Search Results (610)

Virtual synchronous generator (VSG) simulates the dynamic characteristics of synchronous generator, offering significant advantages in flexibly adjusting virtual inertia and damping parameters. However, their dynamic stability is susceptible to constraints such as control parameter design, grid disturbances, and the intermittent nature of distributed power sources. This study addresses the degradation of transient performance in traditional sliding mode control for VSG, caused by insufficient multi-parameter cooperative adaptation. It proposes an adaptive sliding mode control strategy based on radial basis function (RBF) neural networks. Through theoretical analysis of the influence mechanism of virtual inertia and damping coefficient perturbations on system stability, the RBF neural network achieves dynamic parameter decoupling and nonlinear mapping. Combined with an integral-type sliding surface to design a weight-adaptive convergence law, it effectively avoids local optima and ensures global stability. This strategy not only enables multi-parameter cooperative adaptive regulation of frequency fluctuations but also significantly enhances the system’s robustness under parameter perturbations. Simulation results demonstrate that compared to traditional control methods, the proposed strategy exhibits significant advantages in dynamic response speed and overshoot suppression. Full article

This paper analyzes the behavior of a three-phase induction motor (IM) during voltage sags in the supply network and its subsequent re-acceleration following voltage recovery. A dynamic mathematical model based on the two-axis (d,q) representation of the IM is developed, taking into account variations in supply voltage, electromagnetic torque, and stator currents over time. The model enables a detailed assessment of motor stability and transient behavior when the supply voltage falls below nominal levels. The analysis covers sag depths of 0.9–0.5 ${\mathrm{U}}_{\mathrm{N}}$ and interruption durations of 0.14 s and 1.14 s, quantifying stator currents and electromagnetic torque both at the instant of the dip and within the first cycles after recovery. Particular attention is given to identifying the conditions under which the IM may fail to re-accelerate or transition into generator mode, depending on the depth and duration of the voltage sag and the type of mechanical load. The study includes simulations for a 0.75 kW IM under both constant and variable torque conditions, as well as different types and durations of short-circuit faults in the supply system. Results show that sag duration has little effect at sag onset but strongly influences recovery inrush and torque oscillations; shorter interruptions yield lower recovery currents. The findings provide practical insights for the design of more robust power supply infrastructures and the refinement of motor control and protection strategies. Full article

The increasing integration of power-electronic devices, such as voltage source converter-based high-voltage direct current (VSC-HVDC) systems and inverter-interfaced renewable energy sources (RESs), has rendered conventional short-circuit current (SCC) calculation methods inadequate. This paper proposes a novel analytical model that explicitly incorporates the current-limiting control dynamics of voltage source converters to accurately determine SCCs. The key contribution is a simplified yet accurate formulation that captures the transient behavior during faults, offering a more realistic assessment compared to traditional quasi-steady-state approaches. The proposed model was rigorously validated through electromagnetic transient (EMT) simulations and large-scale case studies. The results demonstrate that the method reduces the SCC calculation error to below 4%. Furthermore, when applied to the real-world provincial power grids of ZJ and JS, all computations converged within 10 iterations, confirming its robust numerical stability. These findings offer valuable insights for protection coordination studies and verify the model’s effectiveness as a reliable tool for planning future power systems with high power-electronics penetration. Full article

The rapid global expansion of photovoltaic (PV) generation has increased the prevalence of PV-dominated weak-grid systems, where wideband oscillations (WBOs) pose a significant challenge to secure and reliable operation. Unlike conventional electromechanical oscillations, WBOs originate from inverter control loops and multi-inverter interactions, spanning sub-Hz to kHz ranges. This review provides a PV-focused and mitigation-oriented analysis that addresses this gap. First, it clarifies the mechanisms of WBOs by mapping oscillatory drivers such as phase-locked loop dynamics, constant power control, converter–grid impedance resonance, and high-frequency switching effects to their corresponding frequency bands, alongside their engineering implications. Second, analysis methods are systematically evaluated, including eigenvalue and impedance-based models, electromagnetic transient simulations, and measurement- and data-driven techniques, with a comparative assessment of their strengths, limitations, and practical applications. Third, mitigation strategies are classified across converter-, plant-, and system-levels, ranging from adaptive control and virtual impedance to coordinated PV-battery energy storage systems (BESS) operation and grid-forming inverters. The review concludes by identifying future directions in grid-forming operation, artificial intelligence (AI)-driven adaptive stability, hybrid PV-BESS-hydrogen integration, and the establishment of standardized compliance frameworks. By integrating mechanisms, methods, and mitigation strategies, this work provides a comprehensive roadmap for addressing oscillatory stability in PV-dominated weak grids. Full article

With the rapid development of solar thermal power generation technology, the structural stability of the dish solar concentrator system under complex wind environments has become a critical limiting factor for its large-scale application. This study investigates the flow field distribution and structural response under fluctuating wind loads using computational fluid dynamics (CFD). A three-dimensional model was developed and simulated in ANSYS Fluent under varying wind angles and speed cycles. The results indicate that changes in the concentrator’s orientation significantly influence the airflow field, with the most adverse effects observed at low elevation angles (0°) and an azimuth angle of 60°. Short-period wind loads (T = 25 s) exacerbate transient impact effects of lift forces and overturning moments, markedly increasing structural fatigue risks. Long-period winds (T = 50 s) amplify cumulative drag forces and tilting moments (e.g., peak drag of −73.9 kN at β = 0°). Key parameters for wind-resistant design are identified, including critical angles and period-dependent load characteristics. Full article

This paper proposes a stepwise expert-teaching reinforcement learning framework for intelligent frequency control in hydro–thermal–wind–solar–compressed air energy storage (CAES) integrated systems under high renewable energy penetration. The proposed method addresses the frequency stability challenge in low-inertia, high-volatility power systems, particularly in Southwest China, where large-scale renewable-energy-based energy bases are rapidly emerging. A load frequency control (LFC) model is constructed to serve as the training and validation environment, reflecting the dynamic characteristics of the hybrid system. The stepwise expert-teaching PPO (SETP) framework introduces a stepwise training mechanism in which expert knowledge is embedded to guide the policy learning process and training parameters are dynamically adjusted based on observed performance. Comparative simulations under multiple disturbance scenarios are conducted on benchmark systems. Results show that the proposed method outperforms standard proximal policy optimization (PPO) and traditional PI control in both transient response and coordination performance. Full article

To address the insufficient consideration of system static voltage stability and PV–load coupling in distributed photovoltaic (PV) hosting capacity assessment, this study first investigates the impact of distributed PV integration on power system transient voltage stability based on a typical power supply system. Building on this analysis, we propose a Static Grid Stability Margin (SGSM) index. Subsequently, leveraging historical PV and load data, the copula function is introduced to establish a joint distribution function characterizing their correlation. Massive evaluation scenarios are generated through sampling, with robust clustering methods employed to form representative evaluation scenarios. Finally, a distributed PV bearing capacity assessment model is established with the objectives of maximizing PV bearing capacity, optimizing economic efficiency, and enhancing static voltage stability. Through simulation verification, the power system has a higher capacity for distributed PV when distributed PV is integrated into nodes with weak static voltage stability and a decentralized integration scheme is adopted. Full article

The calculation of Total Transfer Capability (TTC) for transmission corridors serves as the foundation for security region determination and electricity market transactions. However, existing TTC methods often neglect corridor correlations, leading to overly optimistic results. TTC computation involves complex stability verification and requires enumerating numerous renewable energy operation scenarios to establish security boundaries, exhibiting high non-convexity and nonlinearity that challenge gradient-based iterative algorithms in approaching global optima. Furthermore, practical power systems feature coupled corridor effects, transforming multi-corridor TTC into a complex Pareto frontier search problem. This paper proposes a MOEA/D-FRRMAB (Fitness–Rate–Reward Multi-Armed Bandit)-based method featuring: (1) a TTC model incorporating transient angle stability constraints, steady-state operational limits, and inter-corridor power interactions and (2) a decomposition strategy converting the multi-objective problem into subproblems, enhanced by MOEA/D-FRRMAB for improved Pareto front convergence and diversity. IEEE 39-bus tests demonstrate superior solution accuracy and diversity, providing dispatch centers with more reliable multi-corridor TTC strategies. Full article

This paper proposes a predefined time transient coordinated control strategy based on an adaptive nonlinear extended state observer (ANLESO) to address the adaptability challenges of mode transition control in power-split hybrid electric vehicles (PS-HEVs). Firstly, building upon a conventional dynamic coordinated control framework, the influence of varying acceleration conditions and external disturbances on mode transition performance is analyzed. To enhance disturbance estimation under both positive and negative as well as large and small errors, an ANLESO is developed, which not only improves the speed and accuracy of disturbance observation but also guarantees symmetric convergence performance with respect to estimation errors. Subsequently, a predefined time feedback controller is developed based on the theory of predefined time control. Theoretical stability analysis demonstrates that the convergence time of the system is independent of the initial state and can be guaranteed within a predefined time. Finally, the feasibility and superiority of the proposed control strategy are validated through Hardware-in-the-Loop (HIL) testing and vehicle experimentation. The results show that, compared with PID control based on a linear expansion state observer, the proposed strategy reduces the mode transition time by 45.7% and mitigates drivability shock by 59.2%. Full article

Ensuring reliable power system control demands innovative architectural solutions. This research introduces a fault-tolerant hybrid parallel compensator architecture for load frequency control (LFC), combining a Proportional–Integral–Derivative with Filter (PIDF) compensator with a Fuzzy Fractional-Order PI-PD (Fuzzy FOPI–FOPD) module. Particle Swarm Optimization (PSO) determines optimal PID gains, while the Catch Fish Optimization Algorithm (CFOA) tunes the Fuzzy FOPI–FOPD parameters—both minimizing the Integral Time Absolute Error (ITAE) index. The parallel compensator structure guarantees continuous operation during subsystem faults, substantially boosting grid reliability. Rigorous partial failure tests confirm uncompromised performance-controlled degradation. Benchmark comparisons against contemporary controllers reveal the proposed architecture’s superiority, quantifiable through transient metric enhancements: undershoot suppression (−9.57 × 10⁻⁵ p.u. to −1.17 × 10⁻⁷ p.u.), settling time improvement (8.8000 s to 3.1511 s), and ITAE reduction (0.0007891 to 0.0000001608), verifying precision and stability gains. Resilience analyses across parameter drift and step load scenarios, simulated in MATLAB/Simulink, demonstrate superior disturbance attenuation and operational stability. These outcomes confirm the solution’s robustness, dependability, and field readiness. Overall, this study introduces a transformative LFC strategy with high practical viability for modern power networks. Full article

A multi-port conversion system that connects photovoltaic (PV) arrays, battery energy storage (BES), and an electric vehicle (EV) to a single-phase grid offers a flexible solution for smart homes. By integrating Vehicle-to-Grid (V2G) and Vehicle-to-Home (V2H) technologies, the system supports bidirectional energy flow, optimizing usage, improving grid stability, and supplying backup power. The proposed four-port converter consists of an interleaved bidirectional DC-DC converter for high-voltage BES, a bidirectional buck–boost DC-DC converter for EV charging and discharging, a DC-DC boost converter with MPPT for PV, and a grid-tied inverter. Its non-isolated structure ensures high efficiency, compact design, and fewer switches, making it suitable for residential applications. A state-of-charge (SoC)-based power management strategy coordinates operation among PV, BES, and EV in both on-grid and off-grid modes. It reduces reliance on EV energy when supporting V2G and V2H, while SoC balancing between BES and EV extends lifetime and lowers current stress. A 7.5 kVA system was simulated in MATLAB/Simulink to validate feasibility. Two scenarios were studied: PV, BES, and EV with V2G supporting the grid and PV, BES, and EV with V2H providing backup power in off-grid mode. Tests under PV fluctuations and load variations confirmed the effectiveness of the proposed design. The system exhibited a fast transient response of 0.05 s during grid-support operation and maintained stable voltage and frequency in off-grid mode despite PV and load fluctuations. Its protection scheme disconnected overloads within 0.01 s, while harmonic distortions in both cases remained modest and complied with EN50610 standards. Full article

Unplanned islanding and off-grid issues of photovoltaic (PV) power stations caused by tie-line faults have seriously undermined the power supply reliability and operational stability of PV plants. Furthermore, it takes a relatively long time to restore normal operation after an off-grid event, leading to substantial power losses. To address this problem, this paper proposes a tie-line fault ride-through control strategy based on the coordinated control of on-site energy storage units. After a fault on the tie-line occurs, the control mode of PV inverters is switched to achieve source–load balance, and the control mode of energy storage inverters is switched to VF control mode, which supports the stability of voltage and frequency in the islanded system. Subsequently, the strategy coordinates with the tie-line recloser device to perform synchronous checking and grid reconnection. Simulation results show that, for transient tie-line faults, the proposed method can achieve stable control of the islanded system and grid reconnection within 2 s after a fault on the tie-line occurs. It successfully realizes fault ride-through within the operation time limit of anti-islanding protection, effectively preventing the PV plant from disconnecting from the grid. Finally, a connection scheme for the control strategy of a typical PV plant is presented, providing technical reference for on-site engineering. Full article

This paper investigates the transient stability of Grid-Forming (GFM) Permanent Magnet Synchronous Generator (PMSG) systems during grid faults. An analysis demonstrates how a fixed saturated current angle can trap the system in undesirable operating points, while reactive power coupling can degrade performance. Both factors pose a risk of turbine overspeed and instability. To overcome these vulnerabilities, a dual-mechanism control strategy is proposed, featuring an adaptive saturated current angle control that, unlike conventional fixed-angle methods, which risk creating Current Limiting Control (CLC) equilibrium points, dynamically aligns the current vector with the grid voltage to guarantee a stable post-fault trajectory. The effectiveness of the proposed strategy is validated through time-domain simulations in MATLAB/Simulink. The results show that the proposed control not only prevents overspeed trip failures seen in conventional methods but also reduces post-fault recovery time by over 60% and significantly improves system damping, ensuring robust fault ride-through and enhancing overall system stability. Full article

To address the problem of transient disturbance arising during the grid-following (GFL) and grid-forming (GFM) mode switching of energy storage converters, this paper proposes a dual-mode seamless switching control strategy. First, we conduct an in-depth analysis of the mechanism behind switching transients, identifying that sudden changes in current commands and angle-control misalignment are the key factors triggering oscillations in system power and voltage frequency. To overcome this, we design a virtual synchronous generator (VSG) control angle-tracking technique based on the construction of triangular functions, which effectively eliminates the influence of periodic phase-angle jumps on tracking accuracy and achieves precise pre-synchronization of the microgrid phase in GFM mode. Additionally, we employ a current-command seamless switching technique involving real-time latching and synchronization of the inner-loop current references between the two modes, ensuring continuity of control commands at the switching instant. The simulation and hardware-in-the-loop (HIL) experimental results show that the proposed strategy does not require retuning of the parameters after switching, greatly suppresses voltage and frequency fluctuations during mode transition, and achieves smooth, rapid, seamless switching between the GFL and GFM modes of the energy storage converter, thereby improving the stability of microgrid operation. Full article

To address the persistent challenge of reliable real-time flowrate estimation in complex offshore oil production systems using Electric Submersible Pumps (ESPs), this study proposes a hybrid modeling approach that integrates a first-principles hydrodynamic model with Long Short-Term Memory (LSTM) neural networks. The aim is to enhance prediction accuracy across five offshore wells (A through E) in Brazil, particularly under conditions of limited or noisy sensor data. The methodology encompasses exploratory data analysis, preprocessing, model development, training, and validation using high-frequency operational data, including active power, frequency, and pressure, all collected at one-minute intervals. The LSTM architectures were tailored to the operational stability of each well, ranging from simpler configurations for stable wells to more complex structures for transient systems. Results indicate that prediction accuracy is strongly correlated with operational stability: LSTM models achieved near-perfect forecasts in stable wells such as Well E, with minimal residuals, and effectively captured cyclical patterns in unstable wells such as Well B, albeit with greater error dispersion during abrupt transients. The model also demonstrated adaptability to planned interruptions, as observed in Well A. Statistical validation using ANOVA, Levene’s test, and Tukey’s HSD confirmed significant performance differences (α < 0.01) among the wells, underscoring the importance of well-specific model tuning. This study confirms that the LSTM-based hybrid approach is a robust and scalable solution for real-time flowrate forecasting in digital oilfields, supporting production optimization and fault detection, while laying the groundwork for future advances in adaptive and interpretable modeling of complex petroleum systems. Full article