As the penetration of power electronic converters and renewable generation increases, voltage and current waveforms in power systems are increasingly distorted and nonstationary. Accurate estimation and fast tracking of electric power quantities are essential for energy metering and billing, online monitoring, and safe operation of power systems. However, most existing estimation methods assume that the waveform within an observation window is stationary and periodic, which often leads to a slow dynamic response under nonstationary conditions and introduces estimation errors when the fundamental frequency deviates from its nominal value. To address these challenges, this paper introduces a framework termed operating point fluctuations (OPF). In the OPF framework, a nonstationary waveform is reinterpreted by treating the time-varying fundamental component as a dynamic operating point and describing all distortions as fluctuations around it. Based on this framework, a set of single-phase and three-phase power quantity expressions is derived. Furthermore, an estimation method is proposed. Comprehensive simulation studies demonstrate that the proposed method achieves high accuracy under stationary conditions, fast dynamic tracking under nonstationary conditions, low computational burden, and robustness to noise and fundamental frequency deviation. Validation using field measurement data further confirms these results and demonstrates its suitability for practical applications.
Fast and accurate fault identification is crucial for the safe and stable operation of multi-terminal flexible DC grids. Existing protection methods for flexible DC grids are sensitive to transition resistances, with limited engineering adaptability, making it difficult to balance speed and reliability. To address this issue, this paper proposes a single-ended protection method based on the voltage energy spectrum matrix of the current-limiting reactor. This method uses the difference of high-frequency components of voltage on both sides of the current-limiting reactor at the initial stage of fault, with the energy spectrum matrix similarity as the triggering criterion. Combined with the damping effect of the reactor, a fault criterion based on the high-frequency and low-frequency energy ratio is developed for both internal and external faults. The paper first analyses the voltage transient evolution of internal and external faults under the damping effect of the current-limiting reactor. It then studies the time-frequency characteristics of voltage signals under different operating conditions and, based on this, constructs a complete protection scheme. Finally, a multi-terminal flexible DC system model is built in PSCAD/EMTDC for simulation verification. The results show that high-frequency energy quickly concentrates at the early fault stage. The spectrum matrix is rapidly reconstructed, and the similarity between the two sides drops by more than 20%, which enables protecting fast starting. The high-frequency energy ratio shows a clear difference between internal and external faults (more than 49%). The method can complete fault identification within 3 ms after fault inception. It remains reliable under a 300 Omega transition resistance and 30 dB noise. In addition, it is not sensitive to changes in the reactor inductance and can also effectively identify lightning disturbances. Therefore, it is suitable for fast and high-reliability protection of long-distance multi-terminal flexible DC grids.
Tower spotting design in transmission line planning is a critical component, as it directly affects both project cost and safety. Conventional design approaches often inadequately account for terrain characteristics and global optimisation requirements, resulting in low efficiency or limited applicability in large-scale projects. This paper proposes a practical optimisation strategy for transmission line tower spotting that jointly considers multiple safety constraints and terrain features to achieve coordinated designs of tower locations and heights. First, an optimisation model is developed to minimise total construction costs, incorporating constraints such as horizontal span, vertical span, and ground clearance. Next, a terrain-driven optimisation method is developed, which utilises topographic peak points from the terrain profile as initial candidate locations for tower spotting, thereby substantially reducing computational complexity. The approach employs the Simulated Annealing Particle Swarm Optimisation (SA-PSO) algorithm to achieve global height optimisation. Finally, the proposed method is validated using a case study of 500 kV transmission line planning in Guangdong Province, demonstrating enhanced economic efficiency while fully complying with all safety requirements.
Stochastic unit commitment with AC network constraints is intractable for realistic systems. We benchmark machine learning surrogates for AC feasibility classification-Kolmogorov-Arnold networks (KANs), multilayer perceptrons (MLPs), gradient-boosted trees and support vector machines (SVMs)-on three power systems (118-2848 buses) under two feature tracks: pre-solve (load multipliers, renewable factors and contingency identity) and dispatch-aware (adding generator setpoints). KAN, MLP and tree-based models all achieve area under the ROC curve (AUROC) above 0.99 on the pre-solve track. On the dispatch-aware track, gradient-boosted trees lead with AUROC 0.997, while KAN with weight decay reaches AUROC 0.992, a residual gap of approximately 0.005. Violation-type error decomposition identifies which constraint categories drive false-feasible predictions. Split-conformal prediction with group-conditional calibration provides distribution-free coverage guarantees and flags uncertain points for full power flow verification. Speedups of three to five orders of magnitude over Newton-Raphson enable real-time screening.
The growing penetration of renewables and prosumagers in the 2030s will require deeper monitoring and control in medium- and low-voltage grids. Wireless technologies, particularly 5G, offer possibilities for cost-effective, flexible, and scalable connectivity in grid automation. Power system communication is highly heterogeneous, involving diverse traffic types with varying latency and reliability requirements. Prior research on 5G technology enablers, such as carrier aggregation, dual connectivity, and network slicing (NS), has focused on other verticals and relied mainly on simulations, leaving a gap in experimental validation for grid protection and automation under realistic conditions. This paper maps 5G technology enablers to IEC 61850 traffic types and evaluates their performance in commercial 5G networks for line differential protection and virtualised fault passage indication. Results show that NS improves reliability compared to traffic prioritisation, but does not yet meet ultra-low latency requirements for line differential protection. Minimum latency for mission-critical protection traffic reaches approximately 11 ms, and round-trip times are 32% lower than prior works. These findings provide the first end-to-end empirical evidence of 5G technology enabler deployment for smart grid applications and offer practical guidance for future implementations.
