Modern power systems are experiencing a significant increase in the penetration of power electronic devices, such as HVDC links and renewable generation units, which introduce fast switching dynamics. Voltage-dependent switching control strategies — including LCC-HVDC’s control mode selection and renewable energy’s fault ride-through (FRT) — are critical for system transient stability and security. The classical equal area criterion (EAC) and its variants, effective for synchronous-machine-dominated systems with continuous dynamics, are not directly applicable to power-electronics-penetrated systems, where switching behaviors also exacerbate transient voltage and frequency security issues. To address this gap, we generalize the classical EAC to incorporate the voltage-dependent switching dynamics of power electronics, extending it beyond rotor angle stability to transient frequency and voltage security analysis. Leveraging the timescale separation between electromechanical and power electronic dynamics, we model HVDCs and renewables via quasi-steady-state switched algebraic equations. Critical quasi-steady state analysis yields quantitative information for stability and security assessment, and the framework is extended to multi-machine systems using coherency-based model reduction. Comparative case studies on benchmark systems validate the proposed generalized EAC framework as an effective quantitative tool for transient analysis of power electronics-penetrated systems.

The frequency stability of low inertia power systems relies heavily upon the frequency support provided by new energy units, particularly wind turbines (WTs). Departing from conventional control strategies that replicate synchronous generators (SGs). the frequency trajectory optimization control offers a novel approach for frequency regulation in renewable energy systems. However, the existing frequency trajectory optimization controls lack the consideration of the overall frequency regulation capability in the system, thus posing the risk of secondary frequency drop (SFD) under extreme scenarios. Inspired by above issues, this paper proposes an adaptive frequency trajectory optimization control based on the real-time rotor speed of WTs, incorporating a smooth exit mechanism to prevent SFD. Finally, simulation results indicates that the proposed method effectively ensures the safety of WTs and prevent SFD under insufficient frequency regulation energy scenario while tracking the optimal frequency trajectory under normal operation.

Driven by the exponential growth of artificial intelligence, highly efficient, reliable, and scalable datacenters are needed for potentials in energy savings and emission reductions. High voltage DC (HVDC) datacenters offer much improved efficiency, reliability, and power density, compared to other solutions, including AC and low voltage DC (LVDC) datacenters. This paper presents a comparative study on three different HVDC datacenter designs. A 1kV HVDC datacenter infrastructure is proposed with multiple DC voltage levels for high power transfer capacity, high efficiency, scalability, and smooth transition from available low voltage DC datacenter technologies. Based on existing LVDC datacenter technologies, three different HVDC architecture designs are proposed based on DCUPS (Direct Current Uninterruptible Power Supply), Panama Power Supply, and centralized Solid State Transformer (SST), respectively. From time-domain simulation results under dynamic loading conditions, the power quality and energy efficiency of the three proposed designs are evaluated and assessed. The performance of the proposed designs is compared and potential technical improvements are indicated.

The virtual synchronous generator (VSG) has become one of the most popular grid-forming control strategies due to its virtual inertia and grid-support characteristics. However, operational mode transitions during transients, such as current limiting, complicate stability assessment and controller design. To address this issue, this paper first proposes a transient instability detection criterion for VSG integrated systems with current limiting control (CLC) based on the phase trajectory’s concave-convexity. This approach relies solely on VSG’s phase trajectory and can be proven effective under various CLC modes without dealing with the complex switching process, making it suitable for real-time stability assessment. One possible transient stability control for VSG integrated systems is proposed based on the criterion. Electromagnetic transient simulations verify the validity and accuracy of the criterion and control method.

Deploying synchronous condensers (SynCons) near grid-following renewable energy sources (GFLRs) is an effective and increasingly adopted strategy for grid support. However, the potential transient instability risks in such configurations remain an open research question. This study investigates the mechanism of dominant synchronization instability source transition upon SynCon integration and proposes a straightforward approach to enhance system stability by leveraging their interactive characteristics. Firstly, a dual-timescale decoupling model is established, partitioning the system into a fast subsystem representing phase-locked loop (PLL) dynamics and a slow subsystem characterizing SynCon rotor dynamics. The study then examines the influence of SynCons on the transient stability of nearby PLLs and their own inherent stability. The study shows that SynCon's voltage-source characteristics and its time-scale separation from PLL dynamics can significantly enhance the PLL's stability boundary and mitigate non-coherent coupling effects among multiple GFLRs. However, the dominant instability source shifts from the fast-time-scale PLL to the slow-time-scale SynCon after SynCon integration. Crucially, this paper demonstrates that the damping effect of PLL control can also be transferred from the fast to the slow time scale, allowing well-tuned PLL damping to suppress SynCon rotor acceleration. Consequently, by utilizing SynCon's inherent support capability and a simple PLL damping loop, the transient stability of the co-located system can be significantly enhanced. These conclusions are validated using a converter controller-based Hardware-in-the-Loop (CHIL) platform.

Transformers are essential assets within power systems, and their safe operation is essential for grid reliability. However, existing differential protection schemes face significant challenges in detecting minor inter-turn short-circuit faults: although the circulating current at the fault location can be extremely high, the differential current reflected at the transformer terminals may fall below protection settings, preventing timely fault clearance. This study simulates the transformers under different inter-turn fault conditions and compares the variation characteristics, and determines the operational boundary at which differential protection can reliably detect inter-turn short-circuit faults.

The dynamic nature of DC microgrids pose significant challenges for traditional modeling and fault diagnosis methods. To address this issue, this paper proposes an online adjustable modeling and fault reconstruction scheme for DC microgrids featuring dynamic topology and time-varying control strategy. This method divides the system state-space model variables into voltages and currents and introduces enhanced adjacency matrices to generate an adjustable model. On this basis, a fault reconstruction scheme based on sliding mode observer is constructed, which is adaptable to the model change. Simulations on a three-terminal ring DC microgrid demonstrate that the proposed method achieves enhanced accuracy, reduced latency and computational cost compared with existing methods, and appears good adaptability to parameter perturbation and measurement noise. (c) 2017 Elsevier Inc. All rights reserved.

In scenarios where synchronous generators (SGs) and grid-following renewable energy sources (GFLR) are co-located, existing research, which mainly focuses on the first-swing stability of SGs, often overlooks ongoing dynamic interactions between GFLRs and SGs throughout the entire rotor swing period. To address this gap, this study first reveals that the angle oscillations of SG can cause periodic grid voltage fluctuations, potentially triggering low-voltage ride-through (LVRT) control switching of GFLR repeatedly. Then, the periodic energy changes of SGs under “circular” and “rectangular” LVRT limits are analyzed. The results indicate that circular limits are detrimental to SG's first-swing stability, while rectangular limits and their slow recovery strategies can lead to SG's multi-swing instability. Conservative stability criteria are also proposed for these phenomena. Furthermore, an additional controller based on feedback linearization is introduced to enhance the entire period transient stability of SG by adjusting the post-fault GFLR output current. Finally, the efficacy of the analysis is validated through electromagnetic transient simulations and controller hardware-in-the-loop (CHIL) tests.

Timely and accurate detection of series arc faults in multiterminal dc microgrids is a challenging task. Existing series arc fault detection methods suffer from different deficiencies in terms of selectivity, applicability, and efficiency. To solve these problems, this article introduces a model-based series arc fault detection scheme for dc microgrids. First, a minimized system model dedicated to series arc fault detection is derived. On this basis, a bank of reduced-order unknown input observers are established. Through recognizing predefined patterns in the output of the observer bank, various series arc faults can be detected and isolated in a timely manner. The proposed method is advantageous in that it can simultaneously locate multiple series arc faults in complex dc microgrids without relying on auxiliary power hardware, special measurement devices, prior fault data, and avoid cumbersome threshold settings. The performance of the proposed method has been verified through numerical simulations with MATLAB/Simulink and experimental tests.

The three-phase AC-DC voltage source converter (VSC) is one of the most popular converters for connecting DC microgrids and utility grids. The stability of the DC microgrid is an important prerequisite for ensuring its safe operation. Thus, based on passivity theory, this paper investigates the DC-side output impedance of VSCs adopting three droop control strategies. Firstly, the small-signal model and equivalent circuit of VSCs with three droop controls are established. Secondly, the passivity theory and its impacts on stability are introduced. Next, the derived impedance models are validated via frequency-sweep simulations in MATLAB/Simulink/SPS. Then, based on passivity theory, with different parameters including hardware parameters and software parameters, the output impedance characteristics of the VSC under the three droop controls are analyzed and compared. Finally, practical recommendations for selecting an appropriate droop control strategy are provided.

This paper explores the transient stability of power synchronization loop (PSL) - based grid forming converters (GFMCs), under the influence of nearby phase-locked loop (PLL) -based grid following converters (GFLCs). First, the GFMC trajectories affected by GFLC transient dynamics are analyzed. The findings reveal that GFMC may accelerate or decelerate during faults, both present potential risks of failing to switch from current limiting control (CLC) to constant voltage control (CVC) mode after fault clearance. To ensure GFMC can return to the equilibrium point under CVC, a decoupling control strategy is proposed. By adjusting the controllable current angles of both GFMCs and GFLCs from a "fixed mode" to a "tracking mode," this strategy simultaneously enhances GFLC stability and ensures the global stability of GFMCs under CVC. Theoretical analysis and control effectiveness are validated through electromagnetic simulations.

Integrating grid-forming converters (GFMCs) into grid-following converter (GFLC)-dominated power systems enhances the grid strength, but GFMCs' current-limiting characteristic triggers dynamic switching between constant voltage control (CVC) and current limit control (CLC). This switching feature poses critical transient stability risks to GFLCs, requiring urgent investigation. This paper first develops a mathematical model for this switched system. Then, it derives switching conditions for droop-controlled GFMCs, which are separately GFMC angle-dependent and GFLC angle-dependent. On this basis, the stability boundaries of GFLC within each subsystem are analyzed, and the impact of GFMC switching arising from GFLC angle oscillation is investigated. The findings reveal that the switched system's stability boundary coincides with that of the CLC subsystem. To enhance GFLC's transient stability and ensure GFMC converges to the CVC mode, this paper introduces a virtual fixed d-axis control (VFDC) strategy. Compared with existing methods, this method achieves decoupling and self-stabilization using only local state variables from individual converters. The conclusions are validated through simulations and Controller Hardware-in-the-Loop tests.

The optimal-frequency-trajectory-oriented frequency support methods provide a system view for the wind turbines (WI's) frequency regulation. However, the power deficit information is required for the implementation of this frequency regulation strategy. The signal delay caused by the power deficit estimation and transmission will threaten the effectiveness of its implementation. To eliminate the influence of inevitable signal delay, this paper designs a zero power deficit preset strate*,. By presetting power deficit parameter as 0 during the initial stage of disturbance, the proposed method successfully eliminates the system frequency overfall risk caused by lack of the necessary system power deficit information. Finally, simulation results in a modified IEEE 39-bus system verify the performance of the proposed method on delivering preemptive grid frequency support provided by the controllable wind turbine generator systems.

The fault calculation method has not yet been generalized for the transmission system of large-scale new energy resource integration due to the multivariable coupling and nonlinear characteristics present during faults. To address this issue, this paper proposes a fault calculation method specifically designed for large-scale photovoltaic (PV) integrated transmission systems. Firstly, the coupling relationship between the control loop of inverter-based resources (IBRs) and their currents is analyzed, leading to the establishment of an equivalent model of the controlled current source of the IBR. Subsequently, the positive sequence equivalent principle for the large-scale PV transmission system is customized based on the symmetrical component method and is integrated with the composite sequence network under various fault conditions. More importantly, a time-/phasor-domain alternating calculation method is developed, which effectively addresses the nonlinear control loops while simultaneously reducing the complexity of fault calculations in multi-IBR systems. Finally, a comparison between simulation and calculation results demonstrates that the proposed method can effectively and accurately calculate various asymmetric faults in multi-IBR systems.

As renewable energy sources increasingly penetrate power systems, ensuring operational stability during grid faults poses a significant challenge. Conventional fault-ride-through (FRT) control strategies often lack systematic parameter optimization, resulting in limited support for transient rotor angle stability and inadequate suppression of transient overvoltages. This paper introduces a comprehensive optimization framework to address these shortcomings. We first develop a novel quasi-steady-state model that accurately captures critical states governing transient stability and voltage security. Variational analysis at these states yields gradient information to guide stability enhancement. Leveraging this insight, we propose a gradient-informed optimization approach to tune FRT parameters, simultaneously improving transient rotor angle stability and mitigating overvoltages. The effectiveness of the proposed model and method is demonstrated through simulations on a benchmark renewable-integrated power system.

High-altitude electromagnetic pulse (HEMP), generated by high-altitude nuclear explosions, is characterized by high amplitude and broad coverage. Its El component can cause extensive damage to power equipment and lead to system failures. As the intelligentization of power plant equipment continues to advance, the threat posed by HEMP is becoming increasingly severe. Therefore, it is necessary to investigate the effects of the El component on equipment. To address the high computational demands and long simulation time required for coupling simulation of the El component of HEMP, this study first supplements the dataset and then employs an artificial intelligence-based regression algorithm to predict the peak core voltage under arbitrary incident angle , azimuth angle psi, and polarization angle alpha. Subsequently, a generalized extreme value (GEV) distribution is used to fit the damage threshold data of secondary equipment obtained from injection experiments. By integrating coupling analysis, regression prediction, and extreme value distribution, this research establishes a damage probability curve for secondary equipment, enabling the condition discrimination of intelligent relay protection devices. The study provides a reference for electromagnetic protection in power plants and enhances their operational reliability.

DC fault location technology is crucial for estimating the fault location and developing multi-terminal direct current (MTDC) systems. This article presents a novel fault location method using the parameter fitting approach. The propagation of traveling waves (TWs) in the decoupled line-mode fault network is first discussed, resulting in analytical expressions for the backward line-mode current TWs containing fault location information. Then, the adaptive multi-step Levenberg–Marquardt (AMLM) algorithm is applied for parameter fitting owing to its fast processing speed and precision. The exact fault location is estimated using the fitted coefficient. Different testing MTDC systems modeled in PSCAD/EMTDC and a real-time digital simulator (RTDS) validate the proposed fault location method. Based on numerous simulation tests, the AMLM-based parameter fitting and the proposed method are accurate, with errors smaller than 0.5%. Compared to the existing methods, the proposed method has desired performance under close-in faults, can withstand 35 dB noise interference, and obviates the need for an extremely high sampling frequency, estimation of tws velocity, and communication devices.

Compared to AC power distribution systems, DC power distribution systems offer higher power supply reliability, easier integration of renewable energy sources (RESs) and energy storage devices, and fewer power conversion stages. As a result, they are expected to be widely adopted in industrial power distribution systems, data centers, residential buildings, and other fields in the future. This paper conducts a simulation of a single-bus DC industrial power distribution system (IPDS) comprising a grid-connected inverter, a photovoltaic (PV) system, a battery energy storage system (BESS), resistive loads, constant power loads (CPLs), and a three-phase induction motor (IM). Firstly, the topology of the IPDS is proposed. Secondly, the control strategies of each converter in the system and the hierarchical control architecture of the IPDS are presented. Thirdly, multiple operating scenarios including the IM's power energy feedback of the IPDS are simulated based on the real-time simulation equipment Typhoon HIL404 and its software THCC. Finally, the analysis and discussion of the simulation results are conducted.

This study addresses the optimization of urban integrated energy systems (UIESs) under uncertainty in peer-to-peer (P2P) electricity trading by introducing a two-stage robust optimization strategy. The strategy includes a UIES model with a photovoltaic (PV)–green roof, hydrogen storage, and cascading cold/heat energy subsystems. The first stage optimizes energy trading volume to maximize social welfare, while the second stage maximizes operational profit, considering uncertainties in PV generation and power prices. The Nested Column and Constraint Generation (NC&CG) algorithm enhances privacy and solution precision. Case studies with three UIESs show that the model improves economic performance, energy efficiency, and sustainability, increasing profits by 1.5% over non-P2P scenarios. Adjusting the robustness and deviation factors significantly impacts P2P transaction volumes and profits, allowing system operators to optimize profits and make risk-aligned decisions.