Improved Deep Q-Network for User-Side Battery Energy Storage Charging and Discharging Strategy in Industrial Parks

Battery energy storage technology is an important part of the industrial parks to ensure the stable power supply, and its rough charging and discharging mode is difficult to meet the application requirements of energy saving, emission reduction, cost reduction, and efficiency increase. As a classic method of deep reinforcement learning, the deep Q-network is widely used to solve the problem of user-side battery energy storage charging and discharging. In some scenarios, its performance has reached the level of human expert. However, the updating of storage priority in experience memory often lags behind updating of Q-network parameters. In response to the need for lean management of battery charging and discharging, this paper proposes an improved deep Q-network to update the priority of sequence samples and the training performance of deep neural network, which reduces the cost of charging and discharging action and energy consumption in the park. The proposed method considers factors such as real-time electricity price, battery status, and time. The energy consumption state, charging and discharging behavior, reward function, and neural network structure are designed to meet the flexible scheduling of charging and discharging strategies, and can finally realize the optimization of battery energy storage benefits. The proposed method can solve the problem of priority update lag, and improve the utilization efficiency and learning performance of the experience pool samples. The paper selects electricity price data from the United States and some regions of China for simulation experiments. Experimental results show that compared with the traditional algorithm, the proposed approach can achieve better performance in both electricity price systems, thereby greatly reducing the cost of battery energy storage and providing a stronger guarantee for the safe and stable operation of battery energy storage systems in industrial parks.     

Dynamics explore of an improved HR neuron model under electromagnetic radiation and its applications

The influence of electromagnetic field to neuron firing rhythm is not negligible. In order to investigate the behavior mechanism, a five-dimensional neuron model based on the Faraday's law of electromagnetic induction is improved by introducing magnetic flux variables and electric field variables on the three-dimensional Hindmarsh–Rose (HR) neuron model, and then, its rich dynamics and application in image encryption are discussed. Specifically, the equilibrium point distribution is analyzed using Matcont software and it is found that there are subcritical Hopf bifurcation and coexisting mode firing first. Second, numerical simulations are performed in terms of two-parameter bifurcation, ISI bifurcation, the maximum Lyapunov exponent and firing sequences, and the experimental results show that the new model exhibits various firing rhythms. The rich dynamic behaviors make the model more suitable for application in image encryption. So in the end, a grayscale image encryption scheme containing five parts called sparse, compression calculation, forward diffusion, rank scrambling and backward diffusion is designed by combining with the compressive sensing theory. The security analysis results show that the designed encryption scheme not only has excellent compression performance and high security, but also displays faster encryption speed. That is to say, the algorithm can be applied to the field of real encryption owning to the advantages of the lower costs of data transmission and higher efficiency of encryption. It is worth mentioning that the influence of different dimensional compression methods on the encryption and reconstruction effects is analyzed for the first time. The research results of this paper provide some ideas for perfecting the neuron model, revealing the influence of electromagnetic field on biological nervous system, and the excellent performance of the new neuron model provides theoretical guidance and experimental basis for the practical application of digital image encryption.

     

钢铁及其合金中铬含量测定结果的不确定度评定

对用GB／T223、11—1991《过硫酸铵氧化容量法测定铬量》的方法测定钢铁及合金中铬含量测量结果的不确定度进行了评定。对样品测量过程中的不确定度分量进行了分析和量化,求得铬含量测定结果的标准不确定度和扩展不确定度分别为0．06％和0．12％。     

Metabolomics Provides A Novel Interpretation of the Changes in Main Compounds during Black Tea Processing through Different Drying Methods

This study aimed to compare the effect of hot roller (HR) drying and hot air (HA) drying on the sensory evaluation, chemical quality, antioxidant activity, and metabolic profile of Yihong Congou black tea processed from E’cha NO1. The Yihong Congou black tea dried with HA obtained higher sensory scores and better chemical qualities such as the hue of tea brew color (a and b), content of theaflavins, thearubigins, water extract, free amino acids, tea polyphenol, and the ratio of polyphenol to amino acids as well as higher antioxidant capacities compared to that dried with HR. The HA drying tea increased the contents of volatile compounds that had positive correlation with sweet and flowery flavor, while the HR drying tea increased the contents of volatile compounds related to fruity flavor. Moreover, non-targeted metabolomics data indicated that the levels of most free amino acids significantly increased, while the levels of most soluble sugars reduced in the HA drying method compared to the HR drying method. The metabolic analysis was also consistent with the above results and revealed that D-ribose and gallic acid were the main characteristic metabolites of HA drying. Our results could provide a technical reference and theoretical guide to processing a high quality of Yihong Congou black tea.     

水分子辅助的一碳单元转移机理的密度泛函研究

The one-carbon unit transfer reaction catalysed by glycinamide ribonucleotide transformylase（GARTfase）is a key step in the de novo purine biosynthetic pathway. In order to give a theoretical research of the assumption from the experiments,the water-assisted mechanism in GAR Tfase catalysed one-carbon unit transfer reaction has been investigated by a Density Functional Theory method,B3LYP,at 6-31G* basis level. There are two possible reaction channels for the whole reaction,one is concerted（path a）and the other is stepwise（path b）. The water molecule serve as a bridge to connect the proton donor to the proton acceptor. All the transition states in both paths have a six-membered ring in their structures due to the joint of the water molecule. The calculations show that the latter is preferable to the former due to the lower energy barriers. The results have verified the presumption from experiments,and proved that the joint of a water molecule can relax the strong strain in the unstable system,so it is propitious to the whole reaction.     

多孔纳米氧化铝薄膜上荧光分子光谱特性研究

通过两步电化学阳极氧化技术制备了孔径为40nm的多孔纳米阳极氧化铝材料(AAO),在AAO薄膜上分别填充了几种有机荧光分子使其形成高度有序的有机-无机复合体发光阵列,测定了此复合体的发射光谱．结果表明,AAO薄膜对有机分子具有较强的结合能力,其结合能力来源于物理和化学的协同作用．在AAO纳米薄膜上的有机荧光分子的最大发射波长均产生了明显的蓝移现象,初步探讨了此现象的机理．有机分子填充进入高度有序的AAO纳米孔阵列之中时,有机分子的聚集形式会发生改变并且也是高度有序的,同时由于极化作用使有机分子沿着纳米孔的轴向具有相对优势的分子取向,使有机分子在AAO纳米薄膜上形成了接近单分子层的高度有序的排列方式,增强了发光效率．     

大气压电离质谱在超高纯气体纯度分析中的应用

超高纯气体在工业领域有着重大的需求,必须有相应的高灵敏度杂质检测技术作为支撑。大气压电离质谱(APIMS)具有非常高的灵敏度,通常比电子轰击质谱(EIMS)高104~106倍,是分析超高纯气体纯度最有效的方法。该文介绍了APIMS的产生、发展及电离原理,并综述了以往APIMS对超高纯气体纯度分析的工作,包括底气、杂质种类、杂质检出限及特殊杂质的检测方法。由于方法灵敏度对超高纯气体纯度分析至关重要,文中侧重总结了文献中报道的不同杂质的检出限。     

原位限域生长策略制备有序介孔碳负载的超小MoO3纳米颗粒

采用原位限域生长策略制备了一系列有序介孔碳负载的超小MoO₃纳米颗粒复合物(OMC-US-MoO₃). 其中, 有序介孔碳被用作基质来原位限域MoO₃纳米晶的生长. 依此方法制备的MoO₃纳米晶具有超小的晶粒尺寸(<5 nm), 并在介孔碳骨架内具有良好的分散度. 制得的OMC-US-MoO₃复合物具有可调的比表面积(428~796 m²/g)、 孔容(0.27~0.62 cm³/g)、 MoO₃质量分数(4%~27%)和孔径(4.6~5.7 nm). 当MoO₃纳米晶的质量分数为7%时, 所得样品OMC-US-MoO₃-7具有最大的孔径、 最小的孔壁厚度和最规整的介观结构. 该样品作为催化剂时, 表现出优异的环辛烯选择性氧化性能.     

Ovalbumin-stabilized gold nanoclusters with ascorbic acid as reducing agent for detection of serum copper

Ovalbumin-stabilized gold nanoclusters(OVA@AuNCs) were prepared with ascorbic acid as a reducing agent. This strategy could realize the synthesis of water-soluble OVA@AuNCs within 20 min. The asprepared fluorescent probe showed a red fluorescence emission at 630 nm. Moreover, the properties of the OVA@AuNCs were characterized by transmission electron microscope, dynamic light scattering,ultraviolet-visible spectroscopy, fluorescent spectroscopy. Based on the surface electron density decrease-induced fluorescence quenching mechanism, the OVA@AuNCs provided high sensitivity and selectivity for sensing copper ions. A good linear relationship was obtained between the fluorescence intensity of OVA@AuNCs and the concentration of copper ions in the range of 5.0-100.0 μmol/L(R~2=0.999) with a detection limit of 640 nmol/L Furthermore, the rat serum copper contents were determined by using the OVA@AuNCs based assay, indicating great potential of fluorescent probes for application in biological and clinical analysis.     

铜锌锡硫薄膜材料及其器件应用研究进展

铜锌锡硫薄膜材料组成元素储量丰富, 环境友好, 成本低廉, 成为最具前景的薄膜材料之一. 目前, Cu₂ZnSn(S, Se)₄ (CZTSSe)薄膜太阳电池的最高转换效率已经达到12.6%. 本文总结了Cu₂ZnSnS₄ (CZTS)的发展历史, 依次介绍了CZTS薄膜材料的结构特性、光学特性、电学特性、界面特性和Na对CZTS 薄膜的影响, 详细介绍了CZTS薄膜的制备方法及器件应用的最新研究进展, 总结了目前CZTS薄膜太阳电池发展中存在的问题, 展望了今后的研究方向.