Reliable Power Research Articles

Biaxial strain tuned upconversion photoluminescence of monolayer WS2

Monolayer tungsten disulfide (1L-WS2) is a direct bandgap atomic-layered semiconductor material with strain tunable optical and optoelectronic properties among the monolayer transition metal dichalcogenides (1L-TMDs). Here, we demonstrate biaxial strain tuned upconversion photoluminescence (UPL) from exfoliated 1L-WS2 flakes transferred on a flexible polycarbonate cruciform substrate. When the biaxial strain applied to 1L-WS2 increases from 0 to 0.51%, it is observed that the UPL peak position is redshifted by up to 60 nm/% strain, while the UPL intensity exhibits exponential growth with the upconversion energy difference varying from − 303 to − 120 meV. The measured power dependence of UPL from 1L-WS2 under biaxial strain reveals the one photon involved multiphonon-mediated upconversion mechanism. The demonstrated results provide new opportunities in advancing TMD-based optical upconversion devices for future flexible photonics and optoelectronics.

Удосконалення методики визначення нормативів тягових властивостей автомобіля skoda fabia при стендовому діагностуванні

As you know, the main output parameters characterizing the state of the power unit are the power and torque values. These parameters determine the dynamic qualities of the car, and can also affect fuel consumption and the level of harmful emissions.
 The above parameters are checked using traction roller stands. Such stands allow you to reproduce real speed and load modes. Usually, the traction force on the drive wheels is measured on the stands. It is then easy to calculate the power at a given test speed. Traction force is determined, on the one hand, by the output torque of the engine, on the other hand, by mechanical losses in the transmission. In turn, the moment is determined by the perfection of the combustion process, the complete use of the energy of combustion products, and mechanical losses in the engine itself.
 When there is no reliable, experimentally obtained external speed characteristic of an internal combustion engine, Leiderman's formula is usually used for its approximate construction.
 This technique gives a satisfactory approximation of the dependence of power on revolutions. However, the moment curve is noticeably different from the experimental one. due to the fact that it uses only one experimental point - the maximum power and the corresponding revolutions. Therefore, a refined method of building the external speed characteristic using the example of the SKODA FABIA car is proposed using additional equations that specify the values of the empirical coefficients A, B, C.
 On the basis of the refined external speed characteristics of the engine, the revolutions of the crankshaft are converted into speed, and a graph of the permissible traction force against the speed is drawn according to the derived formula. Standards for diagnostic parameters of the power unit in acceleration mode under partial load are also defined.
 The proposed method of registering engine diagnostic parameters to determine their normative values provides an individual approach to diagnosing the technical condition of cars.

Third order intermodulation and third order intercept in a directly modulated Fabry–Perot laser diode

Abstract This paper presents measurement of third order intermodulation distortion and third order intercept (TOI) in a Fabry–Perot semiconductor laser lasing at 1550.3 nm when the laser is biharmonically bias-current modulated. Keeping the modulation current of one signal fixed, the third order intermodulation power at two different frequencies has been found to increase with the increase in second signal modulation power. There is an eventual crossover or tendency to crossover in the intermodulation characteristics when the modulation current amplitudes of the channels assume the same value. The TOI has been experimentally measured. The intermodulation power appearing at two different frequencies along with their signal power dependence and measurement of TOI constitute the outcome of this paper. The typical value of spurious-free dynamic range of the modulation scheme is 70 dB.

Classification of intrusion cyber‐attacks in smart power grids using deep ensemble learning with metaheuristic‐based optimization

AbstractThe most advanced power grid design, known as a ‘smart power grid’, integrates information and communication technology (ICT) with a conventional grid system to enable remote management of electricity distribution. The intelligent cyber‐physical architecture enables bidirectional, real‐time data sharing between electricity suppliers and consumers through smart meters and advanced metering infrastructure (AMI). Data protection issues, such as data tampering, firmware exploitation, and the leakage of sensitive information arise due to the smart power grid's substantial reliance on ICT. To maintain reliable and efficient power distribution, these issues must be identified and resolved quickly. Intrusion detection is essential for providing secure services and alerting system administrators in the case of adversary attacks. This paper proposes an intrusion classification scheme that identifies several types of cyber attacks on modern smart power grids. Grey‐Wolf metaheuristic optimization‐based feature selection is used to learn non‐linear, overlapping, and complex electrical grid properties. An extended deep‐stacked ensemble technique is advanced by putting predictions from weak learners (CNNs) into a meta‐learner (MLP). The outcomes of this approach are explained and confirmed using explainable AI (XAI). The publicly available dataset from Mississippi State University and Oak Ridge National Laboratory (MSU‐ORNL) is used to conduct experiments. The experimental results show that the proposed method achieved a peak accuracy of 96.6% while scrutinizing the original MSU‐ORNL data feature set and a maximum accuracy of 99% when analysing the selected feature set. Therefore, the proposed intrusion classification scheme may protect smart power grid systems against cyber security attacks.

Enhanced gate biasing resilience in asymmetric and double trench SiC MOSFETs towards generalized highly reliable power electronics

The gate oxide quality in SiC MOSFETs presents a significant challenge, particularly at temperatures exceeding 175 °C. This predicament arises from the gate oxide interface's propensity to trap or release charge carriers, compromising device ruggedness. In mainstream SiC MOSFETs, the gate oxide in the trench corner confronts the demanding task of enduring higher electric field strengths, thereby posing a substantial risk to overall device reliability. As a result, research entities are proactively involved in improving the SiC/oxide interfaces to enhance the devices' resilience against elevated E-field. This endeavor aims to maintain the favorable characteristics of the trench SiC MOSFETs, including low on-state resistance, minimal parasitic capacitance, and exceptional switching performance. Thus, the implementation of a streamlined process becomes crucial to fortify the trench corner, ultimately yielding boosted E-field immunity. In this report, our research focuses on enhancing the reliability of trench corner in SiC MOSFET devices. Specifically, we employ spacer etch technology to selectively shield the trench corner with high-K heterolayers, thereby enhancing the device's ability to withstand higher E-field strengths (59.2 % reinforcement) while mitigating the risk of hidden defects. Importantly, compared to the structure without protection, at high-K shielded layer contact angles ranging from 90 to 150°, the E-field decreases, correlated the enhanced reinforcement at larger angles. Furthermore, such technology enables higher E-fields and greater circuit capacity at the bottom of trench gate, leading to enhanced device reliability. Our studies confirm that the developed device structure exhibits simplicity, reliability, maturity, and controllability, rendering it suitable for large-scale integration applications.

Continuous-wave second-harmonic generation in the far-UVC pumped by a blue laser diode

Far-UVC light in the wavelength range of 200–230 nm has attracted renewed interest because of its safety for human exposure and effectiveness in inactivating pathogens. Here we present a compact solid-state far-UVC laser source based on second-harmonic generation (SHG) using a low-cost commercially-available blue laser diode pump. Leveraging the high intensity of light in a nanophotonic waveguide and heterogeneous integration, our approach achieves Cherenkov phase-matching across a bonded interface consisting of a silicon nitride (SiN) waveguide and a beta barium borate (BBO) nonlinear crystal. Through systematic investigations of waveguide dimensions and pump power, we analyze the dependencies of Cherenkov emission angle, conversion efficiency, and output power. Experimental results confirm the feasibility of generating far-UVC, paving the way for mass production in a compact form factor. This solid-state far-UVC laser source shows significant potential for applications in human-safe disinfection, non-line-of-sight free-space communication, and deep-UV Raman spectroscopy.

Analysis of critical factors influencing sustainable infrastructure vulnerabilities using an ISM-MICMAC approach

PurposeThe purpose of this study is to develop a new hybrid method that combines interpretative structural modeling (ISM) and matrix cross-impact multiplication applied to classification (MICMAC) to investigate the influencing factors of sustainable infrastructure vulnerability (SIV).Design/methodology/approach(1) Literature review and case study were used to identify the possible influencing factors; (2) a semi-structured interview was conducted to identify representative factors and the interrelationships among influencing factors; (3) ISM was adopted to identify the hierarchical structure of factors; (4) MICMAC was used to analyze the driving power (DRP) and dependence power (DEP) of each factor and (5) Semi-structured interview was used to propose strategies for overcoming SIV.FindingsResults indicate that (1) 18 representative factors related to SIV were identified; (2) the relationship between these factors was divided into a five-layer hierarchical structure. The 18 representative factors were divided into driving factors, dependent factors, linkage factors and independent factors and (3) 12 strategies were presented to address the negative effects of these factors.Originality/valueThe findings illustrate the factors influencing SIV and their hierarchical structures, which can benefit the stakeholders and practitioners of an infrastructure project by encouraging them to take effective countermeasures to deal with related SIVs.

Experimental study on heat power of wet and pipe sections of wet/dry cooling tower with extended surface pipe exchanger

A hybrid system for recirculated water cooling of industrial enterprises is proposed. The major feature of the cooling system is a wet/dry cooling tower with an inner pipe exchanger. To enhance the heat transfer process, the outer surface of the heat exchanger pipe has fins. Design and function of the experimental setup are described. The goal of this work is to evaluate experimentally the heat power of the wet and pipe sections of the cooling tower. Results were presented as dependencies of the heat power in the wet/dry cooling tower on the mean gas velocity (from 0.89 to 3.20 m/s) and the ratio of the weight flow rates of the gas/liquid phases at various irrigation rates (13.7-35.6 m3/(m2.h)).

Design and Pharmacophore Study of Triazole Analogues as Aromatase Inhibitors.

In current scenario breast cancer measured as one of the dangerous health issues. An effective therapeutic class of drug known as aromatase inhibitors (AIs) is dominant against estrogen receptorpositive breast cancer. However, there is an urgent need to create target-specific AIs with better anti-breast cancer profiles due to the increased toxicity and adverse effects related to currently existing anti-breast cancer drugs. In the present study, we have designed of 100 novel tiazole analogues as aromatase inhibitors their pharmacophoric features were explored. Molecular docking was applied to a series of 4-substituted-1, 2, 3-triazoles containing letrozole for their aromatase inhibitory effects. The aromatase inhibitory activity of the compound in a series varies in the range of (IC50 = 0.008-31.26 μM). A hydrogen atom positioned at R1 of the triazole ring in compound (01) was responsible for the most potent compound (IC50 = 0.008 μM) in the series of 28 compounds as compared to letrozole. The self-organizing molecular field study was used to assess the molecular characteristics and biological activities of the compounds. The four models were developed using PLS and MLR methods. The PLS method was good for statistical analysis. The letrozole scaffold-based 100 compounds were designed by selecting an effective pharmacophore responsible for aromatase inhibitory activity. The designed compound was placed on the previous model as a test set, and its IC50 values were calculated. Hydrogen bonds were established between the potent molecule (01) and the essential residues Met 374 and Arg 115, which were responsible for the aromatase-inhibiting action. Cross-validated q2 (0.6349) & noncross- validated r2 (0.7163) were discovered in the statistical findings as having reliable predictive power. Among 100 designed compounds, seven compounds showed good aromatase inhibitory activities. The additional final SOMFA model created for the interactions between the aromatase and the triazole inhibitors may be helpful for future modification and enhancement of the inhibitors of this crucial enzyme.

Optimal economic dispatch of a virtual power plant based on gated recurrent unit proximal policy optimization

The intermittent renewable energy in a virtual power plant (VPP) brings generation uncertainties, which prevents the VPP from providing a reliable and user-friendly power supply. To address this issue, this paper proposes a gated recurrent unit proximal policy optimization (GRUPPO)-based optimal VPP economic dispatch method. First, electrical generation, storage, and consumption are established to form a VPP framework by considering the accessibility of VPP state information. The optimal VPP economic dispatch can then be expressed as a partially observable Markov decision process (POMDP) problem. A novel deep reinforcement learning method called GRUPPO is further developed based on VPP time series characteristics. Finally, case studies are conducted over a 24-h period based on the actual historical data. The test results illustrate that the proposed economic dispatch can achieve a maximum operation cost reduction of 6.5% and effectively smooth the supply–demand uncertainties.

A New Thermal Management Strategy of IGBT in DFIG for Economic Benefit Maximization

Wind speed fluctuation generally shortens the lifetime of the insulated gate bipolar transistor (IGBT) module in the doubly fed induction generator (DFIG), which leads to frequent component replacement and cost increase of wind power generation. Conventional power control strategies consider solely the wind turbine output power maximization, and existing junction temperature thermal management strategies focus on IGBT lifetime extension, both of which are not effective under turbulent wind speed conditions and ignore the trade-off between the device reliability and output power for the overall DFIG economic benefit. To bridge the gap between the IGBT reliability and the output power under turbulent wind speed conditions, we propose a novel IGBT thermal management strategy for optimal economic benefit. Specifically, we first smooth the output power through a linear power control (LPC) method with conditions on the wind speed and turbine speed to reduce the IGBT low-frequency junction temperature fluctuation, which extends IGBT lifetime. We then propose a grid encirclement and suppression search (GESS) method that maximizes the economic benefit defined by LPC-smoothed output power and IGBT lifetime. Simulation shows that our proposed LPC-GESS strategy outperforms a competing strategy at economic benefit by a large margin, up to 15.3%. Our proposed strategy can potentially be used in wind power stations for fast and reliable economic benefit-oriented IGBT thermal management.

Investigating the Impact of Water Cooling on the Performance of PV Modules in Palestine

The way that energy is produced across the world has altered recently. The use of renewable energy has increased because it does not harm the environment in the same way that other energy sources, such as fossil fuels, nuclear energy, etc., do because of the pollution they produce. In addition, the cost of producing renewable energy is lower than that of fossil fuels. Since the technologies used to convert solar radiation into a reliable power source have advanced significantly over the past few years and have demonstrated their high efficiency in energy production, demand for energy has recently increased significantly. Solar energy is one of the types of renewable energy. The most popular technique is photovoltaic (PV) modules since it generates energy directly. This study's main goal is to increase photovoltaic (PV) modules' operating capacity while also improving their overall efficiency. PV modules play a crucial part in the field of harvesting solar energy, serving as one of the most well-known ways to make use of the sun's unbounded potential as a leading source of renewable energy. The results of a thorough experimental investigation that examined the effects of PV module cooling and identified the most effective cooling techniques to optimize PV module performance within the particular context of Nablus City, located in Palestine, are revealed in this study. The horizontally divided box was discovered to be the most effective cooling technique, resulting in a 30% reduction in temperature and a 0.5% boost in efficiency.

Design and implementation of a cost‐effective practical single‐phase power quality analyzer using pyboard microcontroller and python‐to‐python interface

AbstractThis work presents the design, development, and performance evaluation of a cost‐effective and practical single‐phase power quality analyzer (SPPQA) using Pyboard microcontroller and Python‐to‐Python interface. The SPPQA offers comprehensive measurements, including voltage/current harmonics up to the seventh order, frequency, voltage and current root mean square values, total power, active/reactive power, power factor, voltage and current crest factor, as well as voltage/current total harmonic distortion. To ensure the accuracy of the SPPQA, a testing procedure was conducted using a test bench equipped with a non‐linear load and a 220‐V power source operating at a frequency of 50 Hz. The obtained results, such as and , are compared with measurements obtained from classical approaches and devices, validating the authenticity and reliability of the SPPQA's performance. The SPPQA demonstrates considerable accuracy and reliability in its measurements, establishing it as an efficient and practical tool for power quality assessment. The ability to measure the seven harmonics of voltage and current, alongside other critical parameters, positions the SPPQA as a practical asset in the academic, industrial, and commercial sectors. The affordability and practicality of the SPPQA make it practical in both academic research and practical scenarios. Utilizers can gain deeper information into power quality through its measurements and harmonics analysis, while also enhancing industrial processes and ensuring a reliable power supply in commercial settings.

Design and control of LSTM-ANN controllers for an efficient energy management system in a smart grid based on hybrid renewable energy sources

Many isolated locations, including hilly areas, remote sites, and military camps, lack feasible access to the main power grid. In these conditions, locally established Microgrids can provide the necessary power supply. However, to meet the demands of these isolated areas, numerous individual Microgrids are required. Although some of these Microgrids might be integratable, geographical constraints may preclude full integration. Under these circumstances, the establishment of a smart grid—integrating multiple Microgrids with a battery management system—can potentially solve many power supply issues. A smart grid control system paired with a centralized battery management system is proposed in this paper. The system considers the use of multiple renewable energy sources at various locations for stable and reliable power generation. The proposed method incorporates a long short-term memory (LSTM)-based artificial neural network (ANN) to ensure a stable, high-quality power supply at different load buses. Additionally, this work introduces an artificial intelligence-based operating system designed to maintain energy management under various conditions. To enhance voltage quality, a 7-level aligned multilevel inverter is incorporated into the system. As compared with PI and Fuzzy controllers, the proposed method with LSTM-ANN controller is improved the power quality under sudden changes in the system which are also presented in results, Voltage variation of PI, Fuzzy, and LSTM-ANN is 370V,180V,and 70V . The effectiveness of the proposed energy management system (EMS) is verified by using a hardware-in the-loop approach with OPAL-RT modules, yielding realistic results.

Big data analytics in the healthcare sector: Opportunities and challenges in developing countries. A literature review.

Background: Despite the ongoing efforts to digitalize the healthcare sector in developing countries, the full adoption of big data analytics in healthcare settings is yet to be attained Exploring opportunities and challenges encountered is essential for designing and implementing effective interventional strategies. Objective: Exploring opportunities and challenges towards integrating big data analytics technologies in the healthcare industry in developing countries. Methodology: This was a narrative review study design. A literature search on different databases was conducted including PubMed, ScienceDirect, MEDLINE, Scopus, and Google Scholar. Articles with predetermined keywords and written in English were included. Results: Big data analytics finds its application in population health management and clinical decision-support systems even in developing countries. The major challenges towards the integration of big data analytics in the healthcare sector in developing countries include fragmentation of healthcare data and lack of interoperability, data security, privacy and confidentiality concerns, limited resources and inadequate regulatory and policy frameworks for governing big data analytics technologies and limited reliable power and internet infrastructures. Conclusion: Digitalization of healthcare delivery in developing countries faces several significant challenges. However, the integration of big data analytics can potentially open new avenues for enhancing healthcare delivery with cost-effective benefits.

The Impact of Privatization of the Power Sector on the Economy in Nigeria 2013-2022

This study explores the impact of Privatization of the Power Sector on the Economy in Nigeria and proposes strategies to enhance efficiency and sustainability. The findings, based on data collected through a semi-structured interviews from various stakeholders, reveal diverse perspectives on the performance of privatization reforms. While some stakeholders acknowledge improvements in electricity supply, others highlight the loss of benefits. Challenges faced by the power sector after privatization include insecurity, vandalization of equipment, imbalance in load distribution, outdated infrastructure, and unreliable service delivery. The evaluation of privatization on electricity tariffs and the economy shows mixed views, with some stakeholders expressing dissatisfaction and others noting positive impacts on business performance. Strategies for improvement include government intervention, improved infrastructure, customer engagement, fair distribution of prepaid meters, anti-corruption measures, training and expertise. Implementing these recommendations can enhance the efficiency and sustainability of the power sector, supporting economic growth and development in Nigeria. The study emphasizes the crucial role of the power sector in the economy and highlights the need for collaboration among stakeholders for a robust and reliable power supply system.

Power hardware in the loop methodology applied in the integration of wind energy conversion system under fluctuations: a case study

ABSTRACT In this paper, a power hardware in the loop (p-HIL) validation of a wind energy conversion system (WECS) interconnected into the balanced or unbalanced grid is presented. WECS power is obtained from wind fluctuations of the Yucatan Peninsula, Mexico, and transferred through the DC-AC power electronic converter (PEC). A robust control law based on a simple PI regulator and phasor analysis is proposed, having advantages, such as continuous power generation, operating both under balanced and unbalanced grid conditions; total harmonic distortion (THD) reduction less than 3%; power factor (PF) correction close to the unit; balanced grid currents; a simple mathematical analysis. The main objective is to keep the WECS connected to the electrical grid even in the presence of unbalanced three-phase voltages, including contributions such as: i) VDC ripple reduction; ii) Balanced currents; iii) Sinusoidal currents; iv) Free of Sequence calculation; v) Free of dq0 or αβ Transforms; vi) Simple PI Loop control; and vii) Experimental Validation. The WECS efficiency and robustness are assessed by a complete mathematical examination, validated by the simulations in MATLAB-Simulink®, and support with experimental results through the real-time simulator Opal-RT Technologies®, a low-scale laboratory prototype, and p-HIL methodology. The results present a DC link voltage constant at 75 V and optimal and reliable power integration with an efficiency of 95%.

Renewable energy integration in healthcare systems: A case study of a hospital in Azad Jammu and Kashmir

AbstractRenewable energy sources have gained widespread attention due to their abundance and cost‐effectiveness. In particular, healthcare systems and hospitals are increasingly seeking clean and renewable energy solutions to reduce energy costs, price volatility, and protect community health. However, proper load estimation and techno‐economic analysis are crucial to ensure the optimal performance and reliable power supply of renewable energy systems. This study focuses on conducting a case study on load estimation and techno‐economic analysis for a hospital located in a remote area of Azad Jammu and Kashmir, Pakistan. Through this analysis, the study aims to determine the feasibility of implementing a renewable energy system at the hospital and assess the potential benefits in terms of energy production, cost savings, and environmental impact. Two different clean energy management softwares, HOMER PRO and RETScreen Expert, are utilized to compare the proposed hybrid (PV/Wind/Battery/Convertor/Grid) system with the existing system in terms of cost minimization, optimal system configuration, and environmental effects. The results demonstrate that the proposed hybrid system is more efficient, stable, cost‐effective, and a environmentally friendly option. Moreover, the annualized energy production, consumption, and grid load reduction are also calculated. The findings of both software programs are compared for validation of the proposed optimal system. The techno‐economic analysis of the proposed system can serve as a useful guideline for other commercial facilities in the region to utilize solar and wind energy.

Arrangement for reliable power supply to emergency commercial customers with techno-economic performance improvement of PV enhanced distribution systems

Accelerating engagement of distributed energy resources unleashed the dependency on traditional electric power generation. To reduce the craving for traditional power dependency and unplanned outages the power distribution sectors are gradually adopting cleaner and reliable electrification. However, the unscheduled and unorganized engagement of stochastic generation from renewable energy sources (RES) makes the distribution system operation more vulnerable. For reliable and continuous power supply with RES, scheduled operation of BSSs and power capacitor (CAP) units can be integrated to provide emergency power supply support to consumers. In this paper, the supply of continuous and reliable power to commercial and emergency customers has been investigated subject to complete reliability (CR). The benefit-to-cost ratio (BCR) has been maximized to give reliable power to consumers by the minimum investment cost by utility, which can benefit both electric customers and power distribution operators in a single platform. The maximization of BCR has been evaluated by optimal S-CDS of the BSSs and S-S of CAP units’ operation through the PSO technique in the considered 28-bus active distribution network in different seasons. The techno-economic benefit of integrating only BSSs and BSSs with CAP units in the prospective locations has been analyzed. The improvement in battery life and decrease in SAENS, SADPL, and SADD have been obtained, which shows the efficacy of the proposed work.

A low-cost IoT solution for power availability improvement in hospitals.

Power is a crucial element in hospitals whether it's within the intensive care units, surgical bays, or medical scanning rooms. Without reliable power, patients’ lives are at risk. The power availability improvement is therefore a crucial point in healthcare. A supervising system superimposed to the main components of the power system as able to promptly signal anomalies or malfunctioning or outages can be very useful for this task. To this aim, an Internet of Things (IoT) based solution has been implemented that allows equip at low cost the various electrical components in the distribution MV/LV substations of the hospital’s power system so as to be connected to a central supervising system. The solution implements a platform based on Rapsberry pi 3.