Search Results (375)

Hydro-wind-solar hybrid power systems have become a mainstream configuration for new-type power systems. However, the high proportion of power-electronics-interfaced generation alters system inertia and damping characteristics, leading to complex high-dimensional frequency dynamics and severe stability challenges. This paper investigates the frequency response mechanism and Hopf bifurcation characteristics of the aggregated frequency response model for hydro-wind-solar hybrid power systems. First, primary frequency response models for hydropower, wind power, and photovoltaic (PV) generation are established under a small-signal analysis framework. On this basis, a tenth-order nonlinear dynamic model of the integrated system is constructed by considering hydraulic nonlinearities, virtual inertia control of wind power, and reserve-based frequency regulation of PV systems. Then, Hopf bifurcation theory is applied to analyze stability and oscillatory instability mechanisms of the high-dimensional system. The bifurcation conditions are derived via high-dimensional Jacobian matrix analysis and Routh-Hurwitz criterion, with supplementary normal form calculation and first Lyapunov coefficient derivation to identify the supercritical/subcritical nature of the bifurcation. Finally, numerical simulations under both small and large disturbances validate the theoretical analysis. The results demonstrate that variations in key control parameters may induce Hopf bifurcation, leading the high-dimensional system from a stable equilibrium to sustained low-frequency oscillations. The findings provide insights and practical guidance for stable operation and parameter tuning of hydro-wind-solar hybrid power systems. Full article

Wind-storage coordinated frequency regulation enhances the frequency stability of large-scale wind power systems. However, existing methods often rely on fixed parameters, limiting adaptability and accelerating energy storage depletion. To address these limitations, a coordinated control strategy based on dynamic weighting coefficients and model predictive control (MPC) is proposed. First, a dynamic weighting mechanism is designed to adaptively adjust the contributions of virtual inertia and droop control based on the system frequency state and the energy storage system’s (ESS) state of charge (SOC), thereby avoiding abrupt power variations and maintaining the SOC within safe limits. Second, an MPC-based rolling optimization model is established to continuously allocate the active power outputs between the doubly fed induction generator (DFIG) and the ESS, aiming to minimize both frequency deviations and regulation costs. Simulation results demonstrate the superiority of the proposed strategy. Under a step load disturbance, the maximum frequency deviation is reduced by 11.3%, and the peak time is shortened by 13% compared to conventional droop control. Furthermore, under continuous load fluctuations, the proposed approach significantly mitigates SOC depletion and minimizes system frequency fluctuations, proving its effectiveness in enhancing the frequency resilience of wind-storage combined systems. Full article

The increased penetration of renewable energy sources (RES) in the electrical grid has necessitated the concept of a Virtual Synchronous Generator (VSG) control which is used to make grid-connected power electronic converters behave as synchronous generators. While VSG controls are suitable for supporting the inertia of a microgrid, their use leads to grid instability in the event of a disturbance. This research addresses this limitation by integrating a fully connected Feedforward Neural Network (FCNN) into a VSG control to dynamically adjust the damping coefficient and inertia constant in real time. This approach could enhance system stability by reducing frequency and active power oscillations during grid disturbances, particularly during partial load rejection. To evaluate the effectiveness of the proposed method, a supervised learning-based FCNN was trained on VSG damping behavior under various grid disturbances. The trained model was then implemented in a simulation environment to regulate the VSG parameters dynamically. Simulation results show the neural network-based approach reduces high overshoots at the point of disturbance in active power and frequency oscillations; however, the VSG signal settles faster after the grid disturbance. These findings highlight the potential of machine learning in enhancing the stability of VSG-based microgrids, offering a computationally efficient solution for improving transient response and power-sharing performance. Full article

The increased penetration of renewable energy resources with low inertia poses a risk to the frequency and voltage stability of modern power systems. Therefore, it is important to investigate grid-support functions from inverter-interfaced technologies. While conventional software simulations provide valuable insights into system behavior, they fail to capture physical interactions and hardware dynamics. This paper presents a power-hardware-in-the-loop (PHIL) platform used to evaluate inverter grid-support functions in a physical microgrid supplied by two synchronous generators connected to a load bus. The inverter is implemented in Simulink, executed on a real-time simulator and interfaced to the physical load bus through a power amplifier. The inverter controller uses droop control to inject power in response to frequency and voltage deviations. Experimental results demonstrate that the PHIL platform captures dynamic interactions between virtual and physical components. The paper concludes with practical guidelines and key considerations for the reliable application of PHIL in validating inverter control strategies in small-scale microgrids. Full article

With the increasing penetration of wind power, the participation of wind farms in primary frequency regulation has become important for maintaining power system frequency stability. However, virtual inertia and droop control, while providing frequency support, can increase structural fatigue loads in wind turbines and shorten their service life. To address this issue, this study proposes a coordinated optimization method for wind farm primary frequency control parameters based on fatigue load prediction. First, damage equivalent load (DEL) data under different power disturbances, wind speeds, and control parameter settings are generated through OpenFAST–Simulink co-simulation. Then, a multilayer perceptron (MLP) neural network is developed to establish the mapping from power disturbance, wind speed, and control parameters to turbine DEL. Based on the trained model, an optimization framework is constructed to minimize the total DEL of the wind farm, improve the uniformity of DEL distribution among turbines, and satisfy grid frequency support constraints. Simulation results show that the proposed method effectively reduces the overall fatigue load of the wind farm while ensuring system frequency security and improving load distribution uniformity among turbines. Full article

To address the frequency stability challenges arising from the high penetration of renewable energy, this study proposes a coordinated frequency regulation strategy for wind-power–hydrogen coupled systems, considering the Equivalent State of Charge (ESOC). While wind-power–hydrogen integration offers significant regulation potential, frequent ESOC excursions toward operational limits may lead to power interruptions and increased durability-related stress on hydrogen units. To resolve this, a refined mathematical model comprising wind turbines, electrolyzers, and fuel cells is first established to characterize system dynamics. The proposed method adopts an ESOC-based partitioning control logic: within normal ESOC ranges, the hydrogen storage system provides rapid frequency support via virtual inertia control; when ESOC reaches operational thresholds, the hydrogen unit seamlessly transitions out of service to prolong its lifespan, while the wind turbine dynamically compensates for the power deficit through adaptive droop control. Compared with other methods, the strategy proposed in this paper, implemented via DIgSILENT/PowerFactory simulations, improves the frequency nadir by 0.02 Hz during load increases and reduces the frequency peak by 0.04 Hz during load shedding. Under stochastic disturbances, the absolute steady-state frequency error is maintained below 0.02 Hz, while frequency deviations are strictly confined within ±0.5 Hz. These improvements significantly enhance both grid resilience and the operational safety of hydrogen units. Full article

With the increasing integration of wind power into the grid, power systems are exhibiting characteristics of low inertia and low short-circuit ratio. Virtual synchronous generator (VSG) control technology, which emulates the operational characteristics of synchronous generators, can effectively provide voltage and inertia support to the grid. However, its application in grid-connected permanent magnet synchronous generator (PMSG)-based wind turbines is prone to low-frequency oscillation issues. To address this, this paper first establishes a damping torque model for the grid-forming PMSG. The damping torque method is employed to quantify the damping characteristics of the system in the low-frequency band, while analyzing the influence of various torque components on the system’s damping composition and low-frequency oscillations. Based on this, a machine-side current loop controller incorporating a novel exponential sliding-mode control (NESMC) and a high gain disturbance observer (HGDO) is proposed. This controller aims to reduce the machine-side negative damping effect, thereby effectively suppressing low-frequency oscillations in the system. Finally, a simulation model is built in MATLAB/Simulink to verify the correctness of the damping torque analysis and the effectiveness of the proposed control method. Full article

Medium-voltage (MV) networks are increasingly relying on grid-forming inverter-based resources (IBRs) due to the worldwide transition towards renewable energy sources. This transformation poses considerable challenges for traditional protection schemes that were initially developed for systems powered by inertia-based generation. Key challenges include the low and controlled contributions of fault current, two-way power flows, diminished system inertia, and swiftly changing transient behaviors. These elements weaken the effectiveness of standard protection methods such as overcurrent, distance, and differential protection schemes. A critical review of recent advancements in adaptive protection schemes, impedance-based techniques, virtual synchronous machines, and enhancements in inverter control is provided. However, despite these advancements, current solutions frequently lack validation in real-world scenarios, encounter difficulties in detecting high-impedance faults, and face scalability issues. There remains a demand for protection strategies that are resilient, coordinated, and specifically designed to address the distinct dynamics of MV systems dominated by grid-forming inverters. Full article

With the rapid development of offshore wind power, the fractional frequency offshore wind power system based on the modular multilevel matrix converter (M3C) faces severe frequency stability challenges due to the reduced inertia under high wind power penetration. This paper focuses on its frequency control and proposes a set of coordinated strategies. Modified frequency regulation schemes for wind turbines (WTs) under different operating states avoid secondary frequency drop (SFD) and accelerate rotor speed recovery. A coordinated power allocation strategy combining energy storage (ES) and automatic generation control (AGC) suppresses wind-induced power fluctuations, with a reducing pitch angle variation method to extend WTs’ life. Meanwhile, an adaptive virtual inertia control strategy for M3C enhances sustained inertia support. A coordinated frequency control scheme between wind farm, M3C, and ES is further constructed to achieve faster and better frequency stabilization under wind and load variations. Simulation results under a 10.5 MW load disturbance show that, compared with the uncontrolled scheme, the proposed scheme raises the frequency nadir from 49.01 Hz to 49.67 Hz, limits the maximum rate of change of frequency (ROCOF) to 0.583 Hz/s with a 49.8% reduction, fully eliminates SFD, and provides theoretical support for the stable grid integration of fractional frequency offshore wind power. Full article

The increasing integration of intermittent renewable energy sources (RESs) into islanded Hybrid Power Systems (HPSs) is a critical step towards global energy sustainability; however, it poses significant challenges to frequency stability owing to low system inertia and stochastic power fluctuations. To address these challenges and enable higher penetration of green energy, this study proposes a novel and robust Load Frequency Control (LFC) strategy based on the Crested Porcupine Optimizer (CPO). A customized Mode-Dependent Adaptive Balloon (MDAB) controller is developed, wherein the virtual control gain is dynamically tuned based on the real-time operating modes and disturbance severity. Furthermore, to optimize communication resources and mitigate actuator wear in networked microgrids, an intelligent event-triggered (ET) mechanism is seamlessly integrated into the adaptive logic. The proposed control framework is rigorously validated through comprehensive nonlinear simulations and comparative analyses with state-of-the-art metaheuristic algorithms (GTO, GWO, JAYA, and GO). The evaluation encompasses step load disturbances, severe parametric uncertainties (+25%), realistic 24-h diurnal cycles with solar cloud shading and wind turbulence, and extended practical constraints, including Battery Energy Storage System (BESS) integration and Internet of Things (IoT) communication delays. The results demonstrate the superiority of the CPO-tuned framework, which achieved the fastest transient recovery (settling time of 3.4367 s) and the lowest absolute Integral Absolute Error (IAE). Additionally, the proposed ET-based strategy not only reduced the communication burden but also improved the overall control performance by 37% in terms of IAE compared with continuous approaches. By inherently filtering measurement noise, mitigating control signal chattering, and maintaining resilience under nonideal latency, the proposed architecture offers a highly robust and resource-efficient solution that directly guarantees the operational sustainability and reliability of modern smart microgrids. Full article

With the large-scale integration of wind power, modern power systems are facing reduced equivalent inertia, weakened primary frequency regulation capability, and insufficient coordination between wind turbines and energy storage during joint frequency support. To address these issues, this paper investigates a wind–storage hybrid system composed of doubly fed induction generators (DFIG) and supercapacitor energy storage and proposes a coordinated primary frequency regulation strategy combining fuzzy logic control (FLC) and model predictive control (MPC). Considering the variations in rotor kinetic energy reserve and frequency support capability under different wind speed regions, a coordinated regulation mechanism is developed for multiple operating conditions. In addition, a variable-coefficient synthetic inertia control scheme with rotor speed safety constraints is designed to adaptively adjust the turbine regulation coefficients, while an SOC-feedback-based adaptive virtual droop strategy is introduced to improve the sustained support capability of the energy storage unit. On this basis, a multi-objective model predictive control framework is established to optimize the reference power allocation between the wind turbine and the energy storage unit in a rolling manner. The proposed method is characterized by three coordinated features, namely, multi-region wind–storage frequency regulation, rotor-speed-safe adaptive support of the wind turbine and SOC-aware adaptive support of the storage unit, as well as MPC-based rolling power allocation. Simulation results show that the proposed strategy improves the frequency nadir, reduces the steady-state frequency deviation, and enhances coordinated power sharing, thereby improving the primary frequency regulation performance and overall frequency stability of the wind–storage hybrid system. Full article

Weak-grid operation, with a low short-circuit ratio (SCR), degrades voltage and frequency regulation and impacts the power control performance of inverter-based resources, triggering oscillations. This paper proposes a community-scale battery energy storage system (BESS)-supported grid-forming control scheme, where the grid-forming inverter acts a virtual synchronous generator (VSG). A grid-connected BESS-powered VSG model with cascaded voltage-current dual-loop control is developed to assess the impacts of line impedance and P-Q coupling on weak-grid connection and stability. In addition to the conventional VSG, dq-axis decoupling, virtual impedance, and adaptive inertia-damping (J-D) are incorporated and evaluated through multi-scenario MATLAB/Simulink simulations. The results indicate that virtual impedance effectively suppresses coupled oscillations, and the coordinated J-D adaptation yields the most pronounced peak mitigation during edge disturbances (e.g., fault clearance and load shedding). In particular, under a 50% three-phase voltage sag, the coordinated strategy reduces the post-clearance peaks of $v_{pcc,rms}$ and $i_{pcc,rms}$ by approximately 79.9% and 93.5%, respectively, and decreases the intensity of frequency fluctuations by approximately 97.6%. Overall, the proposed community-scale BESS-VSG scheme enhances the dynamic stability of voltage and frequency under weak-grid conditions and provides a practical control framework for engineering-oriented weak-grid support studies. Full article

To address the instability risk of grid-forming inverters under large power dispatch in low-inertia and low-damping power grids caused by renewable energy integration, based on the grid-forming inverter connected to an infinite bus system model, transient stability under power dispatch is conducted. The power dispatch boundaries constrained by transient stability are analyzed by the inverter’s output power-angle characteristics and the equal area criterion. To enable on-demand power dispatch for the grid-forming inverter, a power ramp scheduling strategy constrained by transient stability is proposed. Furthermore, to overcome the limitations of variable-step ramp scheduling, such as a prolonged transient duration, significant output waveform overshoot, and the need for real-time computation, an improved scheme employing virtual inertia emulation is presented, along with its parameter design methodology for the inertia emulation block. The response time and overshoot can be effectively reduced. Finally, simulations and experiments validate the effectiveness of the proposed equivalent-inertia ramp control scheme in improving system transient stability under power dispatch. Full article

In power systems with a high penetration level of wind power, wind turbines are required to temporarily extract stored rotor kinetic energy to provide primary frequency support, thereby compensating for the limited frequency regulation (FR) capability of the overall system. However, wind turbine participation may lead to underresponse (insufficient frequency support) or overresponse, potentially causing a secondary frequency dip (SFD). Electrolytic aluminum load (EAL), as an industrial load with FR potential, can rapidly adjust its active power input by controlling the electrolytic cell voltage, equivalently increasing the system’s FR capacity and thereby enhancing the load disturbance resistance of power systems with high wind power penetration. This paper first analyzes the causes and mechanisms of the SFD induced by wind turbine overresponse based on a Unified transfer function structure (UTFS) model and introduces the concept of a frequency stability region. Within this region, the virtual droop and virtual inertia coefficients for wind turbines are tuned to prevent SFD during FR. Simultaneously, by involving EAL in system FR, the analysis reveals that its participation essentially equivalently expands the system’s frequency stability region. Building on this analysis and considering spatiotemporal influencing factors, a coordinated wind-aluminum FR control strategy across multiple timescales is proposed to avoid SFD. Finally, a 39-bus simulation system built in DIgSILENT is used for validation. The simulation results indicate that the proposed control strategy effectively suppresses SFD under high wind power penetration conditions, and that the incorporation of EAL significantly expands the frequency stability region of the power system. Full article

This paper reviews recent work on dynamic virtual power plants (DVPPs) using an Energy–Information–Market framework. It addresses the important problem of how DVPPs can support low-inertia power system operation and feeder-level stability under high renewable penetration. First, system-level studies on low-inertia operation and frequency control are used to frame quantitative requirements on rate of change of frequency, nadir, and quasi-steady-state limits. Second, energy-layer models are surveyed, including participation-factor-based DVPP controllers, grid-forming architectures, model-free frequency regulation, and robust frequency-constrained scheduling for allocating virtual inertia and fast frequency response (FFR) across distributed energy resource fleets. Third, information-layer and market-layer models are reviewed, covering stochastic and robust bidding, distribution locational marginal price-based clearing, peer-to-peer and community markets, privacy-preserving coordination, and emerging governance and cybersecurity schemes for DVPP participation. Across these strands, much of the literature remains centred on steady-state active and reactive power dispatch, with dynamic security enforced as constraints rather than formulated as verifiable and tradable services. This review identifies gaps in dynamic metrics and benchmarks, forecasting of available inertia and FFR capacity, market-physics co-design, multi-aggregator interaction, and experimentally validated DVPP implementations. These findings suggest that DVPPs can “sell stability” at the feeder level only through co-designed control, information, and market mechanisms and outline a research roadmap for this purpose. Full article