Zhiguo Hao

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.

Integrating grid-forming converters (GFMCs) into grid-following converter (GFLC)-dominated power systems enhances the grid strength, but GFMCs' current-limiting characteristic triggers dynamic mode 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 mode 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 mode 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.

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.

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.

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.

Medium-voltage DC shipboard power systems exert tough challenges to existing protection techniques. To detect and isolate component faults in medium-voltage DC shipboard power systems, this paper develops a decentralized model-based method. In the proposed method, a protected medium-voltage DC shipboard power system is partitioned into protection zones composed of power electronic converters and DC cables. For each protection zone, a bank of linear parameter varying-unknown input observers is established to achieve the simultaneous detection and isolation of multiple local component faults. The proposed method solves the major limitations of model-based fault diagnosis methods in terms of computational complexity and susceptibility to flexible system topology. In the verification tests with MATLAB/Simulink and laboratory hardware, the proposed method is effective in recognizing switch failures, short-circuits in DC-link capacitors, shunt and series faults in DC cables. Moreover, it exhibits good robustness against non-fault disturbances, measurement noises and modeling errors.

In traditional views, the build-up of accelerating energy during faults can cause the well-known first-swing angle instability in synchronous generators (SGs). Interestingly, this letter presents a new insight that the accumulation of decelerating energy due to the low voltage ride-through (LVRT) and recovery control of grid-following inverter-based resources (GFL-IBRs), might also result in transient angle instability in SGs. The transient energy accumulated during angle-decreasing swing transforms into the acceleration energy of the subsequent swing, hence such phenomena often manifest as multi-swing instability. Both theoretical analysis and simulation support these findings.

The fast frequency support (FFS) towards frequency trajectory optimization provides a system view for the frequency regulation of wind farms (WFs). However, the existing frequency trajectory optimization-based FFS generally relies on the accurate governor dynamics model of synchronous generators (SGs), which aggrandizes the difficulty of controller implementation. In this paper, a proportional-integral (PI) based FFS of WFs is designed for tracking the optimal frequency trajectory, which gets rid of the dependence on the governor model. Firstly, the prototypical PI-based FFS of WFs is proposed and its feasibility for tracking the optimal frequency trajectory is analyzed and demonstrated. Then, based on the “frequency-RoCoF” form of the optimal frequency trajectory, a more practical PI controller is constructed, avoiding the time dependence of the prototypical PI controller. Besides, an adaptive gain associated with PI parameters is designed for multi-WF coordination. Finally, the validity of the proposed method is verified in both the single-WF system and the multi-WF system.

Considerable efforts have been made to address the resonance issue of the Direct-drive Permanent Magnet Synchronous Generator (D-PMSG) wind farm integrated power systems. However, the D-PMSG controller structure and parameters are concealed because of commercial secrecy, thus the target system exhibits grey-box characteristics. The existing resonance damping methods are either unavailable for grey-box systems or economically infeasible, which makes resonance damping of grey-box systems extremely challenging. To address this issue, this paper proposes an Additional Resonance Damping Control (ARDC) specifically for the grey-box D-PMSG system. This strategy is achieved by incorporating an additional control loop outside the D-PMSG controller. Firstly, the external impedance characteristics are obtained by the frequency sweeping technique offline and then the key parameter of the additional control loop is determined by the Bode-diagram-based method under the worst stability scenario. Once the resonance occurs, the external impedance of the black-box D-PMSG is reshaped online to increase the magnitude stability margin of the system, thus providing effective resonance damping. The ARDC's effectiveness is finally verified in the simulation and controller-hardware-in-the-loop experiment under various operating conditions.