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    Fast-Slow-Scale Interaction Induced Parallel Resonance and its Suppression in Voltage Source Converters
    (New York, NY : IEEE, 2021) Ma, Rui; Qiu, Qi; Kurths, Jürgen; Zhan, Meng
    Multi-timescale interaction of power electronics devices, including voltage source converter (VSC), has made the stability and analysis of high penetrating renewable power systems very complicated. In this paper, the impedance model is used to analyze the multi-timescale characteristics and interaction of the VSC. Firstly, the multi-timescale impedance characteristics of VSC are investigated based on the Bode plots. It is found that the slow-timescale (within the DC-link voltage control scale) and fast-timescale (within the AC current control scale) models are separately consistent with the full-order model perfectly within their low- and high-frequency ranges. In addition, there exists a high impedance peak within the intermediate frequency range (roughly from 10 Hz to 100 Hz). Then, the impedance peak is theoretically estimated and explained by the slow-fast-scale impedance parallel resonance through transfer-function diagram analysis. Moreover, it is found that the impedance peak is more related to some outer controllers, such as the alternative voltage control and active power control. Specifically, larger proportional coefficients can greatly suppress the resonance peak. Finally, simulations and experiments are conducted to verify the generality of the multi-timescale characteristics and interaction of the VSC. Hence these findings are not only significant to provide a physical insight into the inner key structure of the impedance of VSC, but also expected to be helpful for controller and parameter design of the VSC.
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    Identifying Multiple Influential Users Based on the Overlapping Influence in Multiplex Networks
    (New York, NY : IEEE, 2019) Chen, Jianjun; Denk, Yue; Su, Zhen; Wang, Songxin; Gao, Chao; Li, Xianghua
    Online social networks (OSNs) are interaction platforms that can promote knowledge spreading, rumor propagation, and virus diffusion. Identifying influential users in OSNs is of great significance for accelerating the information propagation especially when information is able to travel across multiple channels. However, most previous studies are limited to a single network or select multiple influential users based on the centrality ranking result of each user, not addressing the overlapping influence (OI) among users. In practice, the collective influence of multiple users is not equal to the total sum of these users' influences. In this paper, we propose a novel OI-based method for identifying multiple influential users in multiplex social networks. We first define the effective spreading shortest path (ESSP) by utilizing the concept of spreading rate in order to denote the relative location of users. Then, the collective influence is quantified by taking the topological factor and the location distribution of users into account. The identified users based on our proposed method are central and relatively scattered with a low overlapping influence. With the Susceptible-Infected-Recovered (SIR) model, we estimate our proposed method with other benchmark algorithms. Experimental results in both synthetic and real-world networks verify that our proposed method has a better performance in terms of the spreading efficiency. © 2013 IEEE.
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    IEEE Access Special Section Editorial: Recent Advances on Hybrid Complex Networks: Analysis and Control
    (New York, NY : IEEE, 2021) Lu, Jianquan; Ho, Daniel W. C.; Huang, Tingwen; Kurths, Jurgen; Trajkovic, Ljiljana
    Complex networks typically involve multiple disciplines due to network dynamics and their statistical nature. When modeling practical networks, both impulsive effects and logical dynamics have recently attracted increasing attention. Hence, it is of interest and importance to consider hybrid complex networks with impulsive effects and logical dynamics. Relevant research is prevalent in cells, ecology, social systems, and communication engineering. In hybrid complex networks, numerous nodes are coupled through networks and their properties usually lead to complex dynamic behaviors, including discrete and continuous dynamics with finite values of time and state space. Generally, continuous and discrete sections of the systems are described by differential and difference equations, respectively. Logical networks are used to model the systems where time and state space take finite values. Although interesting results have been reported regarding hybrid complex networks, the analysis methods and relevant results could be further improved with respect to conservative impulsive delay inequalities and reproducibility of corresponding stability or synchronization criteria. Therefore, it is necessary to devise effective approaches to improve the analysis method and results dealing with hybrid complex networks.