Optimal design and operation of integrated microgrids under intermittent renewable energy sources coupled with green hydrogen and demand scenarios

Renewable energy integration into existing or new energy hubs together with Green technologies such as Power to Gas and Green Hydrogen has become essential because of the aim of keeping the average global temperature rise within 2 ^°C with regard to the Paris Agreement. Hence, all energy markets are expected to face substantial transitions worldwide. On the other hand, investigation of renewable energy systems integrated with green chemical conversion, and in particular combination of green hydrogen and synthetic methanation, is still a scarce subject in the literature in terms of optimal and simultaneous design and operation for integrated energy grids under weather intermittency and demand uncertainty. In fact, the integration of such promising new technologies has been studied mainly in the operational phase, without considering design and management simultaneously. Thus, in this work, a multi-period mixed-integer linear programming (MILP) model is formulated to deal with the aforementioned challenges. Under current carbon dioxide limitations dictated by the Paris Agreement, this model computes the best configuration of the renewable and non-renewable-based generators, their optimal rated powers, capacities and scheduling sequences from a large candidate pool containing thirty-nine different equipment simultaneously. Moreover, the effect of the intermittent nature of renewable resources is analyzed comprehensively under three different scenarios for a specific location. Accordingly, a practical scenario generation method is proposed in this work. It is observed that photovoltaic, oil co-generator, reciprocating ICE, micro turbine, and bio-gasifier are the equipment that is commonly chosen under the three different scenarios. Results also show that concepts such as green hydrogen and power-to-gas are currently not preferable for the investigated location. On the other hand, analysis shows that if the emission limits are getting tightened, it is expected that constructing renewable resource-based grids will be economically more feasible.     

高耸桥墩保护性爆破拆除关键技术

为解决高耸钢砼桥墩上部倾斜导致的工程质量不合格问题,采用保护性控制爆破将上部倾斜部分钢砼桥墩予以拆除,同时保留下部未偏斜部分桥墩不受破坏。采用开设组合形状切口,预开定向窗、导向窗;设置组合高差卸荷槽,预伤钢筋弱化抗压抗拉能力为关键措施的控制爆破方案。方案实施取得了十分满意的效果,上部拟拆除部分桥墩顺利倾倒下坠,下部保留部分桥墩完好无损。采用保护性控制爆破技术能高效、安全地解决类似高耸钢砼桥墩(构筑物)部分拆除、部分保留利用的问题,并能取得可观的经济、社会效益。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Inversion,chemical complexity,and interstitial transport in spinels

Spinels with the generic chemical formula AB₂O₄ have potential applications in nuclear energy and batteries. In both cases, their functionality is related to mass transport through the crystal. Here, using long-time atomistic simulations, we examine the impact of the cation structure on interstitial transport in two spinel chemistries, inverse MgGa₂O₄ and double MgAlGaO₄. We emphasize two aspects of the transport properties: the unit mechanisms that are described by individual barriers, for which we introduce pole-figure-like plots, and the aggregate behavior of those unit mechanisms. Compared to previous work on normal spinels, we find that inversion significantly reduces the rate of interstitial transport in these structures and has an impact on the stability of defects as they move through the lattice. In particular, B cation interstitials are found to be kinetically stable only in the inverse MgGa₂O₄. These results provide new insight into relationship between structure, chemistry, and transport in spinels.     

梁结构振动支承约束反力控制

支承或连接构件对梁结构的动力学性能有至关重要影响,必须保证其在振动过程中不发生破坏或者失效。通过合理设计和布局附加弹性支承可以实现对这些重要连接构件所承受约束反力的控制。应用微分变换法推导含附加支承的梁结构支承约束反力及其对于附加支承位置和刚度的灵敏度表达式,并通过优化设计附加支承位置和刚度实现具有弹性约束端的简支梁结构各支承约束反力的平衡,可提高结构的动力学性能。     

Sizing of multi-stage Op Amps by combining design equations with the gm/ID method

Analog integrated circuit design has as integral parts both analytical reasoning and numerical validation in the process from topology construction to sizing. Given a circuit topology, different circuit sizing results can be obtained from different processes of sizing inference. Sizing methods by simulation-based numerical searching have been a continuously studied subject. However, almost all approaches in this category require an overwhelming number of circuit simulations to arrive at an optimized sizing result. On the other hand, many published manual sizing methods by using the conventional device equations also require repeated SPICE simulations to correct the equation-based sizing results. This paper proposes a systematic gm/ID-based initial sizing method specifically customized for designing multiple-stage operational amplifiers (Op Amps). A main feature of the proposal is to use circuit-level design equations as constraints on the gm/ID table lookup method to substantially reduce the uncertainty in the sizing calculations. As a result, a significant amount of SPICE based correction work can be reduced to complete an initial sizing. The proposed sizing procedure includes a few regular sizing rules customized to the configuration of multi-stage Op Amps. We validate the proposed sizing method by application to several multi-stage Op Amp examples with a capacitive load or Miller compensation. Simulations have justified that the produced initial sizing results can achieve most of the prespecified design targets.     

Stem Photosynthesis—A Key Element of Grass Pea (Lathyrus sativus L.) Acclimatisation to Salinity

Grass pea (Lathyrus sativus) is a leguminous plant of outstanding tolerance to abiotic stress. The aim of the presented study was to describe the mechanism of grass pea (Lathyrus sativus L.) photosynthetic apparatus acclimatisation strategies to salinity stress. The seedlings were cultivated in a hydroponic system in media containing various concentrations of NaCl (0, 50, and 100 mM), imitating none, moderate, and severe salinity, respectively, for three weeks. In order to characterise the function and structure of the photosynthetic apparatus, Chl a fluorescence, gas exchange measurements, proteome analysis, and Fourier-transform infrared spectroscopy (FT-IR) analysis were done inter alia. Significant differences in the response of the leaf and stem photosynthetic apparatus to severe salt stress were observed. Leaves became the place of harmful ion (Na⁺) accumulation, and the efficiency of their carboxylation decreased sharply. In turn, in stems, the reconstruction of the photosynthetic apparatus (antenna and photosystem complexes) activated alternative electron transport pathways, leading to effective ATP synthesis, which is required for the efficient translocation of Na⁺ to leaves. These changes enabled efficient stem carboxylation and made them the main source of assimilates. The observed changes indicate the high plasticity of grass pea photosynthetic apparatus, providing an effective mechanism of tolerance to salinity stress.     

How Far Are We from Prescribing Fasting as Anticancer Medicine?

(1) Background: the present review provides a comprehensive and up-to date overview of the potential exploitation of fasting as an anticancer strategy. The rationale for this concept is that fasting elicits a differential stress response in the setting of unfavorable conditions, empowering the survival of normal cells, while killing cancer cells. (2) Methods: the present narrative review presents the basic aspects of the hormonal, molecular, and cellular response to fasting, focusing on the interrelationship of fasting with oxidative stress. It also presents nonclinical and clinical evidence concerning the implementation of fasting as adjuvant to chemotherapy, highlighting current challenges and future perspectives. (3) Results: there is ample nonclinical evidence indicating that fasting can mitigate the toxicity of chemotherapy and/or increase the efficacy of chemotherapy. The relevant clinical research is encouraging, albeit still in its infancy. The path forward for implementing fasting in oncology is a personalized approach, entailing counteraction of current challenges, including: (i) patient selection; (ii) fasting patterns; (iii) timeline of fasting and refeeding; (iv) validation of biomarkers for assessment of fasting; and (v) establishment of protocols for patients’ monitoring. (4) Conclusion: prescribing fasting as anticancer medicine may not be far away if large randomized clinical trials consolidate its safety and efficacy.     

基于化学监督的超(超)临界机组关键控制节能指标分析及建议

针对超(超)临界机组参数提高、材质升级,化学技术监督中的监督指标对机组经济性和可靠性影响较大的问题,本文通过机组典型案例分析、技术监督报告、现场实测等,对目前化学监督中影响较大的、关键的技术指标进行了系统性的分析研究。研究结果找出了6项化学监督中超(超)临界机组关键的、影响较大的控制监督指标,且提出了指标控制值和控制方法。这项系统性研究分析方法对指导超(超)临界机组化学监督具有重要的借鉴作用,以控制超(超)临界机组因参数提高和材质升级带来的新问题和新挑战。     

差分准对立学习多目标蚁狮算法

为解决多目标优化问题，对经典的蚁狮算法进行改进，提出了基于差分进化的准对立学习多目标蚁狮算法（DEQOMALO）。该算法针对蚁狮算法易陷入局部最优的不足，一方面，该算法引用差分进化的思想，充分利用种群和精英蚁狮的信息对原算法中蚂蚁个体的位置更新方式进行改进；另一方面采用反向学习策略对蚂蚁种群进行优化，将原种群个体和其准对立个体进行混合并择优作为新的种群，大大增加种群的多样性。选取典型的标准测试函数，将提出的算法与原始蚁狮算法以及其他传统进化策略优化的蚁狮算法进行比较。实验结果表明，改进算法在收敛性和分布性上均有很大程度的提升，在解决双目标优化问题上具有较好的鲁棒性和有效性。