分布式多元随机动态场景生成及快速精准场景降维算法

高比例新能源及多源耦合是电力系统发展的重要特征,这也为系统稳定经济运行提出了新挑战。该文以园区型多能系统为对象,研究了分布式多元随机动态场景分析,从多时空角度有效量化不确定因素给系统造成的影响,可为系统灵活重构、多维度协同运行与决策提供有力模型与场景支撑。首先由预测误差驱动拟合多元功率预测误差概率分布,全面反映随机功率出力信息,提高模型泛化性;以时序相关范围参数为数据驱动关联变量,高效动态控制波动强度;最终场景生成利用逆变换映射思想保证置信度。然后针对典型场景提取,提出一种综合递归聚类思想的多段嵌套削减算法,结合改进Wasserstein距离指标,兼具准确、时效、稳定方面的优势。最后由对比实验论证该方法的前沿有效性。     

IRS辅助的SWIPT系统中基于能效优先的波束成形设计与优化

以智能反射面(intelligent reflecting surface,IRS)辅助的无线携能通信(simultaneous wireless information and power transfer,SWIPT)系统为背景,研究了该系统中基于能效优先的多天线发送端有源波束成形与IRS无源波束成形联合设计与优化方法。以最大化接收端的最小能效为优化目标,构造在发送端功率、接收端能量阈值、IRS相移等多约束下的非线性优化问题,用交替方向乘子法(alternating direction method of multipliers,ADMM)求解。采用Dinkelbach算法转化目标函数,通过奇异值分解(singular value decomposition,SVD)和半定松弛(semi-definite relaxation,SDR)得到发送端有源波束成形向量。采用SDR得到IRS相移矩阵与反射波束成形向量。结果表明,该系统显著降低了系统能量收集(energy harvesting,EH)接收端的能量阈值。当系统总电路功耗为?15 dBm时,所提方案的用户能效为300 KB/J。当IRS反射阵源数与发送天线数均为最大值时,系统可达最大能效。     

Coupling effects of water content,temperature, oxygen density,and polytetrafluoroethylene loading on oxygen transport through ionomer thin film on platinum surface in catalyst layer of proton exchange membrane fuel cell

In this work, coupling effects of water content, temperature, oxygen density, and polytetrafluoroethylene (PTFE) loading on oxygen transport through an ionomer thin film on a platinum surface in a catalyst layer of a proton exchange membrane (PEM) fuel cell are investigated using molecular dynamics approach. Taguchi orthogonal algorithm is employed to comprehensively analyze the coupling effects in a limited number of cases. It is found that the effect of operation temperature is the weakest among the four factors, which has the smallest effect index 14.4. Coupling effects including the PTFE loadings on the oxygen transfer through the ionomer thin film is uncovered. Less PTFE loadings should be beneficial for the oxygen transfer. The chemical potential gradient is considered as the major driven force for the oxygen transport through the ionomer thin film, and oxygen density is the dominating factor, significantly affecting the chemical potential in the thin film.     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.     

Experimental and numerical investigations on the heat production and thermal storage characteristics of rapid preparation amorphous powder activated coke

The heat production and thermal storage characteristics of rapid-preparation amorphous powder activated coke (RAC) were investigated. RAC was prepared by using a drop-tube reactor system. The natural oxidation characteristics of RAC were studied through combined TG–FTIR analysis and temperature-programmed experiment. Experimental results showed that CO and CO₂ were the main oxidation products of RAC in air, and that the oxidation reaction was in accordance with the Arrhenius equation and law of mass action. Thermal storage characteristics were studied through computational fluid dynamics simulation. The maximum excess temperature θ_max increases linearly with the increase of the initial temperature. The concentration fields of the products show that CO₂ is mainly concentrated in the upper part of the coke bin, and the CO generated by CO₂ at high temperature is mainly concentrated in the central part of the coke bin.     

Systematic analysis and multi-objective optimization of an integrated power and freshwater production cycle

This study represents the results of the analysis and optimization of an integrated system for cogenerating electricity and freshwater. This setup consists of a Solid Oxide Fuel cell (SOFC) for producing electricity. Unburned fuel of the SOFC is burned in the afterburner to increase the temperature of the SOFC's outlet gasses and operate a Gas turbine (GT) to produce additional power and operate the air compressor. At the bottom of this cycle, a combined setup of a Multi-Effect Desalination (MED) and Reverse Osmosis (RO) is considered to produce freshwater from the unused heat capacity of the GT's exhaust gasses. Also, a Stirling engine is used in the fuel supply line to increase the fuel's temperature. Using LNG and the Stirling engine will replace the fuel compressor with a pump which increases the system performance and eliminates the need for the expansion valve. To study the system performance a mathematical model is developed in Engineering Equation Solver (EES) program. Then, the system's simulated data from the EES has been sent to MATLAB to promote the best operating condition based on the optimization criteria. An energetic, exergetic, economic, and environmental analysis has been performed and a Non-dominated Sorting Genetic Algorithm (NSGA-II) is used to achieve the goal. The two-objective optimization is performed to maximize the exergetic efficiency of the proposed system while minimizing the system's total cost of production. This cost is a weighted distribution of the Levelized Cost of Electricity (LCOE) and Levelized Cost of freshwater (LCOW). The results showed that the exergetic and energetic efficiencies of the system can reach 73.5% and 69.06% at the optimum point. The total electricity production of the system is 99 MW. The production cost is 11.71 Cents/kWh, of which 1.04 Cents/kWh is emission-related and environmental taxes. The freshwater production rate is 42.44 kg/s which costs 4.38 USD/m³.     

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.     

Techno-economic assessment of hydrogen refueling station: A case study in Croatia

Hydrogen refueling station (HRS) capacity and location depend on the users, which makes it difficult to select the most favorable option before potential users are actually identified. As in Croatia, at least for now, there are no hydrogen users, this study considers a wide range of HRS capacities and their different configurations. These include hydrogen production and charging station within one existing wind farm in Croatia or both nearby the users, the hydrogen production within the wind farm and the charging station nearby the users, while hydrogen is delivered to the station with a tube trailer, and configuration of hydrogen production within the wind farm with a mobile charging station in case of several users in different locations. Each HRS configuration is evaluated by the obtained levelized cost of hydrogen depending on the capital, and operation and maintenance costs within the HRS techno-economic analysis provided.     

Effects of multiple freeze–thaw cycles on meat quality,nutrients, water distribution and microstructure in bovine rumen smooth muscle

This study investigated the effect of 5 freeze–thaw cycles (freezing at −18°C for 12 h and then thawing at 4°C for approximately 12 h) on the meat quality, proximate composition, water distribution and microstructure of bovine rumen smooth muscle (BSM). As the number of freeze–thaw cycles increased, BSM pH, shear force, water content and protein content decreased by 3.06%, 35.50%, 14.49% and 21.11%, respectively, whereas BSM thawing loss, cooking loss, pressing loss, total aerobic count (TAC), ash content and fat content increased by 108.12%, 47.75%, 78.33%, 90.99%, 105% and 35.20%, respectively. The freeze–thaw cycles resulted in greater protein and lipid oxidation, as evidenced by a 36.46% reduction in the sulfhydryl content and a 209.06% and 338.46% increase in the carbonyl and malondialdehyde contents, respectively. Ice crystal formation disrupted the structural integrity of the muscle tissue. Low-field nuclear magnetic resonance results showed that the freeze–thaw cycles prolonged the relaxation times (T_2b, T₂₁ and T₂₂), indicating that immobile water shifted to free water, and consequently, free water mobility increased. After 3 freeze–thaw cycles, the decline in shear force slowed, the increase in thawing loss became accelerated, and the TAC approached the domain value (6 log colony-forming units/g). Therefore, the number of freeze–thaw cycles of smooth muscle during transport, storage and distribution should be controlled to 3 or fewer. The current results provide a theoretical basis and data support for the further utilisation and culinary processing of smooth muscle.     

Direct shear behavior of gravel-rubber mixtures: Discrete element modeling and microscopic investigations

In this paper, a newly developed 3-dimentional discrete element model (DEM) for gravel-rubber mixtures (GRMs), namely DEM4GRM, that is capable of accurately describing the macro-scale shear response (from small to large deformation) of GRMs in a direct shear box apparatus is presented. Rigid gravel grains are modelled as simple multi-shape clumps, while soft rubber particles are modeled by using deformable 35-ball body-centered-cubic clusters. Mixtures are prepared with different volumetric rubber content (VRC) at 0, 10, 25, 40 and 100%, statically compressed under 30, 60 and 100 kPa vertical stress and then sheared, by closely simulating a reference laboratory test procedure. The variation of micro-scale factors such as fabric, normal and tangential force anisotropy is carefully examined throughout the shearing process and described by means of novel micro-mechanical relationships valid for GRMs. Moreover, strong-force chains are scrutinized to identify the transition from rigid to soft granular skeleton and gain insights on the load transfer and deformation mechanisms of GRMs. It is shown that the development of the fabric and force anisotropy during shearing is closely related to the macro-scale shear strength of GRMs, and strongly depends on the VRC. Besides, strong-force chains appear to be primarily formed by gravel-gravel contacts (resulting in a rigid-like mechanical behavior) up to VRC = 30%, and by rubber-rubber contacts (causing a soft-like mechanical response) beyond VRC = 60%. Alternatively, at 30% < VRC < 60%, gravel-rubber contacts are predominant in the strong-force network and an intermediate mechanical behavior is observed. This is consistent with the behavioral trends observed in the macro- and micro-mechanical responses.