Multiterminal high-voltage direct-current (MTDC) systems based on voltage-source converters (VSCs) are used for the transmission of large-scale renewable energy generations. Dynamic interactions among different VSCs through the coupling of DC and AC networks become one salient problem in an MTDC system. Self- and en-stabilizing coefficients, which are expressed analytically in the frequency domain with clear math and physical meanings, are defined to quantitatively describe and analyze the interactions of an MTDC system in this article. Some insights behind such interactions are concomitantly revealed by the analytic quantification. In this course, it not only points to the devices and interaction paths causing the oscillations but also illustrates how controller parameters affect the system stability by analytic expressions. This method provides an analytical way to quantify the interactions among VSCs in DC voltage control timescale, henceforth leaving a deeper understanding of the dynamics in an MTDC system.

Point cloud registration is a crucial preprocessing step for point cloud data analysis and applications. Nowadays, many deep-learning-based methods have been proposed to improve the registration quality. These methods always use the sum of two cross-entropy as a loss function to train the model, which may lead to mismatching in overlapping regions. In this paper, we designed a new loss function based on the cross-entropy and applied it to the ROPNet point cloud registration model. Meanwhile, we improved the ROPNet by adding the channel attention mechanism to make the network focus on both global and local important information, thus improving the registration performance and reducing the point cloud registration error. We tested our method on ModelNet40 dataset, and the experimental results demonstrate the effectiveness of our proposed method.

Grid-forming wind turbines (GFM-WTs) based on virtual synchronous control can support the voltage and frequency of power system by emulating the synchronous generator. The dynamic characteristics of a GFM-WT decided by virtual synchronous control, dq-axis voltage, and current control is significant for small-signal stability analysis. This paper builds a small-signal model of a GFM-WT in active power control (APC) and DC voltage control (DVC) timescale from the perspective of internal voltage. The proposed model describes how the magnitude and phase of the internal voltage are excited by the unbalanced active and reactive power when small disturbances occur. Interactions in different control loops can be identified by the reduced order model. We verify the accuracy of the proposed model in APC and DVC timescales by time domain simulations based on MATLAB/Simulink. Case studies show how the control parameters interact with each other in the two timescales.

Stability analysis of multi-terminal HVDC systems is an important and challenging issue for the safety and stable operation of power systems with large-scale renewable energy generations. It is quite difficult to analyze the system stability caused by the interactions among different VSCs with the coupling of DC and AC networks. This paper aims to present a method to analyze the relative stability of different interactions in multi-terminal HVDC systems. By the $\nu$ -gap metric based robust stability theory, firstly we propose a stability index to quantify the stability margin with respect to different paths of interactions. The influence of the interactions among different VSCs on the stability margin can be analyzed quantitatively. Then we present a method to easily calculate the stable region of parameters in the interactions. Extensive examples are given to demonstrate the application and the effectiveness of the proposed method. Note to Practitioners —This paper is motivated by the problem of improving the small-signal stability of multi-terminal high voltage direct current (MTDC) systems, which are widely used to transmit large-scale renewable energy generations. In recent years, many small-signal instability accidents have occurred in actual HVDC projects. The dynamic behavior of MTDC systems is related to the complex interactions among different voltage source converters (VSCs) through the coupling of AC and DC networks. Therefore, we aim to explain the mechanism of oscillations caused by the interactions and the relation between the dynamics and the control parameters. In this paper, we employ the $\nu$ -gap metric based robust control theory to quantify the stability of an MTDC system with respect to different interactions and to calculate the stable region of a particular parameter in the interactions. The results in this paper can explain the influence of the interactions among different VSCs on the stability margin quantitatively. Moreover, the results provide new ideas for the setting and tuning of control parameters in MTDC systems and even in other multi-equipment power systems.