Design and Evaluation of High Efficiency Power Converters Using Wide-Bandgap Devices for PV Systems

The shortage of fossil resources and the need for power generation options that produce little or no environmental pollution drives and motivates the research on renewable energy resources. Power electronics play an important role in maximizing the utilization of energy generation from renewable energy resources. One major renewable energy source is photovoltaics (PV), which comprises half of all recently installed renewable power generation in the world. For a grid-connected system, two power stages are needed to utilize the power generated from the PV source. In the first stage, a DCDC converter is used to extract the maximum power from the PV panel and to boost the low output voltage generated to satisfy the inverter side requirements. In the second stage, a DC-AC inverter is used to convert and deliver power loads for grid-tied applications. In general, PV panels have low efficiency so high-performance power converters are required to ensure highly efficient PV systems. The development of wide-bandgap (WBG) power switching devices, especially in the range of 650 V and 1200 V blocking class voltage, opens up the possibility of achieving a reliable and highly efficient grid-tied PV system. This work will study the benefits of utilizing WBG semiconductor switching devices in low power residential scale PV systems in terms of efficiency, power density, and thermal analysis. The first part of this dissertation will examine the design of a high gain DC-DC converter. Also, a performance comparison will be conducted between the SiC and Si MOSFET switching devices at 650 V blocking voltage regarding switching waveform behavior, switching and conduction losses, and high switching frequency operation. A major challenge in designing a transformerless inverter is the circulating of common mode leakage current in the absence of galvanic isolation. The value of the leakage current must be less than 300mA, per the DIN VDE 0126-1-1 standard. The second part of this work investigates a proposed high-efficiency transformerless inverter with low leakage current. Subsequently, the benefits of using SiC MOSFET are evaluated and compared to Si IGBT at 1200 V blocking voltage in terms of efficiency improvement, filter size reduction, and increasing power rating. Moreover, a comprehensive thermal model design is presented using COMSOL software to compare the heat sink requirements of both of the selected switching devices, SiC MOSFET and Si IGBT. The benchmarking of switching devices shows that SiC MOSFET has superior switching and conduction characteristics that lead to small power losses. Also, increasing switching frequency has a small effect on switching losses with SiC MOSFET due to its excellent switching characteristics. Therefore, system performance is found to be enhanced with SiC MOSFET compared to that of Si MOSFET and Si IGBET under wide output loads and switching frequency situations. Due to the high penetration of PV inverters, it is necessary to provide advanced functions, such as reactive power generation to enable connectivity to the utility grid. Therefore, this research proposes a modified modulation method to support the generation of reactive power. Additionally, a modified topology is proposed to eliminate leakage current

Problem-Based Learning as a Teaching Method Versus Lecture-Based Teaching in Respiratory Therapy Education

ABSTRACT BACKGROUND: Although Problem-based learning (PBL) approach is a common teaching technique in medical education, its use in the field of respiratory therapy is somewhat controversial. With so many programs adopting PBL strategies, it is important to examine whether there are differences between PBL and traditional teaching approaches in regards to learning outcomes. Therefore, the purpose of this study was to investigate if there are any significant differences between PBL and lecture-based program students in their cognitive abilities in mechanical ventilation. METHODS: Two universities with BS programs in respiratory therapy were chosen—one uses PBL (15 participants) and on uses lecture-based method (24 participants). All 39 participants were given10 multiple-choice questions related to mechanical ventilation derived from the NBRC RRT written exam forms (C & D) as a pre and a post test. RESULTS: The dependent t-test showed a significant difference between the pre and post test of the lecture-based and the PBL groups, resulting in a p value of 0.006 and 0.025 respectively. The independent t-test showed a significant difference in the pre-test favoring the lecture-based group (p = 0.039). However, the independent t-test showed no significant difference in the post-test (p=0.085) CONCLUSIONS: PBL is increasing in popularity despite the fact that studies of its efficacy have been thus far inconclusive. This study has shown PBL to be effective, but not significantly more effective than traditional lecture-based methods in regards to objective test scores

A Mechanism using the Electronic Signature to Verify the Power of Attorney and the Requested Activity

The rapid development that accompanies computer and information technology imposes its applications on all societies in general and developed coun tries in particular. In this paper, we present an algorithm to apply the electronic signature to verify the credibility of power of attorney and the credibility of activity requested using power of attorney. The verification algorithm is to be used in cour ts of law; the algorithm ensures a credible approval by the owner to the agent who has the power of attorney to submit the activity under concern. Selling a real estate property is an example of an activity which might be con ducted by the agent using the " power of attorney". This system, which we designed, implemented and tested, takes into consideration all the financial and security information needed. Our system requirements adopted the financial requirements such as banks and financial firms in number o f societies and countries such as the United States, the European Union and Jordan

Integration of OOFDM with RoF for High Data Rates Long-Haul Optical Communications

One of the advanced technologies in optical fiber communication systems that support efficient convergence of wireless and optical access network structure is Radio over Fiber (RoF). In RoF, light is modulated by using a radio signal and sent over an optical fiber link to simplify wireless access. The demand for high-speed wireless communications is increasing rapidly. To increase the capacity and bandwidth of the optical fiber communication system a Wavelength-Division Multiplexing (WDM) is used. In WDM, multiple optical carrier signals are multiplexed and transmitted over one optical fiber. Optical Orthogonal Frequency Division Multiplexing (OOFDM) technology commits to be a fundamental technique for accomplishing high data when is integrated with RoF. OOFDM is an effective method to overcome different restrictions of optical fiber transmission systems such as chromatic dispersion, polarization mode dispersion, and modal dispersion. Therefore, the combination of OOFDM and RoF will enhance the system flexibility and help to cover a very large area without increasing the system complexity and cost very much. This thesis investigates the integration of OOFDM with RoF for achieving high data rates and the transmission of the signal over long haul optical fiber. Results from the OptiSystem model shows the performance of OOFDM signals through the WDM RoF is studied by using a simulation tool called OptiSystem version 12

Salivary α-amylase gene 1 (AMY1) copy number variation and association with inter-individual differences in body composition and response to carbohydrates intake

Copy number variation has been linked to the development of several syndromes. In a 2014 publication, evidence reported the association of the copy number of salivary amylase 1 (AMY1) with obesity. Several studies confirmed these findings; however, well-powered replication studies in various populations failed to replicate this link. This controversy may be explained by the different study designs and participant populations. A significant association may still be found under specific conditions, such as gender, age, and level of physical activity. Further, if the copy number of AMY1 does influence obesity risk, its mechanisms are yet to be uncovered. We hypothesised that an increased copy number of AMY1 would be associated with body composition more strongly than body mass index (BMI) in athletes and healthy male and female adults. That led us to hypothesise that an increased copy number of AMY1 may be associated with strength athletes and muscle performance due to their lower fat mass and increased lean mass. To understand the association between AMY1 copy number and obesity from a clinical perspective, we hypothesised that healthy adults with a high copy number of AMY1 would have a healthy, controlled glycaemic response after complex CHO ingestion and a higher rate of complex CHO oxidation during rest and exercise compared to a low copy number AMY1 group. This thesis reports on three studies. The first study (Chapter 3) investigated the association of AMY1 copy number with underlying anthropometric aspects of body composition, precisely strength and measures of muscle performance. The study included 388 young adult Lithuanian males divided into non-exercising controls (CON; n= 187, aged 23.91 ± 4) and athletes (n= 201). The latter included the subgroups of strength athletes (STP; n= 50, aged 21.06 ± 3), team sports athletes (TEA; n= 67, aged 22.31 ± 3), and endurance athletes (END; n= 84, aged 21.68 ± 4) were controls recruited between 2006 to 2009. All athletes trained a minimum of twice a week, whereas participants in the control group did not participate in any organised physical activity more than twice a week and did not compete in competitive sports. The copy number of target genes was determined using a quantitative polymerase chain reaction (qPCR). Percentage body fat (% BF) was calculated by Faulkner’s (1968) equation considering the modified Yuhasz method. We observed that the copy number of AMY1 did not differ between the athletes and the control group. Nor was it associated with athletes’ fat mass or FFM; however, a strong association was found with their height. The second study (Chapter 4) assessed the association of increasing AMY1 copy number and body composition, including fat mass and lean mass and assessed the influence of gender differences on fat distribution among males and females. This study included 228 healthy volunteers aged 22.2 ± 3, of which 108 were male and 220 were female recruited between 2016 to 2019. Dual-energy X-ray absorptiometry (DXA) were used for BF % and FFM measurements. Participants completed a 3-day self-reported food questionnaire to assess macronutrient and energy intake and one week of physical activity level questionnaire (SPAQ). The AMY1 copy number distribution did not differ between males and females. No association was noticed between increasing copy number of AMY1 and fat mass or lean mass across the whole study sample nor in males and females. WC (cm) was negatively associated with high AMY1 in female only. The reginal body fat distribution and lean mass distribution did not correlate with AMY1 CN in either gender. Increasing Total EI was associated with decreasing AMY1 CN in males. However, physical activity level (PAL) did not associate with AMY1 CN in either gender. The third study (Chapter 5) examined the effects of high copy number on glycaemic response after starch and glucose ingestion. This pilot study was conducted on 15 healthy young adult participants, divided into two groups, a high copy number group ≥ 9 copies (n= 10) and a low copy number group ≤ 5 copies (n= 5). We observed that the high AMY1 copy number group had higher iAUC plasma glucose concentration post starch ingestion than low CN group post glucose ingestion. However, iAUC plasma insulin concentration was post glucose ingestion higher post glucose ingestion in low CN group than high CN group. plasma lipid concentration did not differ between examined groups after glucose or starch ingestion. 60 % (n = 3) of the low CN group are insulin resistance compeered to 10% (n= 1) in the high AMY1 CN group. The total sample size of 62 adults is recommended to detect 80 % differences between the AMY1 CNV groups in the tested variables in future research

Evaluation of Machine Learning Models for Smart Grid Parameters: Performance Analysis of ARIMA and Bi-LSTM

The integration of renewable energy resources into smart grids has become increasingly important to address the challenges of managing and forecasting energy production in the fourth energy revolution. To this end, artificial intelligence (AI) has emerged as a powerful tool for improving energy production control and management. This study investigates the application of machine learning techniques, specifically ARIMA (auto-regressive integrated moving average) and Bi-LSTM (bidirectional long short-term memory) models, for predicting solar power production for the next year. Using one year of real-time solar power production data, this study trains and tests these models on performance measures such as mean absolute error (MAE) and root mean squared error (RMSE). The results demonstrate that the Bi-LSTM (bidirectional long short-term memory) model outperforms the ARIMA (auto-regressive integrated moving average) model in terms of accuracy and is able to successfully identify intricate patterns and long-term relationships in the real-time-series data. The findings suggest that machine learning techniques can optimize the integration of renewable energy resources into smart grids, leading to more efficient and sustainable power systems.© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

Neuro-Fuzzy Based High-Voltage DC Model to Optimize Frequency Stability of an Offshore Wind Farm

Lack of synchronization between high voltage DC systems linking offshore wind farms and the onshore grid is a natural consequence owing to the stochastic nature of wind energy. The poor synchronization results in increased system disturbances, grid contingencies, power loss, and frequency instability. Emphasizing frequency stability analysis, this research investigates a dynamic coordination control technique for a Double Fed Induction Generator (DFIG) consisting of OWFs integrated with a hybrid multi-terminal HVDC (MTDC) system. Line commutated converters (LCC) and voltage source converters (VSC) are used in the suggested control method in order to ensure frequency stability. The adaptive neuro-fuzzy inference approach is used to accurately predict wind speed in order to further improve frequency stability. The proposed HVDC system can integrate multiple distributed OWFs with the onshore grid system, and the control strategy is designed based on this concept. In order to ensure the transient stability of the HVDC system, the DFIG-based OWF is regulated by a rotor side controller (RSC) and a grid side controller (GSC) at the grid side using a STATCOM. The devised HVDC (MTDC) is simulated in MATLAB/SIMULINK, and the performance is evaluated in terms of different parameters, such as frequency, wind power, rotor and stator side current, torque, speed, and power. Experimental results are compared to a conventional optimal power flow (OPF) model to validate the performance.© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed

An unusual presentation of hemoglobin SD Punjab in a Saudi Arabian adult

HbDPunjab is an uncommon variant hemoglobin that does not result in significant pathology when inherited as a homozygous disorder. When inherited with other hemoglobinopathies, it may result in varying disease phenotypes. HbSDPunjab has been rarely reported in Saudi Arabia, coexisting with alpha or beta thalassemia. In this report, we discuss the case of a 39 years old male who presented with severe anemia and renal injury and was later diagnosed with HbSDPunjab through electropheresis and genetic testing

High yield and high packing density porous carbon for unprecedented CO2 capture from the first attempt at activation of air-carbonized biomass

The first attempt at activation of air-carbonized carbon reveals unusual resistance to activation and unprecedentedly high yields (32–80 wt%) of high packing density (0.7–1.14 g cm−3) microporous carbon dominated by 5.5–7 Å pores, which are just right for CO2 uptake (up to 5.0 mmol g−1) at 1 bar and 25 °C. The high gravimetric uptake and packing density offer exceptional volumetric storage, and unprecedented performance for low pressure swing adsorption (PSA) with working capacity of 6–9 mmol g−1 for a pure CO2 stream (6 to 1 bar) and 3–4 mmol g−1 for flue gas (1.2 to 0.2 bar). The working capacity for vacuum swing adsorption (VSA) is attractive at 5.0–5.4 mmol g−1 under pure CO2 (1.5 to 0.05 bar), and 1.8–2.2 mmol g−1 for flue gas (0.3 to 0.01 bar). The pure CO2 volumetric working capacity breaks new ground at 246–309 g l−1 (PSA) and 179–233 g l−1 (VSA). For flue gas conditions, the working capacity is 120 to 160 g l−1 (PSA). The performance of the activated air-carbonized carbons is higher than the best carbons and benchmark zeolites or MOFs

Modification and Application of Carbon Nanotubes for the Removal of Emerging Contaminants from Wastewater: A Review

The emerging contaminants (ECs) refer to chemical compounds either naturally originated or synthetically modified having potential toxic effects to the environment. The ECs include different pollutants such as biocides, pesticides, pharmaceuticals (antibiotic, analgesics, and hormones) and personal care products (cosmetics, fragrances, and hygiene products). The ECs are considering the top priority pollutants by the European Union (EU) and the United States Environmental Protection Agency (US EPA). Among other materials, the carbon nanotubes (CNTs) are one of widely used materials for the removal of ECs applying diverse techniques of wastewater decontamination. The momentous advancement of these functional nanostructured materials has found to be cost-effective, reusable, smart materials for the application of ECs removal. The aim of this chapter was to explore the modification routes and advancement of functionalization of CNTs with other functional groups by the reported works. The possible mechanistic insight of ECs removal reactions was also evaluated applying different methods for decontamination reported in the past studies. This review will be significant sources of information of CNTs-based materials for the application of wastewater treatment especially ECs removal from wastewater and ultimate environmental remediation