utilizing the line loss power factor to assess the reactive, unbalanced, and harmonic line losses in low-voltage distribution networks and explores the method of calculating decoupled line loss values based on this factor. To achieve this objective, we establish preliminary definitions of single-phase and three-phase reactive, unbalanced, and harmonic line loss power factors, drawing upon the principles of electrical theory outlined in IEEE Standard 1459. These power factors serve as crucial indicators for evaluating the severity of line losses caused by reactive power, unbalance, and harmonic problems. Subsequently, the values of line loss attributed to reactive, unbalanced, and harmonic components are decoupled and quantified using the line loss power factor as a fundamental parameter. The effectiveness and accuracy of the proposed method were verified in Matlab simulation and physical experiments.

Immune checkpoint inhibitors (ICI)are increasingly used in the first-line treatment of malignant tumors. There is increasing recognition of their cardiotoxicity and, in particular, their potential to lead to myocarditis. Cardiovascular magnetic resonance (CMR)can quantify pathological changes, such as myocardial edema and fibrosis. The purpose of this systematic review and meta-analysis was to examine the evidence for the roles of CMR in predicting prognosis in ICI-associated myocarditis. PubMed, Cochrane Library, and Web of Science databases were searched until October 2023 for published works investigating the relationship between CMR parameters and adverse events in patients with ICI-associated myocarditis. The analysis included studies reporting the incidence of late gadolinium enhancement (LGE),T1 values, T2 values, and CMR-derived left ventricular ejection fraction (LVEF).Odds ratios (OR)and weighted mean differences (WMD)were combined for binary and continuous data, respectively. Newcastle-Ottawa Scale was used to assess the methodological quality of the included studies. Five cohort studies were included (average age 65-68 years; 25.4% female). Of these, four studies were included in the meta-analysis of LGE-related findings. Patients with major adverse cardiovascular events (MACE)had a higher incidence of LGE compared with patients without MACE (OR = 4.18, 95% CI: 1.72-10.19, p = 0.002). A meta-analysis, incorporating data from two studies, showed that patients who developed MACE exhibited significantly higher T1 value (WMD = 36.16 ms, 95% CI: 21.43-50.89, p < 0.001) and lower LVEF (WMD = - 8.00%, 95% CI: -13.60 to -2.40, p = 0.005). Notably, T2 value (WMD = -0.23 ms, 95% CI: -1.86 to -1.39, p = 0.779) was not associated with MACE in patients with ICI-related myocarditis. LGE, T1 value, and LVEF measured by CMR imaging have potential prognostic value for long-term adverse events in patients with ICI-related myocarditis.

Series-connected integrated gate-commutated thyristors (IGCTs) find application in hard-switched commercial power converters at the megawatt power levels. Expanding the application of these devices to medium-voltage dc&#x2013;dc resonant converters is of great interest due to the IGCT&#x0027;s low conduction losses. This requires a deeper understanding of the device&#x0027;s behavior in series connection and under switching conditions different than those in hard-switched converters. In particular, the voltage sharing between series-connected IGCTs must be achieved with significantly reduced turn-<small>off</small> currents, typical for resonant converters. Relying on a versatile IGCT test setup, this article explores the operational performances of series-connected IGCT operation at very low turn-<small>off</small> current and with snubber capacitance in the range of a few tens of nanofarad. The results presented in this article are obtained from commercially available 4.5-kV 68-mm reverse-conducting IGCTs (with standard irradiation), as well as two customized engineering samples (high irradiated variants), optimized on their technology curve for high switching frequencies. The IGCTs are successfully operated in series connection at 5 kHz, with device voltage being effectively shared in resonant converter operation.