The detailed modeling of renewable energy power stations captures the full impedance characteristics of the system but significantly increases the scale of electromagnetic transient (EMT) simulations. Parallel computing is essential to enhance the simulation efficiency, but it requires algorithms that are specifically designed to leverage the architecture of high-performance hardware. This paper proposes the generalized latency insertion method (GLIM) to establish component-level models for renewable energy power systems. GLIM extends its applicability to complex equipment incompatible with the constraints of the traditional latency insertion method (LIM) by introducing controlled sources. In this way, the simulation of complex power systems can be transformed into the solution of massive GLIM basic topologies. Then, according to the multi-thread parallel and optimized storage techniques, GLIM conducts fine-grained simulations on graphics processing units (GPUs), significantly improving the solving efficiency. In the case study, a renewable energy power system with large-scale wind farm integration is used to demonstrate the effectiveness of GLIM on a GeForce RTX 3060 laptop GPU. The simulation accuracy of GLIM is verified through comparison with PSCAD, and the simulation efficiency is verified by changing the scale of wind farms.

Existing real-time simulation methods for cascaded power electronic systems face significant challenges. Physics-driven approaches often suffer from limited applicability when critical system information is unavailable, as well as inefficiency due to the extensive manual effort required for model derivation. Conversely, data-driven methods are constrained by large data demands and prolonged training times. To address these limitations, this article proposes a hybrid data-physics-driven (HDPD) modeling method. The cascaded subcircuits, referred to as "modules," are represented by discretized state-space equations with associated transition matrices. At the module level, a data-driven approach based on the least squares method is employed to automatically generate the transition matrices, utilizing data obtained from short-duration offline simulations. At the system level, a physics-driven approach is applied to directly compute the equivalent model of the cascaded system, leveraging the inherent characteristics of series and parallel connections. The proposed HDPD method is applied to the cascaded solid-state transformer using an established CPU-field-programmable gate array real-time simulation platform. Results demonstrate that the proposed approach effectively balances the strengths of data-driven and physics-based modeling, providing high efficiency and flexibility in model development, while maintaining strong parallelism and low computational complexity during simulation. Consequently, the method facilitates convenient model construction and enables large-scale simulations with improved scalability.

The decoupling method based on the natural or inserted artificial delays, when applied to the simulation of power electronic (PE) systems, may encounter challenges such as inadequate length of delay lines or numerical instability and precision issues due to the high-frequency voltage/current variations at interfaces. To deal with the challenge, a delay-free decoupling method is proposed in this article. The method reduces both the dimension of matrix multiplication and the number of switch state combinations without sacrificing numerical stability and compresses the calculation progress by representing the decoupled system with the discrete state-space equation. The PE system is decoupled at the series/parallel interface of submodules, treating currents as boundary variables linked to each submodule's extended port. A preliminary formula for these variables is derived by simultaneously solving nodal voltage equations and kirchhoff voltage laws (KVL) equations. Submodule solutions are compacted and parallelized based on the discrete state-space equations. These equations are then substituted back and decomposing boundary variables into independent segments, to achieve parallelization of boundary variable solutions. The proposed method is validated through real-time simulation of cascaded PE systems on an field programmable gate array (FPGA) platform with a 250 ns time step. Results show that it achieves high precision compared to nondecoupled systems in power systems computer aided design (PSCAD) across diverse transient conditions. Additionally, it boosts the simulation scale by roughly 2-7 times on the FPGA-based platform compared to nondecoupled nodal analysis.

The aggregation models of renewable energy power stations are difficult to apply to the stability research of the fault inside the station or the oscillation analysis between the station and the grid-side system, and the high dimensional characteristics of their detailed model will pose an enormous challenge to the simulation efficiency. To alleviate the contradiction between accuracy and efficiency, this paper proposes a state-variable-preserving method to efficiently model inverter-based resources and a node tearing method to realize parallel simulation of the renewable energy power station consisting of inverter-based resources. The state-variable-preserving model uses discrete state space expression to eliminate the internal nodes on the basis of preserving the original variables of the generation unit and reduces the solving scale of the generation station. The node tearing method reduces the solving complexity of the associated variables, which is more consistent with the topology characteristic that different power generation clusters are interconnected by the same bus. In the case study, the results of numerical accuracy analysis and numerical stability analysis of a photovoltaic power plant verify the reliability of the proposed method, and its simulation efficiency is verified by changing the scale of the photovoltaic power plant.

Regard to the real-time dynamic digital twin modelling problem of a new-type distribution network that includes distributed resources such as distributed photovoltaic, energy storage, charging pile, and electric vehicle, a new-type distribution network digital twin topology modeling method based on Common Information Model (CIM) specifications and spectral clustering is proposed. Firstly, according to the specifications of the CIM standard, the digital twin topology models of distributed resources are extended and established. Secondly, based on the digital twin topology models of distributed resources, a digital twin aggregation modelling method for new-type distribution network is proposed based on spectral clustering. Furthermore, an online linked update strategy for the digital twin model of new-type distribution network that integrates real-time topology states is proposed. Finally, a case study is conducted on a distribution network in a certain demonstration area in China, and the results verify the practicability and effectiveness of the method proposed in this paper. This lays the foundation for the application of electrical network twin analysis, such as power flow calculation, optimal power flow, economic dispatch, and safety check, in a new-type distribution network that includes diversified distributed resources.

External disturbances can induce torsional oscilla-tion with weak damping in the shaft system of permanent mag-net synchronous generators(PMSGs)based wind generation system,thereby inducing low-frequency oscillations.However,the influence of electromagnetic torque on the shaft system damping and corresponding parameter laws have been scarcely explored.We define the electrical damping coefficient as a quan-titative measure for the influence of electromagnetic torque on the shaft system damping.The torsional oscillation damping characteristics of the shaft system under vector control are ana-lyzed,and the transfer function for electromagnetic torque and speed is derived.Additionally,we elucidate the mechanism by which the electromagnetic torque influences the shaft system damping.Simultaneously,laws describing the influence of wind speed,system parameters,and control parameters on the tor-sional oscillation damping are analyzed.Accordingly,the opti-mal damping angle of the shaft system a torsional oscillation suppression strategy is proposed to compensate for with uncer-tainty in the parameters affecting damping.The studied system is modeled using MATLAB/Simulink,and the simulation results validate the effectiveness of the theoretical analysis and pro-posed torsional oscillation suppression strategy.

Although (poly)phenols have shown potential in anti-cancer activities, their impact on improving ovarian cancer (OC) survival remains unknown. Therefore, we aim to first investigate the association between dietary polyphenol intake and OC survival, providing valuable insights into potential interventions. The prospective cohort recruited 560 patients with OC to assess the associations of polyphenol intake, not only pre- and post-diagnosis but also the change from pre- to post-diagnosis with OC survival. Dietary intakes of total (poly)phenols and their five classes (flavonoids, phenolic acids, lignans, stilbenes, and other polyphenols) were assessed using a validated 111-item food frequency questionnaire. Overall survival (OS) was tracked through active follow-up and medical records until February 16th, 2023. Cox proportional hazard regression models were applied to calculate the hazard ratios (HR) and 95

Voltage source converter (VSC)-based power systems are characterized by oscillations with extensive propagation, wide-band responses, and complex multi-modal coupling. Analyzing the stability of these systems poses significant challenges due to their high-order features and the need for flexible analysis models. To address these issues, this paper proposes a novel multi-domain-mapping (MDM) based impedance calculation method, notable for its efficiency, flexibility, and precision. The discrete-time small-signal models (DT-SSMs) at the component level are established replace conventional continuous-time SSMs (CT-SSMs). Furtherly, the subsystems are described using the nodal analysis method (NAM), and then directly equivalent to portal equivalent SSMs (PE-SSMs). By leveraging the superposition theorem and mapping between the z-plane and s-plane, the admittance and impedance matrices in discrete-frequency (DF) and continuous-frequency (CF) domains are derived. This method facilitates the straightforward construction of system-level models and the efficient acquisition of impedance for large-scale systems, making it readily implementable on computers. The accuracy and efficiency of this method are validated through comparisons with existing analytical calculation methods, frequency scanning methods, and time-domain simulations in cases of a VSC-based microgrid and a wind farm.

The switching frequency of power electronic converters can be as high as hundreds of kilohertz in some cases. The time-step of the real-time simulation is generally suggested to be about one percent of the switching period to accurately locate the switch event. That brings great computation burden in unit time. To break this limitation, this article proposes a real-time simulation method based on the idea of switching period synchronization (SPS). The simulation time is synchronized with the reality time at an interval of the switching period, instead of the time-step. The switching period is adopted as the synchronization interval and also as the main time-step, which is further divided into several variable sub-time-steps determined by switch events within the switching period. To implement the proposed real-time simulation on the field-programmable gate array-based platform, an electromagnetic transient model in discrete-state-space form is proposed to simulate the circuit with the variable subtime-steps. The hardware-in-the-loop simulation of an on-board charger shows that the proposed method can realize the real-time simulation with a switching frequency of 200 kHz. The accuracy, efficiency, and applicability of the proposed method have been further validated.

The complicated control structure and limited dynamic performance restrict the overmodulation operation of the hybrid modular multilevel converter (MMC) in the medium-voltage DC (MVDC) distribution network. To solve these issues, a model predictive control method is proposed for the hybrid MMC in this paper. The proposed method selected the number of inserted submodules (SMs) of each arm as the control option. Firstly, by expanding the search range of the control options into a negative number, the full-bridge (FB) SMs can be reversely inserted, and the hybrid MMC can operate under overmodulation conditions. Secondly, only the adjacent numbers of the historical optimal options are evaluated in each period. As a result, the computation burden can be reduced, and the dv/dt of the output voltage can be minimized. Afterward, the state variables of the hybrid MMC are predicted based on the discrete system model. Finally, the cost function is designed where the sum and difference of arm capacitor voltages are integrated to balance the arm energy, and the optimal control options are selected according to the evaluated cost function. Simulation and experimental results verify that by the proposed method, the hybrid MMC can operate normally under both normal and overmodulation conditions.

With good adaptability to weak power grids, the grid-forming inverter becomes the foundation of future power grids with high-proportion renewable energy. Moreover, the virtual synchronous generator (VSG) control is recognized as the mainstream control strategy for grid-forming inverters. For permanent magnet synchronous generator (PMSG) based wind generation systems connected to power grid via VSG-controlled grid-forming inverters, some novel impacts on the low-frequency oscillations (LFOs) emerge in power grids. The first impact involves the negative/positive damping effect on LFOs. In this paper, the small-signal torque model of VSG-controlled PMSG-based wind generation systems is established based on the damping torque analysis method, revealing the influence mechanism of machine-side dynamics on LFOs and proving the necessity of the double-mass model for accurate stability analysis. The second impact is the resonance effect between torsional oscillation and LFOs. Subsequently, this paper uses the open-loop resonance analysis method to study the resonance mechanism and to predict the root trajectory. Then, a damping enhancement strategy is proposed to weaken and eliminate the negative damping effect of machine-side dynamics on LFOs and the resonance effect between torsional oscillation and LFOs. Finally, the analysis result is validated through a case study involving the connection of the VSG-controlled PMSG-based wind generation system to the IEEE 39-bus AC grid, supporting the industrial application and stable operation of VSG-controlled PMSG-based wind generation systems.

As power systems become increasingly complex, the analysis of large-scale electromagnetic transient simulations faces challenges such as excessive bandwidth consumption for simulation result transmission and insufficient local analysis capabilities of users. To address this bottleneck, this paper proposes a multi-level on-site intelligent analysis framework that runs directly on a supercomputing platform. This framework facilitates the conversion of terabyte-level raw waveform data into the delivery of lightweight core analysis conclusions. The core methodology comprises a three-tier architecture: first, automatically identifying different simulation application scenarios; second, employing embedded zero-tree wavelet and other compression algorithms to achieve efficient data compression while preserving features; and finally, calculating key performance metrics. The efficacy of the framework is demonstrated in this paper through two simulation examples–optimal parameter analysis and impedance sweep analysis–implemented on the MATLAB/Simulink platform.

Power electronic converters are gradually developing towards modularization and cascaded structures to adapt to high voltage, large capacity, and various energy conversion scenarios. However, the real-time simulation models of cascaded power electronic converters are mainly aimed at specific topologies. For example, commercial real-time simulators have developed various package models for modular multilevel converter (MMC). But package models are difficult to meet the simulation requirements of more new topologies such as solid-state transformer (SST). This paper proposes a general real-time simulation method for cascaded power electronic converters based on N-port submodules of any topology and any cascaded structure. Firstly, a general equivalent model of N-port submodules is built. Based on the equivalent model, the topology of each N-port submodule can be customized, and the simulation efficiency can be improved by eliminating the internal nodes of each submodule. Secondly, the incidence matrix is redefined to describe the cascade structures of submodules, which is more flexible than the traditional method and can avoid the decoupling between submodules. Cascaded power electronic converters based on single-port, dual-port and four-port submodule are simulated on the NI-PXI based real-time simulation platform, which verifies the universality and efficiency of the proposed method.

Most permanent magnet synchronous generator (PMSG)-based wind systems currently employ grid-following control, relying on a phase-locked loop (PLL) for grid connection. However, it leads to a lack of inertia support in the system. To address this, virtual inertia control (VIC) is essential for improvement, but it introduces new impacts on the grid-connected PMSG-based wind-driven system. The first impact is the deterioration of torsional oscillation damping. This paper establishes a small-signal model of the grid-connected PMSG-based wind-driven system using the damping torque method and small-signal analysis. It derives the transfer function of electromagnetic torque and speed difference considering VIC, explaining the mechanism and influence of VIC parameters on torsional oscillation damping characteristic. The second impact is the resonance between torsional, PLL, and low-frequency oscillations. This paper uses open-loop resonance analysis and eigenvalue analysis methods are employed to investigate the resonance mechanism between quasi-electromechanical timescale (QET) oscillations and predict the corresponding root locus using the residue method. Finally, the effectiveness of the theoretical analysis is validated through a simulation case study of PMSG-based wind-driven system connected to the four-machine two-area (FMTA) system using the SIMULINK platform.

The integration of renewable energy has expanded the time scale range of power systems, making the stability dynamics more complex. Analyzing stability issues across different time scales using a globally detailed model by adding more computational resources is a high-cost approach with low resource efficiency. Although existing hybrid simulation methods take into account the multi-time-scale characteristics of the system, the differences in algorithm frameworks among various types of simulation programs lead to a lack of flexibility in modeling and simulation. To address this problem, this paper proposes an adjustable resolution modeling and layered hybrid decoupling method for renewable energy power systems. The adjustable resolution models can control the level of detail in equipment modeling and flexibly adjust the model resolution of different regions according to research requirements. The layered hybrid decoupling method is suitable for regional power grids and renewable energy stations with different topological connection characteristics, which can further enhance the simulation flexibility of complex power systems combined with adjustable resolution models. In the case study, simulation results show that the proposed method can improve the solving efficiency of renewable energy power systems while ensuring reasonable accuracy.

Most permanent magnet synchronous generator(PMSG)based wind generation systems currently employ grid-following control,relying on a phase-locked loop(PLL)for grid connection.However,it leads to a lack of inertia support in the system.To address this,the virtual inertia control(VIC)is cru-cial for improvement,yet it introduces potential instability due to torsional oscillation interaction with PLL and low-frequency oscillations,which is an underexplored area.This paper pres-ents a comprehensive analysis of the grid-connected PMSG-based wind generation system.It confirms the necessity of em-ploying a full-order model for studying stability on the quasi-electromechanical timescale(QET)by a comparison with the re-duced-order model.Then,a comprehensive modal analysis is conducted to analyze the effect of VIC parameters,shaft inertia time constant,PLL parameters,and torsional oscillation damp-ing(TOD)controller gain on the interaction of QET oscillations under two typical control strategies.The occurrence of interac-tion and mode conversion is observed when the oscillation fre-quency and root loci of the torsional,PLL,and low-frequency oscillations are close.Finally,a theoretical analysis is validated via simulation verification in Simulink.These findings offer a valuable guidance for industrial PMSG applications considering VIC.

The high penetrability of renewable energy and the increasing demand for hydrogen energy pose challenges to system scheduling and the accommodation of photovoltaic and wind power. Therefore, a data-driven multienergy economic scheduling method with experiential knowledge bases is proposed to enhance system operational efficiency and economic performance. Firstly, the Wasserstein generative adversarial network is used to enhance wind power and photovoltaic historical samples. The K-medoids clustering algorithm and & phi;-divergence are applied to achieve scenario reduction and acquire fuzzy sets, eliminating the need for assumptions about their probability distributions. Secondly, a kernel density estimation is used to improve the accuracy of characterizing the probability distribution of energy loads. Based on fuzzy sets, the distributionally robust optimization is used to achieve optimal scheduling in an integrated electricity-hydrogen-heat system. This technique enhances the accommodation capacity of photovoltaic and wind power while reducing operational costs. Finally, a decision-making technique based on an experiential knowledge base is studied, aiming to swiftly match corresponding decision variables by evaluating the similarity of labeled state variables. Simulation results show that the proposed method improves the decision-making speed by about 0.8 times and reduces operating costs and photovoltaic or wind power curtailment by at least 1%. The method can provide fast and efficient day-ahead economic scheduling for digitized integrated energy systems.

The majority of PMSG-based wind systems currently use grid-following control, which depends on a phase-locked loop (PLL) for grid connection. However, it leads to a lack of inertia support in the system. To tackle this issue, the implementation of virtual inertia control (VIC) is essential for improvement. However, it may introduce potential instability to the shaft system, which remains a relatively unexplored area. This paper provides a comprehensive analysis of a grid-connected wind farm (WF) system based on PMSG. It confirms the necessity of using a full-order model for studying system stability through a comparison with a reduced-order model. Furthermore, the transfer function of electromagnetic torque and speed difference in the PMSG is derived, taking VIC into account. The detrimental effect of VIC on shaft system damping is illustrated using the damping torque method. Subsequently, a comprehensive modal analysis is performed to assess how VIC parameters affect the primary oscillation modes in three common control scenarios. Lastly, the theoretical analysis is validated through SIMULINK simulation verification.

Most permanent magnet synchronous generator (PMSG)-based wind systems currently employ grid-following control, relying on a phase-locked loop (PLL) for grid connection. However, it leads to a lack of inertia support in the system. To address this, virtual inertia control (VIC) is essential for improvement, but it introduces new impacts on the grid-connected PMSG-based wind-driven system. It is the resonance between torsional, PLL, and low-frequency oscillations. This paper uses open-loop resonance analysis and eigenvalue analysis methods are employed to investigate the resonance mechanism between QET oscillations and predict the corresponding root locus using the residue method. Finally, the effectiveness of the theoretical analysis is validated through a simulation case study of PMSG-based wind-driven system connected to the four-machine two-area (FMTA) system using the SIMULINK platform.

Abstract To improve the stability of the hybrid modular multilevel converter (MMC), a simplified dominant mode‐based control parameter optimisation method of the hybrid MMC system is proposed. Firstly, in the medium‐voltage DC distribution network, the small‐signal model of the hybrid MMC is established. Secondly, the influence of a weak AC system on stability is analysed through eigenvalue analysis. Finally, a simplified objective function is designed for eigenvalues of the dominant mode by considering only real parts, and improved small‐signal stability can be achieved by control parameters optimisation. The proposed method optimises all control parameters at the same time, which further reduces the number of algorithm iterations. Simulation results show that by the proposed control parameter optimisation method, the hybrid MMC has better transient performance and reduced disturbance under SCR variation, indicating a significantly improved system stability, and the dynamic response time can be reduced.