86 research outputs found

    Power System Stability With a High Penetration of Inverter-Based Resources

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    Inverter-based resources (IBRs) possess dynamics that are significantly different from those of synchronous-generator-based sources and as IBR penetrations grow the dynamics of power systems are changing. This article discusses the characteristics of the new dynamics and examines how they can be accommodated into the long-standing categorizations of power system stability in terms of angle, frequency, and voltage stability. It is argued that inverters are causing the frequency range over which angle, frequency, and voltage dynamics act to extend such that the previously partitioned categories are now coupled and further coupled to new electromagnetic modes. While grid-forming (GFM) inverters share many characteristics with generators, grid-following (GFL) inverters are different. This is explored in terms of similarities and differences in synchronization, inertia, and voltage control. The concept of duality is used to unify the synchronization principles of GFM and GFL inverters and, thus, established the generalized angle dynamics. This enables the analytical study of GFM-GFL interaction, which is particularly important to guide the placement of GFM apparatuses and is even more important if GFM inverters are allowed to fall back to the GFL mode during faults to avoid oversizing to support short-term overload. Both GFL and GFM inverters contribute to voltage strength but with marked differences, which implies new features of voltage stability. Several directions for further research are identified, including: 1) extensions of nonlinear stability analysis to accommodate new inverter behaviors with cross-coupled time frames; 2) establishment of spatial–temporal indices of system strength and stability margin to guide the provision of new stability services; and 3) data-driven approaches to combat increased system complexity and confidentiality of inverter models

    Advertising Effectiveness of Different Social Appeals through Microblog

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    In today’s interactive marketplace,microblog has become a powerful social marketing and advertising platform. An important type of information in microblog is consumer generated and forwarded advertising. In our study, we explore advertising effects of different social appeals through microblog. We find that oriented appeals (i.e., other-oriented and self-oriented appeals) are more effective than non-oriented appeals. But the difference between other-oriented appeal and self-oriented appeal is insignificant. The relationship between sender and receiver moderate the result. Other-oriented appeal is more effective than self-oriented appeal for dyads with offline relationship, while self-oriented appeal is more effective for dyads of online-only relationship

    Mapping of Dynamics between Mechanical and Electrical Ports in SG-IBR Composite Grids

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    Participation Analysis in Impedance Models: The Grey-Box Approach for Power System Stability

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    The Impact of Frame Transformations on Power System EMT Simulation

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    Shapley Q-value: A Local Reward Approach to Solve Global Reward Games

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    Cooperative game is a critical research area in the multi-agent reinforcement learning (MARL). Global reward game is a subclass of cooperative games, where all agents aim to maximize the global reward. Credit assignment is an important problem studied in the global reward game. Most of previous works stood by the view of non-cooperative-game theoretical framework with the shared reward approach, i.e., each agent being assigned a shared global reward directly. This, however, may give each agent an inaccurate reward on its contribution to the group, which could cause inefficient learning. To deal with this problem, we i) introduce a cooperative-game theoretical framework called extended convex game (ECG) that is a superset of global reward game, and ii) propose a local reward approach called Shapley Q-value. Shapley Q-value is able to distribute the global reward, reflecting each agent's own contribution in contrast to the shared reward approach. Moreover, we derive an MARL algorithm called Shapley Q-value deep deterministic policy gradient (SQDDPG), using Shapley Q-value as the critic for each agent. We evaluate SQDDPG on Cooperative Navigation, Prey-and-Predator and Traffic Junction, compared with the state-of-the-art algorithms, e.g., MADDPG, COMA, Independent DDPG and Independent A2C. In the experiments, SQDDPG shows a significant improvement on the convergence rate. Finally, we plot Shapley Q-value and validate the property of fair credit assignment
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