Test System Research Articles

Voltage and frequency control of microgrid in presence of micro-turbine interfaced to matrix converter

The active and reactive load changes have a significant impact on voltage and frequency. In this paper, in order to stabilize the microgrid (MG) against load variations in islanding mode, the active and reactive power of all distributed generators (DGs), including energy storage (battery), diesel generator, and micro-turbine, are controlled. The micro-turbine generator is connected to MG through a three-phase to three-phase matrix converter, and the droop control method is applied for controlling the voltage and frequency of MG. In addition, a method is introduced for voltage and frequency control of micro-turbines in the transition state from grid-connected mode to islanding mode. A novel switching strategy of the matrix converter is used for converting the high-frequency output voltage of the micro-turbine to the grid-side frequency of the utility system. Moreover, using the switching strategy, the low-order harmonics in the output current and voltage are not produced, and consequently, the size of the output filter would be reduced. In fact, the suggested control strategy is load-independent and has no frequency conversion restrictions. The proposed approach for voltage and frequency regulation demonstrates exceptional performance and favorable response across various load alteration scenarios. The suggested strategy is examined in several scenarios in the MG test systems, and the simulation results are addressed.

Multi-source data driven harmonic spectrum estimation of substation feeder current

With the proliferation of non-linear loads and distributed power resources that connect through power electronic equipment, decentralized harmonic pollution in three-phase symmetric power system becomes increasingly serious. Despite this, monitoring the current harmonic of all substation feeders regardless of cost is unrealistic. To this end, a multi-source data driven method is proposed in this paper, utilizing data from the power quality monitoring system, dispatching system, and market business system, to estimate the harmonic spectrum of substation feeder currents and estimate the harmonic current components of each feeder with monitoring data of bus voltage harmonics and line harmonic currents. The objective function of the harmonic spectrum estimation model is constructed based on the analysis of current harmonic phasor and power relationship on the feeders. An improved particle swarm optimization (PSO) algorithm is proposed to solve the proposed estimation model thereby obtaining the current harmonic content of each feeder and the phase angle difference between the current harmonics of the feeders. The performance of the proposed model and algorithm is validated by numerical simulation with a test system and an actual system.

The thermodynamic properties of diatomic gases. A rigorous analytical approach

The paper reports a closed-form analytical representation of the thermodynamic functions of diatomic molecules in the ground electronic state. For this purpose, analytical formulas for vibrational and rotational partition functions are derived. A rigorous method is proposed for factorizing the vibrational and rotational contributions to the ro-vibrational partition function using an average vibrational quantum number. The behavior of thermodynamic functions as a function of temperature is discussed for carbon monoxide as a test system. The reliability of the analytical method is verified by comparison with experimental data and with the direct summation method, which uses theoretical values of energy levels.

Load frequency control of interconnected power system using cuckoo search algorithm

This paper presents a new time-domain multi-objective function approach for solving load frequency control issue in an interconnected power system. The performance of interconnected power system in each area is validated for overshoot and settling time values of frequency change and tie-line power exchange. An objective function is created with the goal of enhancing proportional integral derivative (PID) controller settings by reducing overshoot and achieving faster time-domain settling times. The efficiency of the proposed time-domain multi-objective function is evaluated in a two-area thermal power plant using a nature-inspired cuckoo search optimization (CSA) technique. By comparing the time-domain simulation results of the test system with the existing integral error-based objective functions IAE, ISE, ITAE, and ITSE, the proposed objective function is validated. Further, a sensitivity analysis were carried out to analyze the robustness of the proposed multi-objective function under various uncertain conditions.

Multi-objective economic load dispatch using hybrid NSGA-II and PVDE techniques

Over decades, numerous methods have been used to optimize objective functions. Where cost and emissions clash. The improved non-dominated sorting genetic algorithm (NSGA-II) employs elitism to discover the optimum value and speed convergence in multi-objective optimization problems. Population variant differential evolution algorithm alters differential evolution (DE). The main distinction between DE and population variant differential evolution algorithm (PVDE) is population replenishment. NSGA-II and PVDE are combined in the suggested hybrid approach. The hybrid technique solves multi-objective optimization problems efficiently by combining two or more methods. The hybrid technique solves multi-objective optimization problems well. This optimization problem pits cost vs pollution. The hybrid approach exposes half the population to the NSGA-II algorithm and half to the PVDE algorithm. In optimization problems with opposing aims, such as minimizing costs and emissions, a hybrid technique is utilized to find the optimal solution. Elitist diversity-preserving strategies avoid optimization issues becoming converging too soon. A 10-generator IEEE 39 bus test system was validated using this method. The hybrid NSGA-II and PVDE methodology achieves global optimal solutions with more durability, simplicity, and optimization performance than existing methods.

Development of a dynamic traffic microsimulator for on-demand transit operations within an integrated modelling system

ABSTRACT This study develops an intelligent dynamic agent-based microsimulation (iDAMS) module for on-demand transit (ODT) operations within an integrated transport, land-use and energy (iTLE) model. A real-time optimization component within the iDAMS is formulated by the utilization of travelling salesman problem and simulated annealing metaheuristics that perform dynamic passenger-vehicle assignment. It simulates ODT operations for meeting the 24-hour auto-trip demand of Halifax, Canada, to compare the performance of the proposed system with personal cars (PCs). The optimization objectives are to determine the optimal fleet size and seat capacity that satisfies maximum trip requests while minimizing waiting time, travel time and vehicle kilometres travelled (VKT). Simulation results indicate that the ODT system can deliver service similar to PCs in Halifax while decreasing cost and emissions (13% reduction in VKT). The tools developed in this research will provide transit planners ability to conduct ODT scenario simulation and test system performance in real time.

Chemoreactomic analysis of the antioxidant properties of vitamin B12 derivatives

Background. Synthetic derivatives of vitamin B12 exhibit various physical, chemical and pharmacological properties. The development of methods for predicting the properties of these molecules based on their chemical structure is important for the targeted organic synthesis of corrins with the desired properties and range of applications in pharmacology.Objective: chemoreactomic assessment of the antioxidant effects of vitamin B12 and its derivatives: aquacobalamin, diaquacobinamide, aquacyano-forms of heptaethanolamine-, heptaethylenediamine-, heptamethyl- and heptabutylcobyrinates.Material and methods. The study was conducted using the method of chemoreactomic analysis, implemented within the framework of the algebraic theory of recognition and topological data analysis and based on the theory of isomorphism of labeled graphs and modern methods for predicting numerical target variables. To carry out chemoinformatic chemoreactome analysis, a special problem-oriented theory was developed within the boundaries of the combinatorial theory of solvability and the antioxidant properties of vitamin B12 derivatives were assessed (140 activities in total).Results. Significant differences were found in the properties of the studied substances in relation to oxidative stress. In test systems based on the oxidant 1,1-diphenyl-2-picrylhydrazyl, at different exposure times to molecules (15–60 min) in different concentrations (10–125 μM, 50–3000 μg/ml), aquacobalamin exhibited the most pronounced antioxidant properties at lower concentrations (up to 100 µM). At higher concentrations of substances (125 μM), the antioxidant activity of other vitamin B12 derivatives was higher. All studied molecules had a moderate antimicronutrient effect (total score of about 3.0; for most synthetic drugs, this score is higher than 3.6). Aquacobalamin was characterized by еhe least pronounced antimicronutrient effect (total score less than 0.8), which indicates an almost complete absence of antivitamin and antimineral action, corresponding to an average increase in the risk of a particular micronutrient excretion by no more than 5%.Conclusion. All the studied compounds exert antioxidant properties to one degree or another. Regardless of the choice of simulated test systems for assessing oxidative stress, aquacobalamin demonstrated antioxidant effects to the greatest extent and practically did not stimulate the loss of other micronutrients.

Influenza surveillance in pigs: balancing act between broad diagnostic coverage and specific virus characterization

BackgroundMonitoring of infectious diseases on swine farms requires a high diagnostic sensitivity and specificity of the test system. Moreover, particularly in cases of swine influenza A virus (swIAV) it is desirable to include characterization of the virus as precisely as possible. This is indispensable for strategies concerning prophylaxis of swIAV and furthermore, to meet the requirements of a purposeful monitoring of newly emerging swIAV strains in terms of vaccine design and public health. Within the present cross-sectional study, we compared the diagnostic value of group samples (wipes of surfaces with direct contact to mouth/nose, dust wipes, udder skin wipes, oral fluids) to individual samples (nasal swabs, tracheobronchial swabs) for both swIAV identification and characterization. Sampling included different stages of pig production on 25 sow farms with attached nursery considered as enzootically infected with swIAV. Firstly, samples were analyzed for IAV genome and subsequently samples with Ct-values < 32 were subtyped by multiplex RT-qPCR.ResultsNasal swabs of suckling piglets and nursery pigs resulted in a higher odds to detect swIAV (p < 0.001) and to identify swIAV subtypes by RT-qPCR (p < 0.05) compared to nasal swabs of sows. In suckling piglets, significant higher rates of swIAV detection could be observed for nasal swabs (p = 0.007) and sow udder skin wipes (p = 0.036) compared to contact wipes. In the nursery, group sampling specimens were significantly more often swIAV positive compared to individual samples (p < 0.01), with exception of the comparison between contact wipes and nasal swabs (p = 0.181). However, in general nasal swabs were more likely to have Ct-value < 32 and thus, to be suitable for subtyping by RT-qPCR compared to dust wipes, contact wipes, udder skin wipes and tracheobronchial swabs (p < 0.05). Interestingly, different subtypes were found in different age groups as well as in different specimens in the same holding.ConclusionAlthough population-based specimens are highly effective for swIAV monitoring, nasal swabs are still the preferable sampling material for the surveillance of on-farm circulating strains due to significantly higher virus loads. Remarkably, sampling strategies should incorporate suckling piglets and different age groups within the nursery to cover as many as possible of the on-farm circulating strains.

Network equivalent-based VQ Curve method and its application in a novel real-time voltage stability assessment methodology

The PV and VQ curves have been widely accepted tools for monitoring voltage stability. Although these curves have been used in offline studies, their online applications are not trivial, involving specific issues and complexities concerning real-time environment. The literature presents some approaches to determine quantities related to voltage stability limit in real-time analysis of the PV curve. However, it does not occur with the corresponding quantities for the VQ curve, making it difficult to analyze these curves jointly. This work presents two significant innovative contributions, based on the use of real-time network equivalents estimated through measurement data. The first is a technique suitable for real-time applications to calculate the complete VQ curve, called Network Equivalent-based VQ Curve. The second is a methodology for determining voltage stability margins using information from both PV and VQ curves. Simulations were carried out in RVS Test System, and 9, 14, 30 and 118 Bus Test Cases available in MATPOWER. The results of Network Equivalent-based VQ Curve application were validated by power flow solution. The voltage stability assessment methodology proposed in this paper represents a significant advance, going beyond the traditional approaches.

Decoding IELTS writing performance: Grammatical Clauses mastery by Universitas Ahmad Dahlan students

Indonesian learners of English produced ungrammaticalities in their writing for the International English Language Testing System (IELTS) and faced complicated writing score descriptors for self-evaluations and improvements. These problems were observed among students at Universitas Ahmad Dahlan during their preparatory course for IELT. To address this issue, this study focused on identifying some rules in grammar, the grammatical and ungrammatical clauses based on subject-verb (S + V) structures in their writing performances and measuring the proportions of the two clause types in accordance with the performance’s score variation. Both qualitative and quantitative methods were employed. To do so, the study conducted archival research by retrieving data from the teacher's course documents. The archived handwritten writing performances were transcribed manually into digital texts. It employed syntactic analysis to classify the clauses as either grammatical or ungrammatical. It converted the numbers of each clause type per performance into percentages for comparison, and grouped them according to the different scores as the variable. The results showed that the participants produced predominantly simple grammatical clauses to minimize failures when generating more complex structures. To achieve the minimum score of 6 in the writing section, the proportion of grammatically correct and incorrect clauses should be above 47% and below 53%, respectively. These findings offer valuable insights into predicting scores, especially concerning the dimension of 'grammatical range and accuracy in the writing assessment, which benefit both learners and educators.

Effects of Unbalanced Incentives on Threshing Drum Stability during Rice Threshing

As a result of the uneven growth of rice, unbalanced vibration of threshing drum caused by stalk entanglement in combine harvester is more and more severe. In order to reveal the influence of unbalanced excitation on the roller axis locus during rice threshing, the stability of threshing drum was studied. The dynamic signal test and analysis system are used to test the axial trajectory of threshing drum. At the same time, the influence of the unbalanced excitation caused by the axis winding on the axis trajectory is analyzed by the experimental results. Axis locus rules under no-load and threshing conditions are obtained. In order to simulate the axial and radial distribution of unbalanced excitation along the threshing drum, the counterweight was distributed on the threshing drum instead of the entangled stalk. Then, the definite effect of unbalanced excitation on the rotating stability of threshing drum is analyzed. Results show that the amplitude of stem winding along the grain drum is larger in the vertical direction and smaller in the horizontal direction when compared with the unloaded state under 200 g weight. It was found that the amplitude in both horizontal and vertical directions decreased after 400 g and 600 g counterweights were added, respectively, to simulate the radial distribution of stalk winding along the grain barrel. Finally, it can be seen that with the increase in the weight of the counterweight, the characteristics of the trajectory misalignment of the threshing cylinder axis become more and more obvious. This study can provide reference for reducing the unbalanced excitation signal of threshing drum and improving driving comfort.

Expert knowledge data-driven based actor–critic reinforcement learning framework to solve computationally expensive unit commitment problems with uncertain wind energy

With the expansion of power grid, unaffordable computational cost and time will pose serious challenges of time-efficient scheduling in unit commitment problem (UCP). However, existing optimization methods, i.e., mathematical programming methods and meta-heuristic algorithms, are powerless and time-consuming to handle computationally expensive UCP (CEUCP). Thus, reinforcement learning methods with strong inference and time-saving performances are motivated to solve the computationally expensive challenges in tackling CEUCPs. In this paper, a novel expert knowledge data-driven based actor–critic (AC) reinforcement learning methodology is proposed for solving CEUCPs. Specifically, in the proposed AC reinforcement learning methodology, expert knowledge, data-driven surrogate model, and improved meta-heuristic algorithm are integrated for further performance enhancement. Firstly, a novel action selection mechanism (based on the expert knowledge of thermal units characteristic) is integrated into AC to improve the efficiency of network training. Secondly, an improved extreme learning machine (ELM) data-driven surrogate model is proposed to build reward function in AC. In detail, original cost function in reward is replaced by a lightweight ELM model. Shape distance is integrated into ELM for enhancing accuracy. Finally, original marine predators algorithm (MPA) is improved for obtaining optimal dispatching decisions and rewards of AC method quickly and correctly. Original search pattern is replaced by quantum based representation for boosting convergence. The excellent performances of the proposed AC framework are verified by simulations of 10-units, 100-units, and 100-units with wind energy test systems.

Development of novel magnetorheological dampers with low-speed sensitivity for flying car suspensions

Abstract As urban traffic environments continue to grow in complexity, there is an urgent need for a versatile mode of transportation that seamlessly transitions between terrestrial and aerial mobility. In these conventional magnetorheological damper (CMRD), the magnetorheological (MR) fluid flowing through the narrow annular gap between the piston and cylinder in CMRD results in a damping force directly proportional to velocity. As velocity increases, the damping force rises sharply, posing a significant risk to the vehicle's mechanical structure and passenger safety. This velocity sensitivity restricts their applications primarily to standard commercial vehicle suspension systems. They face significant challenges when it comes to high-speed impact scenarios. To overcome this limitation, enhance the shock-absorbing capacity of flying cars, ensure passenger safety, and improve passenger comfort during the landing phase, this study introduces a novel magnetorheological damper (NMRD) with unique internal channel structure embedded in a circular permanent magnet. In road travel mode, flying cars equipped with NMRD can maintain a broad dynamic range. During the landing process with high-speed impact, the specialized channel activates to reduce the peak impact force effectively. This feature greatly expands the application range of magnetorheological dampers (MRD). The researches included simulations of the electromagnetic induction phenomenon within the piston, followed by numerical analyses and impact tests to compare the velocity sensitivity of these two distinct impact dampers. Experimental evaluations were conducted using a material testing system (MTS), the peak force and peak acceleration experienced by the two dampers during impact were tested using a dedicated drop hammer apparatus. These tests demonstrate that the NMRD exhibits superior impact resistance performance compared to CMRD. This highlights the promising potential for the NMRD's application within the suspension systems of flying cars.&amp;#xD;

Improved mountain gazelle optimizer based interactive distributed strategy to solving large scale OPF

Abstract this paper focuses on solving with accuracy the multi objective optimal power flow of large-scale power systems under critical loading margin stability using a novel improved mountain gazelle optimizer (IMGO)-based flexible distributed strategy. Multi-shunt compensator-based flexible AC transmission systems (FACTS), such as SVC and STATCOM devices, are integrated at specified locations to exchange reactive power with the network. It is well known that several metaheuristic methods are able to solve the standard OPF related to small and medium test systems with success. However, by considering large-scale electric systems based on FACTS devices and renewable energy and by considering the operation under loading margin stability, the majority of these techniques fail to achieve the near-global solution due to the high dimension and nonlinearity of the problem to be solved. In this study, a new planning strategy, namely the Multi-Objective OPF-Based Distributed Strategy (MO-OPFDS), is proposed to optimize individually and simultaneously various objective functions, in particular the total power loss (T∆P), and the total voltage deviation (T∆V). The mechanism search of the standard MGO is improved by dynamically adjusting exploration and exploitation during the search process. The robustness of the proposed variant was validated on the large electric test system, the IEEE 118-Bus, and on the Algerian Network 114-Bus under normal conditions and at critical loading margin stability. The obtained results compared to several recent techniques clearly confirm the high performance aspect of the proposed method in terms of solution accuracy and convergence behaviors.&amp;#xD;

First-Principles and Experimental Study of Ge, V, Ta-Doped AgNi Electrical Contact Materials

To explore the stability, electrical, and mechanical characteristics of undoped AgNi alongside AgNi doped with elemental Ge, V, and Ta, we performed calculations on their electronic structures using density functional theory from first-principles. We also prepared AgNi(17) and AgNi-x(Ge, V, Ta) electrical contact materials using the powder metallurgy technique, and they were subsequently assessed experimentally. The electrical properties of these materials were evaluated under a 24 V/15 A DC-resistive load using the JF04D contact material testing system. A three-dimensional morphology scanner was employed to examine the contact surface and investigate the erosion patterns of the materials. Our findings indicate that doping with metal elements significantly enhanced the mechanical properties of electrical contacts, including conductivity and hardness, and optimizes arc parameters while improving resistance to arc erosion. Notably, AgNi-Ge demonstrated superior conductivity and arc erosion resistance, showing significant improvements over the undoped AgNi contacts. This research provides a theoretical foundation for selecting doping elements aimed at enhancing the performance of AgNi electrical contact materials.

Therapeutic Promises of Bioactive Rosavin: A Comprehensive Review with Mechanistic Insight.

Rosavin is an alkylbenzene diglycoside primarily found in Rhodiola rosea (L.), demonstrating various pharmacological properties in a number of preclinical test systems. This study focuses on evaluating the pharmacological effects of rosavin and the underlying molecular mechanisms based on different preclinical and non-clinical investigations. The findings revealed that rosavin has anti-microbial, antioxidant, and different protective effects, including neuroprotective effects against various neurodegenerative ailments such as mild cognitive disorders, neuropathic pain, depression, and stress, as well as gastroprotective, osteoprotective, pulmoprotective, and hepatoprotective activities. This protective effect of rosavin is due to its capability to diminish inflammation and oxidative stress. The compound also manifested anticancer properties against various cancer via exerting cytotoxicity, apoptotic cell death, arresting the different phases (G0/G1) of the cancerous cell cycle, inhibiting migration, and invading other organs. Rosavin also regulated MAPK/ERK signaling pathways to exert suppressing effect of cancer cell. However, because of its high-water solubility, which lowers its permeability, the phytochemical has low oral bioavailability. The compound's relevant drug likeness was evaluated by the in silico ADME, revealing appropriate drug likeness. We suggest more extensive investigation and clinical studies to determine safety, efficacy, and human dose to establish the compound as a reliable therapeutic agent.

Research on a dedicated thin-film thermocouple testing system for transient temperature measurement.

Abstract The thin-film thermocouple (TFTC) is featured on small heat capacity and rapid response speed for transient temperature measurements under narrow space and difficult installation. Consequently, we propose a novel transient temperature testing system specifically designed for TFTC. This system features signal conditioning circuits with extended bandwidth and superior transfer speeds, a cold junction compensation method that supports customizable indexing tables, and an adaptive data filtering approach that precisely balances the smoothing of steady-state data with rapid responsiveness to transient data. This approach effectively mitigating the measurement distortion of transient temperature signals and the nonlinear phenomenon in cold junction compensation for TFTC. Utilizing NiCr/NiSi TFTC, we evaluated the system's accuracy, demonstrating a precision range of -0.5 to 0.25 °C within 20 - 100 °C, and a response delay under 0.1 ms. Compared to traditional thermocouple measurement systems, our system exhibits a finer time-domain resolution. Lastly, we successfully applied this system to observe the response of TFTC under the thermal load of short-pulse laser shocks, measuring a time constant of only 1.16 ms for the TFTC. This novel transient temperature testing system provides a new approach for TFTC to achieve online dynamic measurement and online calibration, and provides technical support for TFTC measurement technology towards engineering applications.

Digital twin-based probabilistic prediction of microcrack initiation and propagation in the weld zone of orthotropic steel deck

Orthotropic steel deck (OSD) has become the primary bridge deck structure for steel bridges, but it is vulnerable to fatigue cracks in the weld zone of OSD under traffic loading. This study proposes a digital twin (DT)-based framework to give the probabilistic prediction of microcrack initiation and propagation in the weld zone of OSD. The DT-based framework couples crystal plasticity finite element model (CPFEM) simulations with fatigue tests through Dynamic Bayesian Network (DBN). The fatigue tests of the specimen (physical entity) cut from the weld zone of OSD and sliced to the centimeter scale are carried out using the standard dynamic test system together with optical microscope. The CPFEM simulations are used to develop a multiscale virtual entity to map the physical entity. The role of the DBN is to integrate the uncertainties into a hierarchical network. After completing the updating of uncertainties in the virtual entity via DBN, the microcrack propagation is predicted probabilistically by the DBN inference, and the microcrack initiation is predicted probabilistically by the inverse DBN inference. The results demonstrate the feasibility and accuracy of the DT-based framework for a full prediction of microcrack initiation and propagation in the weld zone of OSD.

Syntheses and Conformatios a Trinuclear Gold(I) System Based on a Triethinyl‐trisilacyclohexane Scaffold

Trisilacyclohexanes and bissilylmethanes with acetylene units attached to silicon sites have been converted into tri‐ and dinuclear gold(I)phosphane complexes and characterized by NMR spectroscopy and X‐ray diffraction. The bissilylmethane‐based gold complexes were used as a test system to work out the synthetic routes before transferring them to the trisilacyclohexane scaffolds, because the latter are more difficult to access. The occurrence of aurophilic interactions (short Au···Au contacts) depends on the steric bulk of the phosphorus‐bonded alkyl and aryl groups. DFT studies show that dispersion effects play an important role in the ability to form intramolecular Au···Au interactions. QTAIM analyses show that a subtle change of the steric bulk of the phosphane groups alters the relative strength of the dispersion and aurophilic interactions. The combination of DFT studies and X‐ray diffraction experiments shows that the conformation of the trisilacyclohexane backbone is also phase dependent.

Optimizing power system stability: A hybrid approach using manta ray foraging and Salp swarm optimization algorithms for electromechanical oscillation mitigation in multi‐machine systems

AbstractThis paper emphasizes the significance of ensuring adequate damping of electromechanical oscillations in power systems to ensure stable operation. Power System Stabilizers (PSSs) are influential in enhancing system damping and refining dynamic characteristics during transient conditions. However, the efficacy of PSSs is notably contingent on parameter values, particularly in the case of lead‐lag PSSs. In response to this challenge, the paper introduces a Tilt‐Integral‐Derivative (TID)‐based PSS, optimized through a novel optimization algorithm called Hybrid Manta Ray Foraging and Salp Swarm Optimization Algorithms (MRFOSSA). The MRFOSSA algorithm demonstrates robustness and enhanced convergence, validated through benchmark function tests, and outperforms competing algorithms. These superior characteristics of MRFOSSA were employed in optimal tuning of TID‐PSSs to uphold the stability of multi‐machine power systems. The MRFOSSA algorithm demonstrates robustness and enhanced convergence, outperforms competing algorithms in the optimal tuning of TID‐PSS within the Western System Coordinating Council (WSCC)‐3‐machines 9‐bus test system. In summary, the proposed TID‐PSS, coupled with the MRFOSSA algorithm, presents a promising avenue for enhancing power system stability.