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• A reduced-order model for assessing the transient DC-link voltage oscillation stability of VSC-HVDC systems is proposed. • Lyapunov direct method is applied to assess the transient DC-link voltage oscillation stability of VSC-HVDC systems. • The conservative stabilizing conditions based on two kinds of Lyapunov functions are derived. • Limit cycle of the converter-tied DC system is found and the asymptotic stability boundary is mapped based on limit cycle theory. • The system stability can be improved by tuning the system parameters. Lyapunov direct method is utilized in this paper to reveal the transient voltage oscillation stability mechanism for VSC-HVDC systems. Firstly, a reduced analytical nonlinear model for transient voltage oscillation stability assessment is proposed, which is a Liénard system. Based on the proposed model, a novel Lyapunov function is constructed and the conservative stability boundary is depicted, which reveals that the transient voltage oscillation can be well damped when the operating points are within the domain of asymptotic stability. In addition, it is found that there exists one limit cycle for VSC-HVDC systems. Once any system operation point exceeds the limit cycle, the divergent oscillations are triggered, and the aperiodic instability will eventually appear if the perturbations failed to be cleared in time. Finally, according to the limit cycle theory, one sufficient instability condition is derived and the transient voltage instability risk of the VSC-HVDC systems can be well evaluated. [ABSTRACT FROM AUTHOR]

• The analytical expressions of fault traveling waves are derived for MMC-HVDC grids. • The curvatures of fault traveling waves are proposed as the protection criterion. • The protection method based on curvatures has good sensitivity to fault resistance. • A protection platform has been developed and tested with RTDS platform. The existing protection techniques for high-voltage direct-current (HVDC) grids suffer from several shortcomings such as high sampling frequency, poor robustness, and reliance on simulation for threshold setting. To solve these problems, this paper proposes a non-unit protection method for modular multilevel converter (MMC)-based HVDC grids using the curvatures of backward traveling waves. To this end, the propagation characteristics of traveling waves and the boundary characteristics of DC lines are first studied, then the analytical expressions of backward traveling waves are derived. Moreover, the curvatures of backward traveling waves are analyzed. On this basis, a non-unit protection method is proposed, including zone selection, disturbance identification, and pole selection. At last, with a protection platform and a real-time digital simulator (RTDS) platform of the MMC-HVDC grid, the accuracy and the robustness of the proposed protection method are verified. The results show that the protection method can correctly identify faults with different distances and resistance in 1 ms and has strong robustness against transition resistance, sampling frequency, boundary value, noise, system topology, and line parameters. [ABSTRACT FROM AUTHOR]

The wind farm (WF) provides fast frequency regulation (FFR) has become a consensus in low-inertia power systems. However, the optimal power sharing within the large-scale WF during the FFR process is intractable. Inspired by the intrinsic similarity between the information flow and the power flow, this paper proposes a distributed power sharing control for the FFR of the large-scale WF based on the idea of equation-based congestion control (EBCC). Concretely, a global congestion index, reflecting the deviation between the output power and the FFR order of the WF, is introduced for power tracking at the WF level. Besides, a local congestion index, which implies the operating cost of each WT, is constructed to reduce the operating cost of the WF. Then, the power sharing of each WT is determined locally. The distributed control significantly reduces the computational and communication burden, which makes the proposed method suitable for the large-scale WF, as well as meeting the demand of FFR. Moreover, the robustness to varying operating conditions makes the method practical and attractive. Finally, the effectiveness of the proposed method is verified under various scenarios by simulations. • The concept of congestion control is introduced in the WF power sharing issue. • It achieves distributed and non-iterative optimal power sharing among WTs. • It has a lightweight computational and communication burden. • It tracks various FR orders rapidly and smoothly with less operating cost. • Optimization objectives is flexible and can be customizable. [ABSTRACT FROM AUTHOR]

The liquid–liquid coexistence curves for the binary solutions of the room temperature ionic liquid (RTIL) 1-methyl-3-octylimidazolium tetrafluoroborate ([C 8 mim][BF 4 ]) in 1-pentanol and 1-hexanol were measured in the critical region. The critical exponent β and the critical amplitude B were deduced and the former was found to be consistent with the 3D-Ising value. The complete scaling theory was applied to describe the asymmetry of the diameters of the coexistence curves. Moreover, the dependences of the critical temperature, the critical mole fraction, the reduced critical temperature and the reduced critical density on the permittivity of alcohol for a series of binary solutions of RTIL in alcohols were discussed. [ABSTRACT FROM AUTHOR]

The lack of fault data is the major constraint on data-driven fault detection and isolation schemes for DC microgrids. To solve this problem, this paper develops an adversarial-based deep transfer learning model that can detect and classify short-circuit faults in DC microgrids without using historical fault data. In this transfer learning framework, the knowledge of faults is extracted from the transient features of line currents during normal operating disturbances, which is adversarially augmented and then transferred to a target domain as the labels of faults. With the transferred knowledge, a deep learning model combining convolutional neural network and attention-based bidirectional long short-term memory is trained, which is strengthened by attention and soft-voting ensemble mechanisms. In verification tests, this model reaches a high accuracy of over 90 % in classifying various short-circuit faults in a multi-terminal DC microgrid model within a short response time of less than 1 ms. Moreover, it is robust against measurement noises and adaptive to system configuration changes. The test results prove the effectiveness of the proposed method in the protection of DC microgrids without prior knowledge of faults. • No historical fault data needed for the proposed fault classification model. • Fault knowledge obtained from non-fault disturbances through transfer learning. • High accuracy (> 90 %) and short response time (< 1 ms). • Good robustness against measurement noises and changes in system configurations. [ABSTRACT FROM AUTHOR]

The rehabilitation of disaster-prone areas can enhance the stability of soil structure and is a common way to increase organic carbon storage. The response of soil carbon sequestration pathways to different recovery modes is not clear, especially in mountain soils. After 11 years of recovery, we evaluated soil organic carbon (SOC) sequestration pathways in plantations (dominated by Olea europaea 'Leccino'), croplands [ Zea mays (L.) ] natural shrublands (Lycium chinense Mill), and natural grasslands [ Setaria viridis (L.) Beauv ]. The physical and chemical properties of the soil and the 13C natural abundance of each aggregate and its density components were studied. The results showed that, during the restoration process, the soil organic carbon content of natural grassland increased the most, while the δ13C value of soil of natural shrubs was the highest. The natural abundance of 13C was used to reveal the pathway of C flow in soil organic matter (SOM), as follows: free light fractions (ρ < 1.6 g cm−3)→mineral fractions (ρ > 2.0 g cm−3)→dense occluded fractions (ρ from 1.6 to 2.0 g cm−3) (in plantation, natural shrubland, and grassland). However, in cropland soil, C flowed as follows: mineral fractions→free light fractions→dense occluded fractions. Specifically, the SOC content decreased with aggregate particle size, and after entering the soil, plant litter was first stored in large aggregates and then decomposed into the free light fraction. The study revealed the mechanism of organic carbon sequestration in the restoration area, emphasizing that artificial restoration treatment can change the carbon conversion pathway, and reduced the sequestration of organic carbon. • The pathways of organic carbon turnover had been clearly determined by 13C natural abundance. • Natural grasslands have the highest soil organic carbon content under the same years of restoration. • δ13C was more enriched in micro-aggregates than in large and small macro-aggregates. • Artificial restoration altered the carbon flow pathway of transformation and reduced the sequestration of organic carbon. [ABSTRACT FROM AUTHOR]