Power Rate Research Articles

Development of an Indoor Line Scanning System for Photovoltaic Modules Performance Characterization

Uganda’s interest in using solar energy for various applications began 20 years ago. However, there have been numerous reports by the public over the poor performance of the photovoltaic (PV) modules during their operations. This study determined the performance of selected PV modules openly sold in the Ugandan markets. The low-cost indoor line scanning system developed using locally available materials was used to assess the performance of each of the solar cells in the PV module by determining their photogenerated currents. In addition, the electrical characteristics of the PV modules were determined using the outdoor characterization method, which assumed the actual operation of the PV modules under direct sunlight. From the indoor line scans, the percentage of performing solar cells in the three PV modules of single-crystalline silicon (c-Si), multi-crystalline silicon (mc-Si), and amorphous silicon (a-Si) technologies were determined as 79%, 61%, and 95% respectively. The outdoor characterization results revealed that the c-Si, mc-Si, and a-Si PV modules had measured maximum power outputs of 18.5 W, 19.0 W, and 18.9 W, respectively and these were lower than the rated power values of 20 W. The line scan results had a direct relationship with the measured power output of the PV module, which implied that solar cells mismatch, affected the performance of the PV modules by lowering their performance. This developed testing system is affordable for developing countries with limited testing systems and would in the long run contribute to significant increase in the deployment of PV technology in Uganda since only performing PV modules would be allowed into the open market.

The Role of LEM in Mine Slope Safety: A Pre- and Post-Blast Perspective

Slopes are formed as a result of mining operations. These slopes are classified as artificial slopes. Improper planning of slopes can lead to instability and potentially trigger landslides. PT. Allied Indo Coal Jaya employs the open-pit mining method in its coal mining operations. Slopes are naturally formed in open-pit mines. Additionally, PT. Allied Indo Coal Jaya utilizes blasting for rock demolition. Therefore, it is crucial to assess the impact of blasting activities on slope stability. This study investigates the influence of blasting on slope stability in coal mines using the limit equilibrium method (LEM). The study evaluates the effects of factors such as ground vibration, blast distance, and blast hole count on the factor of safety (FoS) of slopes. The limit equilibrium method (Fellenius, Bishop, Janbu, Spencer, and Morgenstern-Price) is employed to determine the factor of safety. The factor of safety is modeled using RocScience SLIDE version 6.0 in this study. The factor of safety (FoS) is defined as the ratio of the stabilizing force to the destabilizing force acting on the slope. This study also models the influence of ground vibration, distance, and total number of blast holes on the factor-of-safety (FoS) value. The results indicate that the slope remains stable both pre- and post-blasting, with an overall FoS value greater than 1 for the five slopes examined using various limit equilibrium method (LEM) techniques. However, the FoS value decreased prior to blasting due to the impact of ground vibration and blast distance. It is evident that the ground vibration (PPA) increases with the number of blast holes. The amount of ground vibration decreases as the number of blast holes increases. An increased number of blast holes leads to a decrease in the FoS value. The observed decline in slope FoS values and the increase in PPAs is attributable to the growing number of blast holes. The type of explosive, along with its power and rate of detonation, influences the amount of energy produced, which in turn affects the degree of ground vibration. The findings indicate that the slopes remain stable (FoS > 1) both before and after blasting, although blasting slightly reduces the FoS. The study reveals that as the number of blast holes increases, both ground vibration (PPA) and the reduction in FoS increase, underscoring the effects of explosive power and detonation rate on slope stability.

Fine-grained simulation model for PV power output interval based on two-stage scenario clustering and dual-ensemble compatible learning

Photovoltaic (PV) power simulation is indispensable for the planning and operation of renewable-rich power systems. Among various simulation methods, data-driven indirect simulation methods are the most efficient, primarily involving scenario extraction and power output generation. Typical scenario extraction methods often feature coarse characterizations, which also cannot be expressed by traditional power output generation models lacking the ability of quantifying the uncertainty of the output results. This paper proposes a fine-grained simulation model for PV power output interval, i.e., upper bound and lower bound, based on two-stage clustering of multiple typical scenarios and dual-ensemble compatible learning. The first stage of scenario extraction, considering the impact of total daily irradiance on PV output, employs a line distance index for preliminary scenario division of daily PV output. These scenarios are further divided into five characteristic scenarios with an angular distance index considering the impact of intra-day irradiance variations on power output. PV power output interval is generated from dual-ensemble compatible learning including Stacking and Bagging, which are adaptively selected with a Bias-Variance Selection Index (BS) calculated using the value of scenario characteristics. Stacking and Bagging are driven by three neural network base learners with Bayesian layers, which can output the lower bound and upper bound with confidence at a certain level, thus quantifying the uncertainty of the result accurately. The actual data of Daxing and Gangjialing power stations are used in case study. Results form case study show that compared with the existing methods, the proposed method can improve the Power Coverage Rate (PCR) and Average Power Simulation Accuracy (APA) of uncertainty simulation results by 27.44% and 5.39%, respectively. Meanwhile, the Average Daily Maximum Power Simulation Accuracy (AMPA) is similar to that of existing methods.

Novel multi-modular power conditioning system and decoupling control strategy for SMES with coupled superconducting coil

The high-temperature superconducting magnetic energy storage system (HTS-SMES) utilizes a superconducting coil (SC) to store electric energy in a magnetic field. It has several advantages such as high efficiency, fast response, and infinite charge–discharge cycles. Coupling two SCs made of different HTS materials, known as coupled SC (CSC), can enhance the utilization rate of HTS tapes, reduce manufacturing costs, increase the energy storage density of the SC, and lower magnetic leakage. However, the presence of a coupled magnetic field in CSC makes precise power and current regulation of the individual SC challenging. Additionally, the self-inductances of the individual SCs, composed of different materials, typically differ from each other. Consequently, the current variation induces electromotive force in each SC that differs from the others, necessitating the design of power converters with different voltage ratings connected to each SC. To address the difficulties associated with SMES implementation using CSC, this paper proposes novel modular power conditioning system (MPCS) and decoupling control strategy for SMES. The MPCS enables the flexible design of individual SC power ratings by selecting the appropriate number of power modules. The decoupling control ensures precise current control of each individual SC, which significantly reduces the current ripple of the SCs. Moreover, by employing carrier phase shift modulation, the total harmonic distortion (THD) of the PCS output current is as low as 0.79%. Furthermore, the feedforward power control is proposed to reduce the power control overshoot, and the current sharing control is presented to ensure precise current sharing between each SC. Simulation results verify the efficacy of the proposed approaches.

Effects of wire feeding direction on the deposition characteristics of 316L stainless steel in laser-directed energy deposition

This study investigates the effect of wire feeding direction on the microstructure of 316 stainless steel during the laser-directed energy deposition (L-DED) process. The process parameters were optimised by varying the scan speed, laser power, and wire feed rate to identify a common parameter set for all feed directions to give desired weld bead geometries. The identified process parameter window has shown that the conduction mode is preferred over the balling and keyhole modes. Comprehensive microstructural characterization using optical and electron microscopy has revealed that for the same parameters, the front wire feed had higher penetration, while the back wire feed had a wider bead with optimal penetration. The current findings are of significance for advancing wire-L-DED additive manufacturing for more complex component designs.

Effects of flywheel resistance training on countermovement jump performance and vastus lateralis muscle stiffness: A controlled study

ABSTRACT This study aimed to investigate the effects of an 8-week resistance training using flywheel (FW) device on countermovement jump (CMJ) performance and resting stiffness of the vastus lateralis (VL) muscle. Physically active adults were randomly assigned to a training intervention group (T; n = 18) and a control group (C; n = 13), which received no intervention. Jump performance variables and ultrasound-assessed resting VL shear modulus were measured before and after the intervention. Analysis of covariance revealed statistically significant group differences in jump height (T = +9%; C = -3%), rate of force development (T = +32%; C = +4%), peak power (T = +9%; C = -1%), and peak force (T = +7%; C = -1%). Jump performance improved only in the training group (all CMJ variables p < 0.05). Conversely, no significant changes within groups were observed in the resting shear wave modulus results (p > 0.05). VL stiffness decreased in the training group (−4%) and increased in the control group (+6%). Our results suggest that resistance training using FW device with individually allocated high-load FW inertia induces significant improvements in jump performance, which are not underpinned by changes in VL muscle stiffness.

A Comprehensive Strategy for Implementing Adaptive Data Rate (ADR) in LoRaWAN Technology: Optimizing IoT Networks

The Internet of Things (IoT) is increasingly essential for creating smart environments by establishing long range connectivity among devices. LoRaWAN is a prominent technology choice for these applications due to its energy efficiency and extensive coverage. Central to LoRaWAN’s functionality is the Adaptive Data Rate (ADR) mechanism, which optimizes network performance by adjusting each device’s data rate and transmission power dynamically. This study delves into ADR’s operational principles, benefits, and implementation challenges in LoRaWAN networks. The proposed simulation model, featuring configurable parameters like the spreading distribution factor (SF), the adjustable number of devices, and the SNR threshold, denotes enhanced network performance after implementing the ADR algorithm. With an SNR threshold of 15 dB, ADR reduced the average transmission power of 200 devices from 7 dBm to 3 dBm after twenty iterations, underscoring ADR’s role in minimizing energy consumption while improving network efficiency.

Integrative Computational Intelligence Techniques for Insomnia and Sleep Stage Recognition from ECG Data

Abstract—Insomnia is a common sleep disorder that can lead to serious health problems, including cardiovascular issues. Early and accurate detection is essential for effective treatment, but traditional diagnostic methods are often costly, time-consuming, and prone to human error. To address these challenges, this paper introduces a novel hybrid artificial intelligence (AI) approach for automatic insomnia detection using electrocardiogram (ECG) signals. The method utilizes heart rate variability (HRV) and power spectral density (PSD) analysis in various classification scenarios, including subject- based classification (normal vs. insomnia), sleep stage-based classification (REM vs. wake), and a combined classification approach using both subject and sleep stage features. Ensemble learning techniques, such as random forest (RF) and decision tree (DT) classifiers, are used in the first two scenarios, while linear discriminant analysis (LDA) is applied in the combined classification. The approach includes ECG signal collection, HRV feature extraction, PSD estimation, and classification. Evaluation using the publicly available PhysioNet dataset shows strong performance across all scenarios, with high sensitivity, specificity, and accuracy. The combined classification scenario, in particular, achieves the highest detection accuracy with LDA. Keywords—HRV Extraction, Sleep Stage, Ensemble, LDA

Experimental Parametric Study on the Primary Efficiency of a Fixed Bottom-Detached Oscillating Water Column Wave Energy Converter in Short-Fetch Sea Conditions

The Oscillating Water Column (OWC) represents a highly promising approach for wave energy conversion. This study presents laboratory experiments conducted on a fixed, bottom-detached OWC device to evaluate the impact of various design parameters (specifically, turbine damping, front wall draft, and chamber length in the direction of wave propagation) on the device’s capture width ratio. Despite the extensive research over the past few decades on OWC devices, most studies and field-tested prototypes have been designed for long-fetch sea conditions. Consequently, these devices tend to be larger in size and have higher rated power outputs. In contrast, short-fetch sea conditions necessitate tuning the OWC to the shorter dominant wave frequencies, which calls for the development of smaller devices and specialized turbines, highlighting the need for focused research. This work specifically addresses short-fetch sea conditions, which are representative of moderate wave climates, such as those found in the central Mediterranean region. The study identifies a maximum capture width ratio of approximately 73%. The experimental dataset generated can serve as a benchmark for numerical models under these specific conditions and assist in the development of air turbines optimized for effective performance in short-fetch wave climates.

Influence of wood modification on parameter settings and treatment results in CO2 laser structuring of beech veneers

In this study, the possible influences of thermal modification of wood on the quality of laser texturing of beech veneers are investigated by comparing native and thermally modified samples. By varying the process parameters of a CO2 laser, the surfaces of both types of veneer were textured and the resulting surface roughness and aspect ratios were analyzed in order to evaluate the efficiency of the laser texturing and the quality of the textures produced. The main results show that the thermal modification of the wood influences the cutting widths, the removal depths, and the surface roughness, with thermally modified veneers generally having larger cutting widths and different removal depths compared to native veneers, indicating the influence of the wood modifications on the material physical and chemical properties and their interaction with the laser processing. Furthermore, the study shows how the laser processing parameters—feed rate and laser power—influence the surface quality and structural dimensions of the engraved lines, and establishes that the moisture content of the wood has a significant influence on its thermal conductivity and thus on the laser cutting process. The research work highlights the complexity of laser texturing of wood and emphasizes the need to take into account the change in the intrinsic properties of the material as a result of thermal modification.

A comparative study of diesel engine fueled by neem and ethanol biodiesel: performance, emissions, and sustainability assessment

Examining the emission characteristics of compression ignition (CI) engines using neem biodiesel in conjunction with ethanol and different percentages of exhaust gas recirculation (EGR) was the aim of the present research. In this experiment, a four-stroke, air-cooled, single-cylinder diesel engine with a rated power output of 5.2 kW was used to change the EGR percentage from 0% to 20%. Examining engine emission parameters and comparing them to diesel fuel was the aim of the research. The experiment indicates that as the EGR fraction in the fresh mixture rises, nitrogen oxide emissions fall. the most percentage of nitrogen oxide reduction as compared to diesel operating on its own. Using ethanol with varying EGR rates may lower emissions of hydrocarbons and carbon monoxide.

Ingeniously controlling interface diffusion endows the Skutterudite thermoelectric device with ultra-high service stability

Building a barrier layer/thermoelectric material interface with high-bonding strength, low-contact resistivity, and high-thermal stability is a prerequisite for reliable applications of thermoelectric devices and is currently a bottleneck problem. Herein, we designed a unique Ni-Cr barrier layer with a narrow-channel structure for thermoelectric skutterudite (SKD) to ingeniously control the diffusion/reaction process of Sb and Ni (Co, Fe) at the interface, affecting the interfacial phase structure and then preventing the interface structural damage caused by thermal mismatch during thermal aging while ensuring strong metallurgical bonding. After enduring at 823 K for 70 days, the contact resistivities of Ni45Cr55/n-SKD and Ni75Cr25/p-SKD joints increase slowly and their bonding strengths remain stable, based on which the calculated annual attenuation rates of conversion efficiency and output power are both less than 2 %, reaching a leading level. The assembled 8-pair SKD module shows no performance degradation after 168-hour continuous service test with hot-side temperature of 823 K. This work not only strongly elevated the service stability of SKD device, but also opens the new horizon of designing barrier layers for other TE materials.

Effect of Synthesis Conditions on the Structure and Electrochemical Properties of Vertically Aligned Graphene/Carbon Nanofiber Hybrids

In recent years, significant efforts have been dedicated to understanding the growth mechanisms behind the synthesis of vertically aligned nanocarbon structures using plasma-enhanced chemical vapor deposition (PECVD). This study explores how varying synthesis conditions—specifically hydrocarbon flow rate, hydrocarbon type, and plasma power—affect the microstructure, properties, and electrochemical performance of nitrogen-doped vertically aligned graphene (NVG) and nitrogen-doped vertically aligned carbon nanofibers (NVCNFs) hybrids. It was observed that adjustments in these synthesis parameters led to noticeable changes in the microstructure, with particularly significant alterations when changing the hydrocarbon precursor from acetylene to methane. The electrochemical investigation revealed that the sample synthesized at higher plasma power exhibited enhanced electron transfer kinetics, likely due to the higher density of open edges and nitrogen doping level. This study contributes to better understanding the PECVD process for fabricating nanocarbon materials, particularly for sensor applications.

A System to Store Waste Heat as Liquid Hydrogen Assisted by Organic Rankine Cycle, Proton Exchange Membrane Electrolyzer, and Mixed Refrigerant Hydrogen Liquefaction Cycle

ABSTRACTThis study proposes a system to store waste heat as liquid hydrogen using a proton exchange membrane electrolyzer (PEME) and a mixed refrigerant hydrogen liquefaction cycle. The novelty of this study lies in proposing a waste heat recovery system that stores electricity as liquid hydrogen, consuming less power due to the improved exergy efficiency of the components. The proposed system is analyzed to achieve better efficiency in terms of thermal and exergy efficiencies. Waste heat is used to generate power by an organic Rankin cycle (ORC), produced electricity is utilized in the PEME unit and compressors of liquefaction cycle to produce and liquefy hydrogen, respectively. Codes are written in EES software to simulate the system. Thermodynamic analysis is done in order to achieve better thermal efficiency for the proposed model. Membrane potential at different values of current density is calculated and compared with validate the simulated model. The exergy efficiency of the liquid hydrogen production process is 57%. The exergy efficiency, rate of power produced in ORC, and rate of hydrogen production by the electrolyzer increase significantly by increasing the isentropic efficiency of the turbine. At a temperature of 340 K for the evaporator, the thermal efficiency of ORC is obtained at 8.5%, which is approximately 3% higher compared with that of the previous similar process.

Does the Intensity of Therapy Correspond to the Severity of Acute Respiratory Distress Syndrome (ARDS)?

Objectives: The intensity of respiratory treatment in acute respiratory distress syndrome (ARDS) is traditionally adjusted based on oxygenation severity, as defined by the mild, moderate, and severe Berlin classifications. However, ventilator-induced lung injury (VILI) is primarily determined by ventilator settings, namely tidal volume, respiratory rate, and positive end-expiratory pressure (PEEP). All these variables, along with respiratory elastance, are included in the concept of mechanical power. The aim of this study is to investigate whether applied mechanical power is proportional to oxygenation severity. Methods: We analyzed 291 ARDS patients (71 mild, 155 moderate, and 65 severe). We defined low, middle, and high mechanical power by dividing the entire population into tertiles with a similar number of patients. In each oxygenation class, we measured computed tomography (CT) anatomy, gas exchange, respiratory mechanics, mechanical power, and mortality rate. Results: ARDS severity was proportional to lung anatomy impairment, as defined by quantitative CT scans (i.e., lung volume and well-aerated tissue decreased across the ARDS classes, while respiratory elastance increased, as did mortality). Mechanical power, however, was similarly distributed across the severity classes, as the decrease in tidal volume in severe ARDS was offset by an increase in respiratory rate. Within each ARDS class, mortality increased from low to high mechanical power (roughly 1% for each J/min increase). Conclusions: Both lung severity and mechanical power independently impact mortality rates. It is tempting to speculate that ARDS severity primarily reflects the natural course of the disease, while mechanical power primarily reflects the risk of VILI.

Assessment of electricity production and coastal protection of a nearshore 500 MW wave farm in the north-western Portuguese coast

Wave energy can contribute towards the “green” energy transition, but complementary applications like coastal protection are equally pertinent. However, viable commercialization should entice large wave energy farms of significant capacity, which may raise conflicts with coastal industries and/or protected areas. Such matters are addressed in this paper's numerical case study of a dual wave farm for a nearshore Portuguese site. It incorporates two parks of 75 bottom-fixed oscillating flap units, each. The farm's configuration, orientation, layout, and rating were evaluated for varying wave conditions and water levels, based on a statistically representative clustering technique. The farm's location was selected to minimize marine space conflicts. The numerical modelling was executed with SNL-SWAN, from which it was found that a staggered configuration – “W” – would yield better results than an aligned configuration – “III”. The “shadowing” effect of one park onto the other was equally observed, but with limited impact. Greater farm unit spacing and rated power benefited the annual energy production, with values of nearly 345 GWh/yr being achieved. However, the capacity factors were generally greater for lower power ratings, as pondered mean values varied between 0.078 (3.332 MW) to 0.144 (1 MW). Wave power absorption ratios between wave farms and cumulative standalone units (q-factors) were always below 1, pointing towards a destructive interference pattern. Important significant wave height reductions were observed (above 30 %, at times), albeit increments were punctually identified near two shallow water areas. Lastly, increasing the tidal level did not impact the farm's performance considerably, but benefited the nearshore impact.

Optimization and performance analysis of a hybrid system for hydrogen production: Thermodynamic, economic, and environmental perspectives

The increasing demand for sustainable energy solutions necessitates innovative systems that generate hydrogen, electricity, heating, and freshwater, addressing resource limitations and fossil fuel impacts. With a focus on green hydrogen for sustainable energy transformation, this study introduces a multi-generation system to enhance hydrogen production. A parametric and sensitivity analysis, including energy, exergy, exergoeconomic, and exergoenvironmental analyses, was conducted alongside a system sustainability analysis. The outputs of the considered basic system include net power, freshwater, and hydrogen production rates of 10.178 MW, 18.67 kg/s, and 1.727 kg/h, respectively. The system achieves an exergy efficiency of 50.30%, an energy efficiency of 42.58%, a capital cost rate of $112.87/h, an exergoenvironmental impact index of 0.9734, and a sustainability index of 2.012. Optimization using a genetic algorithm was performed across three scenarios. In one of these scenarios, specifically aimed at hydrogen production, the system achieved a production rate of 1.72 kg/h and a capital cost rate of $91.32/h.

Chisel plow characteristics impact on power-fuel consumption, stubble cover, and surface roughness using deep learning neural networks with sensitivity analysis

The aim of this study was to determine the effects of different shank types, tine types, and tractor forward speeds on the power and fuel consumption of chisel plows, stubble cover, soil surface roughness, and penetration resistance. In addition, using the obtained results, the draft power, fuel consumption, soil surface roughness, and soil stubble cover rate were modeled using Deep Learning Neural Network (DLNN) architectures and sensitivity analysis of these models were performed. Four different shank types (rigid, semi-spring, spring, and vibrating) and two different tine types (conventional and winged) were used at three different tractor forward speeds (4.5, 5.4 and 6.3 km.h− 1) were tested to this end. The obtained results indicated that the maximum draft power was achieved with the rigid type shank. The highest soil surface roughness values were observed for the vibrating shank type and winged tine type. Sixteen different network architectures were conducted using deep learning neural network methods and draft power, fuel consumption, soil surface roughness, and percent stubble cover were modeled. Sensitivity analyses were performed to indicate which modeled parameters were more sensitive to the factors using the obtained models. Draft power was modeled with 97.7% accuracy using the DLNN9 network architecture. Additionally, fuel consumption and soil roughness were best modeled with the DLNN13 network architecture, R2 values for those targets were 0.929 and 0.930 respectively. According to the sensitivity analysis, draft power, fuel consumption, soil roughness, and stubble cover rate were significantly affected by changes in the physical properties of the soil.

Power Converters for Green Hydrogen: State of the Art and Perspectives

This paper provides a comprehensive review and outlook on power converters devised for supplying polymer electrolyte membrane (PEM) electrolyzers from photovoltaic sources. The produced hydrogen, known as green hydrogen, is a promising solution to mitigate the dependence on fossil fuels. The main topologies of power conversion systems are discussed and classified; a loss analysis emphasizes the issues concerning the electrolyzer supply. The attention is focused on power converters of rated power up to a tenth of a kW, since it is a promising field for a short-term solution implementing green hydrogen production as a decentralized. It is also encouraged by the proliferation of relatively cheap photovoltaic low-power plants. The main converters proposed by the literature in the last few years and realized for practical applications are analyzed, highlighting their key characteristics and focusing on the parameters useful for designers. Future perspectives are addressed concerning the availability of new wide-bandgap devices and hard-to-abate sectors with reference to the whole conversion chain.

Vector Reconfiguration on a Bidirectional Multilevel LCL-T Resonant Converter

With the development of distributed energy technology, the establishment of the energy internet has become a general trend, and relevant research about the core component, energy router, has also become a hotspot. Therefore, the bidirectional isolated DC–DC converter (BIDC) is widely used in AC–DC–AC energy router systems, because it can flexibly support the DC bus voltage ratio and achieve bidirectional power flow. This paper proposes a novel vector reconfiguration on a bidirectional multilevel LCL-T resonant converter in which an NPC (neutral-point clamped) multilevel structure with a flying capacitor is introduced to form a novel active bridge, and a coupling transformer is specially added into the active bridge to achieve multilevel voltage output under hybrid modulation. In addition, an LCL-T two-port vector analysis is adopted to elaborate bidirectional power flow which can generate some reactive power to realize zero-voltage switching (ZVS) on active bridges to improve the efficiency of the converter. Meanwhile, due to the symmetry of the LCL-T structure, the difficulty of the bidirectional operation analysis of the power flow is reduced. Finally, a simulation study is designed with a rated voltage of 200 V on front and rear input sources which has a rated power of 450 W with an operational efficiency of 93.8%. Then, the feasibility of the proposed converter is verified.