A two-layer optimisation management method for the microgrid with electric vehicles

The file attached to this record is the author's final peer reviewed version.The energy management of the microgrid (MG) with electric vehicles (EVs) is a large-scale optimization problem where the goal should take into account the performance and economic benefits of the power system while meeting the travel needs of EVs. Due to the development of vehicle to grid (V2G) technologies and demand response (DR), the relationship between EVs and MG becomes currently closer, which leads to a more complex situation. Therefore, the relationship of interest between MG and EVs has to be clarified to improve the performance of MG and EVs to achieve a win-win situation. This paper proposes a two-tier energy management strategy that considers the benefits for both MG and EVs. The first layer ensures the performance of the MG, while the second layer reduces the charging cost from the perspective of the car owners. In addition, based on the existence of uncertain parameters, mixed type variables and nonlinear constraints in the optimization problem, the differential evolution, stochastic search and greedy algorithm are used to analyze and find the optimal solution. Simulation results verify the effectiveness of the proposed strategy and solutions, which benefit both the MG and EV owners

Particle swarm optimisation for scheduling electric vehicles with microgrids

The file attached to this record is the author's final peer reviewed version.The explosion in the number of electric vehicles (EVs) has had a significant impact on the energy systems and structures of cities. Large-scale EVs inevitably increase the load on the grid, while uncoordinated vehicle to Grid (V2G) technologies pose challenges to the stability and security of the grid. This paper introduces a global intelligent method to find optimal cooperation charging/discharging strategies for EVs to minimize the operation cost. EVs aggregates co-ordinate the energy information and needs of all EVs and use real-time pricing based on micro-grid loads to influence EV charge-discharge behavior. Particle swarm optimization (PSO) is introduced to solve the EV scheduling problem. This study also discusses the negative impact on the energy system of different strategies for charging EVs. Simulation shows that this smart charging strategy and improved PSO can effectively decrease the operation cost of EVs and reduce the load for each micro-grid

Study on a class of Schrödinger elliptic system involving a nonlinear operator

This paper considers a class of Schrödinger elliptic system involving a nonlinear operator. Firstly, under the simple condition on and ', we prove the existence of the entire positive bounded radial solutions. Secondly, by using the iterative technique and the method of contradiction, we prove the existence and nonexistence of the entire positive blow-up radial solutions. Our results extend the previous existence and nonexistence results for both the single equation and systems. In the end, we give two examples to illustrate our results

Spin transport in ferromagnet-InSb nanowire quantum devices

Signatures of Majorana zero modes (MZMs), which are the building blocks for fault-tolerant topological quantum computing, have been observed in semiconductor nanowires (NW) with strong spin-orbital-interaction (SOI), such as InSb and InAs NWs with proximity-induced superconductivity. Realizing topological superconductivity and MZMs in this most widely-studied platform also requires eliminating spin degeneracy, which is realized by applying a magnetic field to induce a helical gap. However, the applied field can adversely impact the induced superconducting state in the NWs and also places geometric restrictions on the device, which can affect scaling of future MZM-based quantum registers. These challenges could be circumvented by integrating magnetic elements with the NWs. With this motivation, in this work we report the first experimental investigation of spin transport across InSb NWs, which are enabled by devices with ferromagnetic (FM) contacts. We observe signatures of spin polarization and spin-dependent transport in the quasi-one-dimensional ballistic regime. Moreover, we show that electrostatic gating tunes the observed magnetic signal and also reveals a transport regime where the device acts as a spin filter. These results open an avenue towards developing MZM devices in which spin degeneracy is lifted locally, without the need of an applied magnetic field. They also provide a path for realizing spin-based devices that leverage spin-orbital states in quantum wires.Comment: 30 pages, 12 figure

Study on response characteristics of rotor-bearing system under sudden base excitation load

In this paper, the rotor system with nonlinear bearing force and base excitation load was modeled based on finite element method, and its response characteristic under the excitation of base load was studied. The results show that the response of the rotor is the superposition of the basic impulse response and the unbalanced response. The pulse excitation energy can be dispersed while the rotation speed and pulse frequency are close to each other. When the phase difference of unbalanced excitation is 180°, the response amplitude of rotor bearing system was the smallest. The correctness of the rotor bearing system model was verified by experiments

Villain Stardom in Socialist China: Chen Qiang and the Cultural Politics of Affect

Despite playing various kinds of roles across genres from 1949 to 1965, Chen Qiang acquired stardom mainly due to his remarkable screen performance as villainous landlords in socialist China. His villain stardom is an aberrant case, compared to the majority of film stars in Chinese socialist cinema who encouraged identification and emulation and helped propagate socialist ideology to reform Chinese citizens. Paying special attention to socio-historically specific film exhibition practices and the actor's own reflections on his villain performance, this article argues that Chen's stardom functioned as an important affective technology within a wider and complex Communist propaganda enterprise in that it helped cultivate class hatred necessary for the Communist revolution and socialist land reform campaigns. Through this case study, the article suggests that close engagement with both cultural–historical specificities of cinema and recent critical theories of affect open up a space for researching the diversified star phenomena in contemporary China

The Existence of Radial Solutions to the Schrödinger System Containing a Nonlinear Operator

In this paper, we investigate a class of nonlinear Schrödinger systems containing a nonlinear operator under Osgood-type conditions. By employing the iterative technique, the existence conditions for entire positive radial solutions of the above problem are given under the cases where components μ and ν are bounded, μ and ν are blow-up, and one of the components is bounded, while the other is blow-up. Finally, we present two examples to verify our results

An Improved Perceptual Hash Algorithm Based on U-Net for the Authentication of High-Resolution Remote Sensing Image

Data security technology is of great significance for the effective use of high-resolution remote sensing (HRRS) images in GIS field. Integrity authentication technology is an important technology to ensure the security of HRRS images. Traditional authentication technologies perform binary level authentication of the data and cannot meet the authentication requirements for HRRS images, while perceptual hashing can achieve perceptual content-based authentication. Compared with traditional algorithms, the existing edge-feature-based perceptual hash algorithms have already achieved high tampering authentication accuracy for the authentication of HRRS images. However, because of the traditional feature extraction methods they adopt, they lack autonomous learning ability, and their robustness still exists and needs to be improved. In this paper, we propose an improved perceptual hash scheme based on deep learning (DL) for the authentication of HRRS images. The proposed method consists of a modified U-net model to extract robust feature and a principal component analysis (PCA)-based encoder to generate perceptual hash values for HRRS images. In the training stage, a training sample generation method combining artificial processing and Canny operator is proposed to generate robust edge features samples. Moreover, to improve the performance of the network, exponential linear unit (ELU) and batch normalization (BN) are applied to extract more robust and accurate edge feature. The experiments have shown that the proposed algorithm has almost 100% robustness to format conversion between TIFF and BMP, LSB watermark embedding and lossless compression. Compared with the existing algorithms, the robustness of the proposed algorithm to lossy compression has been improved, with an average increase of 10%. What is more, the algorithm has good sensitivity to detect local subtle tampering to meet the high-accuracy requirements of authentication for HRRS images