An interconnection and damping assignment passivity-based (IDA-PB) control design is proposed to improve the dynamic performance of voltage source converter high-voltage direct current (VSC-HVDC) system. The port-controlled Hamiltonian with dissipation (PCHD) model for voltage source converter (VSC) is developed according to the PCHD equation, and the strict passivity of the PCHD model is proved. On the basis of the PCHD model, a desired energy function is constructed by assigning interconnection and damping matrix and used as Lyapunov function. Then the IDA-PB control is designed according to desired equilibrium point, state variables, and IDA-PB control principle. By using this type of controller, the influence of the equivalent resistance of the VSC direct current side on the VSC-HVDC system is eliminated. The effectiveness of the proposed IDA-PB control is demonstrated through simulation studies on a two-terminal VSC-HVDC system by PSCAD/EMTDC software. The simulation results show that the controller has significant contribution to improve the dynamic behavior of the VSC-HVDC system under a variety of operation conditions. Copyright © 2014 John Wiley & Sons, Ltd.

Continuous monitoring of the minimum safety distance between construction machinery and energized bodies is essential during operations near energized equipment in substations. Existing methods mostly rely on fixed-view observation, online LiDAR, or rigid camera–LiDAR installation, leading to inflexible deployment, high extrinsic-maintenance cost, and insufficient metric consistency across viewpoints. To address these limitations, this paper proposes a safety-distance monitoring method based on cross-modal self-registration between monocular images and a pre-built LiDAR map. During online operation, only the current monocular image is used. Monocular depth estimation first generates a pseudo-point cloud, which is then registered with historical LiDAR point clouds to solve the camera pose and align the current observation with the map. Combined with target-boundary segmentation and prior energized-hazardous-region information, the method localizes key parts of construction machinery in 3D and computes the minimum safety distance to energized regions. Experiments show that the proposed method achieves a registration recall of 92.2%, a mean absolute error of 0.748 m, a maximum error of 0.822 m, and a single-frame latency of 180 ms. Notably, these results are achieved without real-time LiDAR input or on-site extrinsic recalibration. These results demonstrate the feasibility of the proposed framework in a representative substation scenario and indicate its potential for auxiliary online safety-distance monitoring.