Electromagnetic transients in the control system of output parameters of a solar power plant in Tajikistan Central Asia region

At present, as the demand for electricity increases in all sectors, there is an urgent need to introduce alternative renewable energy sources into modern energy systems. Renewable energy sources, which consist of solar (photovoltaic, PV), wind and hydro power, are key alternative sources of “green energy’’ energies, but it can also be used to produce “green” hydrogen. Thanks to scientific and technological progress, the cost of photovoltaic solar radiation converters is constantly decreasing at a high rate, which makes it possible to build solar power plants of sufficiently large capacity. In the coming decades, solar energy will become an incentive for the economic development of countries that have the maximum “solar” resource. The Republic of Tajikistan is one of these countries with a high potential for solar energy.The article presents an analysis of the resources and potential of solar energy in the Republic of Tajikistan. The study of electromagnetic transients in networks with photovoltaic solar power plants is performed. The main equations, simulation model and calculations of transients are presented, taking into account changes in voltage on DC buses. An algorithm for controlling the system of automatic control of output parameters is proposed. The analysis of dynamic and static modes in parallel operation of a solar power plant with the grid is carried out. A block diagram and computer model is constructed in the MATLAB package together with Simulink and Power System Blockset.     

Hydrangea like composite catalysts of ultrathin Mo2S3 nanosheets assembled on N,S-dual-doped graphitic biocarbon spheres with highly electrocatalytic activity for HER

Water electrolysis is the most clean and high-efficiency technology for production of hydrogen, an ultimate clean energy in future. Highly efficient non-noble electrocatalysts for hydrogen evolution reaction (HER) are desirable for large scale production of hydrogen by water electrolysis. Especially, exposing as many active sites as possible is a vital way to improve activities of the catalysts. Herein, a series of new hydrangea like composite catalysts of ultrathin Mo₂S₃ nanosheets assembled uprightly and interlacedly on N, S-dual-doped graphitic biocarbon spheres were facilely prepared. The unique structure endowed the catalysts highly exposed edge active sites and prominently high activities for HER. Especially, the optimized catalyst Mo₂S₃/NSCS-50 exhibited as low as 106 mV of overpotential at 10 mA/cm² (denoted as ?₁₀). The catalyst also showed low Tafel slope of 53 mV/dec, low electron transfer resistance of 34 Ω and high stability evidenced by the result that the current density only attenuated 11.7% after 10 h i-t test. The catalyst has shown broad prospect for commercial application in water electrolysis.     

Hydrogen supply scenarios for a climate neutral energy system in Germany

A climate neutral energy system in Germany will most likely require green hydrogen. Two important factors, that determine whether the hydrogen will be imported or produced locally from renewable energy are still uncertain though - the import price for green hydrogen and the upper limit for photovoltaic installations. To investigate the impact of these two factors, the authors calculate cost optimized climate neutral energy systems while varying the import price from 1.25 €/kg to 5 €/kg with unlimited import volume and the photovoltaic limit from 300 GW to unlimited. In all scenarios, hydrogen plays a significant role. At a medium import price of 3.75 €/kg and photovoltaic limits of 300–900 GW the hydrogen supply is around 1200 to 1300 TWh with import shares varying from 60 to 85%. In most scenarios the electrolysis profile is highly correlated with the photovoltaic power, which leads to full load hours of 1870 h–2770 h.     

Combining a new baseboard radiator with a fan coil system for improving heating performance and reduce energy consumption

In the present work, the heating performance of a new system combined with a new modified baseboard radiator and fan coil is investigated. Using longitudinal fins with special geometry and also forced airflow at the end of the system causes that at the lower inlet water temperature compared with the conventional models, higher heat output rate be obtained. The heat output rate of the new modified system is obtained by experimental metrology based on the European Standard No. EN-442. Temperature and velocity distribution in the room space is done by simulation of the modified system in the Flovent software. Computational fluid dynamics (CFD) results are validated against experimental results and there is a good agreement between them. Also, the energy consumption of the system during the winter season is calculated in TRANSYS software. Experimental results show that the heat output rate of a new modified heating system with inlet water temperature in the range of 45–55°C is on average 4.17 times higher compared with the conventional model. CFD simulation also showed that the combined system provides good thermal comfort conditions. Energy consumption of the new system reduced about 13% compared with conventional models.     

Effect of metal oxide nanofluids on the performance of passive solar still single slope for two different absorbent plates

This study aims to improve the performances of a solar still single slope using metal oxide nanofluid (Al₂O₃–water, Cu₂O–water, and TiO₂–water). The numerical study was carried out for the climatic conditions of Agadir, Morocco, with different concentrations of nanofluids inside a basin equipped with an absorber plate with two different absorptivities. The numerical study is based on thermal balance equations applied on different solar system components and solved using the Runge Kutta method. The numerical model is validated by comparing our results with the literature available data. A comparison study of the effect of these nanofluids on solar still productivity is done. The results show that the productivity of the solar still using nanoparticles Cu₂O, TiO₂, and Al₂O₃ are 7.38, 7.1, and 7.064 kg m⁻² day⁻¹, respectively. It is obtained that the maximum efficiency of the solar still is found to be 55.27% by using cuprous oxide nanoparticles. Furthermore, an enhancement in solar still productivity of 6.36%, 19.54%, and 33.25% is obtained by dispersing 1%, 3%, and 5% volume fraction of Cu₂O nanoparticles in pure water, respectively compared to the conventional solar. Moreover, the impact of the absorptivity of the absorber plate on the solar still effectiveness is investigated. Two types of coatings are considered to change the absorber plate absorptivity. The results indicate that the efficiencies of the solar system are 58.81% and 51.77% using an absorber plate with 0.95 and 0.85 of absorptivity, respectively.     

Facile self-assembly approach to construct a novel MXene-decorated nano-sized phase change material emulsion for thermal energy storage

In recent years, phase change material emulsions (PCMEs) with enhanced energy storage capacities and good flow characteristics have drawn significant attention. However, due to the thermodynamically unstable nature and tiny particle confinement, the nanomaterial modification strategies at PCM/water interface to improve stabilities and reduce supercooling of nano-sized PCMEs (NPCMEs) are very limited and challenging. Herein, we report a facile strategy for constructing MXene-decorated NPCME with good stability, little supercooling, and high thermal conductivity by self-assembly of MXene nanosheets at PCM/water interface. The concentrations of MXene have great influences on the average droplet diameters, stabilities, and thermophysical properties of the NPCMEs. The results show that the PCMs have been well dispersed into the water in the form of quasi-spherical droplets, with average droplet diameters of 242–805 nm. The thermal conductivity of 10 wt% n-tetradecane/water NPCME containing 9 mg ml^-1 MXene is 0.693 W m^-1·K^-1, achieving an enhancement by 15.5%, as compared to that of water. Besides, the MXene-decorated paraffin/water NPCMEs exhibit little supercooling and enhanced heat storage capacities. More importantly, this facile self-assembly strategy opens a new platform for preparing high-performance NPCMEs, which can be used as novel heat transfer fluids for thermal energy storage systems.     

雪菊精油对希氏肠球菌产酪胺及相关基因表达的影响

探讨不同质量浓度雪菊精油对希氏肠球菌（Enterococcus hirae）N47产酪胺的影响机制。利用反转录实时定量聚合酶链式反应分析E. hirae在雪菊精油作用下酪氨酸脱羧途径相关基因的表达情况；利用高效液相色谱法检测不同质量浓度雪菊精油对E. hirae产酪胺的影响。并将E. hirae接入到含不同质量浓度雪菊精油的熏马肠中发酵，评估香肠pH值、菌落总数和酪胺积累量。结果表明：在E. hirae纯培养体系和熏马肠体系中，雪菊精油通过抑制微生物的生长和酪氨酸脱羧途径中tyr DC、tyr P基因的表达，降低酪胺的积累量（P＜0.05）。当雪菊精油添加量为1/2最小抑菌浓度（minimal inhibitory concentration，MIC）和MIC时，熏马肠中酪胺的含量分别为78.52 mg/kg和45.83 mg/kg，较对照组分别减少了64.72%和79.41%。     

基于乙酰胆碱酯酶和氧化应激研究海胆酮对阿尔茨海默症的作用机制

海胆酮是一种酮式类胡萝卜素，主要从海胆及藻类等海洋生物中提取。本文研究海胆酮对乙酰胆碱酯酶（acetylcholinesterase，AChE）的抑制作用，应用酶动力学、荧光光谱、圆二色光谱和分子对接技术研究海胆酮对AChE的抑制机理，并用淀粉样β蛋白片段25～35（amyloid beta-peptide 25-35，Aβ25-35）诱导大鼠肾上腺嗜铬细胞瘤细胞（PC12细胞）建立阿尔茨海默症（Alzheimer’s disease，AD）模型，研究海胆酮对AD细胞模型氧化应激损伤的作用。结果表明，海胆酮有很强的AChE抑制活性，其半抑制质量浓度为（16.29±0.97）μg/mL，抑制常数Ki为3.82 μg/mL，表现为竞争性抑制；海胆酮可诱导AChE二级结构改变，更容易与AChE活性中心氨基酸Ser200、His440、Trp84和Tyr121结合，阻碍底物碘代硫代乙酰胆碱（acetylthiocholine iodide，ATCI）与酶结合，从而引起酶活力降低。海胆酮能有效抑制Aβ25-35诱导PC12细胞的AChE活力，降低丙二醛含量，增加超氧化物歧化酶、过氧化氢酶和谷胱甘肽过氧化物酶活力，减轻Aβ25-35诱导的PC12细胞氧化应激损伤。本研究基于AChE和氧化应激阐明了海胆酮对AD的潜在作用机制，为海胆酮在功能食品、生物医药等领域的应用提供了数据支持和理论根据。     

Deterministic and probabilistic ship pitch prediction using a multi-predictor integration model based on hybrid data preprocessing,reinforcement learning and improved QRNN

The deterministic and probabilistic prediction of ship motion is important for safe navigation and stable real-time operational control of ships at sea. However, the volatility and randomness of ship motion, the non-adaptive nature of single predictors and the poor coverage of quantile regression pose serious challenges to uncertainty prediction, making research in this field limited. In this paper, a multi-predictor integration model based on hybrid data preprocessing, reinforcement learning and improved quantile regression neural network (QRNN) is proposed to explore the deterministic and probabilistic prediction of ship pitch motion. To validate the performance of the proposed multi-predictor integrated prediction model, an experimental study is conducted with three sets of actual ship longitudinal motions during sea trials in the South China Sea. The experimental results indicate that the root mean square errors (RMSEs) of the proposed model of deterministic prediction are 0.0254°, 0.0359°, and 0.0188°, respectively. Taking series #2 as an example, the prediction interval coverage probabilities (PICPs) of the proposed model of probability predictions at 90%, 95%, and 99% confidence levels (CLs) are 0.9400, 0.9800, and 1.0000, respectively. This study signifies that the proposed model can provide trusted deterministic predictions and can effectively quantify the uncertainty of ship pitch motion, which has the potential to provide practical support for ship early warning systems.