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. 相似文献
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.
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. 相似文献
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. 相似文献
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. 相似文献