Search Results (324)

The increasing integration of wind power reduces the equivalent inertia of power systems, leading to lower frequency nadirs and higher rate of change of frequency following disturbances. In Type-4 wind turbine systems, conventional maximum power point tracking (MPPT) may counteract the additional inertial power command during frequency support and cause secondary frequency dips during rotor-speed recovery. To address these issues, this paper proposes a virtual-inertia rate-of-change-of-frequency (VI-RoCoF) frequency-modulated Andronov-Hopf oscillator (AHO)-based adaptive inertia enhancement method together with an adaptive MPPT coordination strategy. The proposed method constructs a frequency-support demand from frequency deviation and VI-filtered RoCoF and embeds it into the instantaneous angular-frequency evolution of the AHO. Different from a conventional linear virtual-inertia controller that directly converts frequency-deviation and RoCoF signals into an algebraic power command, the proposed method realizes the additional support through a bounded limit-cycle frequency-forming process, thereby preserving phase continuity and nonlinear amplitude self-regulation during frequency modulation. Meanwhile, the adaptive MPPT strategy adjusts the power reference in stages to suppress the counteractive effect of conventional MPPT on inertial support and to ensure a smooth transition back to maximum power point tracking. Theoretical analysis shows that the proposed modulation maintains the limit-cycle stability of the AHO under bounded control constraints while improving the equivalent inertia and damping characteristics of the system. Simulation results, including both averaged-model and switching-level SPS simulations, demonstrate that, compared with conventional AHO-based, fixed-inertia AHO-based, and linear VI-RoCoF benchmark schemes without AHO dynamics, the proposed AHO-MPPT coordinated control strategy increases the frequency nadir, reduces the peak RoCoF, improves recovery-stage frequency dynamics, mitigates secondary frequency dips, maintains bounded AHO internal variables, and preserves DC-link voltage stability. Full article

Against the background of the dual carbon goals and the high proportion of distributed energy access, the distribution network presents the characteristics of source–network–load–storage two-way interaction. Traditional centralized control struggles to cope with voltage fluctuation, new-energy consumption difficulties and control dimension explosion. This paper focuses on the study of flexible resource aggregation modeling and cloud-side collaborative control, constructs the control constraint model of distributed Photovoltaic, energy storage, electric vehicle and flexible load constraints, proposes a resource aggregation method based on weight-improved K-means clustering, and includes voltage sensitivity to achieve accurate evaluation of adjustable capacity. A cloud–edge–end three-level collaborative control framework is built, and a two-layer scheduling model is established with the goal of peak shaving and valley filling so as to realize global optimization and local rapid response. The simulation results based on the improved IEEE 33-node distribution network show that the proposed method can effectively cluster flexible resources and quantify the adjustable potential. The cloud–edge coordination strategy can effectively reduce the load peak–valley difference, improve new-energy consumption rate and voltage stability, and provide a feasible technical path for the efficient regulation of the active distribution network. Full article

This paper introduces the Improved Runge–Kutta algorithm (IRUN), an enhanced optimization framework that addresses the limitations of the standard RUN method. By integrating success-history adaptation, an external archive, and linear population reduction, IRUN achieves a more effective exploration–exploitation balance, leading to faster and more stable convergence. Evaluations on twenty-three unimodal, multimodal, and composite benchmark functions confirm that IRUN consistently outperforms RUN, achieving markedly lower median errors, narrower interquartile ranges, and more reliable convergence trajectories. In a real-world 136-bus distribution system, IRUN reduces active and reactive power losses by 1.6%, lowers maximum and daily utility energy consumption by 5.9% and 2.5%, and produces smoother, more coordinated charging behavior for distributed BESS units. Voltage-quality indicators—including minimum/maximum voltages and total voltage deviation—demonstrate improved regulation and enhanced system stability, while convergence time is reduced by 16.3%, reinforcing IRUN’s suitability for real-time operational environments. Overall, the combined benchmark and distribution-system results establish IRUN as a robust, accurate, and computationally efficient optimization strategy for next-generation smart distribution networks. Full article

An increase in penetration of photovoltaic (PV) systems in a distribution system causes voltage regulation issues that create serious problems for the On-Load Tap Changer (OLTC) of the power transformer, leading to higher tap-changing frequency and reduced transformer life. Traditional voltage control methods are ineffective when PV penetration exceeds load demand, and more sophisticated control methods are needed. This paper combines a systematic literature review conducted in accordance with the PRISMA 2020 guidelines with a case study on operational issues of OLTC transformers under both normal and non-normal operating conditions. It entails a detailed examination of the effect of PV integration on the operating characteristics of OLTC in a systematic approach and also dwells upon coordination processes between OLTC and Flexible AC Transmission Systems (FACTS) devices, such as Distribution Static Synchronous Compensator (D-STATCOM) or Static VAR Compensator (SVC), which are highly effective in reducing tap operations. The future directions covered in the review include the operation of hybrid systems, cost-effective implementations, weather effects, predictive analytics, adaptive control techniques, etc. The case study included online monitoring of OLTC performance in two scenarios at the cement factory. First, under supply changes and load changes. Second, including PV penetration. The results show that OLTC increases the average daily tapping frequency (90 taps/day) by about 60%, with full PV penetration. It is concluded that this can’t be applied without coordinated control among OLTC, D-STATCOM, and PV inverters to maintain transformer life, improve reliability, and provide stable voltage profiles even under highly variable PV generation conditions. These results aim to provide a comprehensive resource for academics and practitioners, facilitating the advancement of advanced voltage control methods to support the transition to sustainable energy systems. Full article

Rural distribution networks increasingly face voltage quality challenges due to high penetration of distributed renewable energy, heterogeneous rural load behavior, and long radial feeder structures with limited voltage regulation capability. Photovoltaic generation variability and agricultural load fluctuations can lead to voltage rise, reverse power flow, and branch congestion, particularly in weak rural grids. Conventional deterministic voltage control approaches relying on tap changers and capacitor banks often struggle to maintain stable voltage profiles under stochastic operating conditions. This paper proposes a risk-aware coordinated operation framework for rural multi-energy microgrids that integrates stochastic scenario modeling, voltage state perception, and adaptive optimization-based control. Renewable generation uncertainty and rural load variability are represented through correlated scenario generation and Wasserstein-distance-based scenario reduction, where 100 raw joint photovoltaic-load trajectories are reduced to 20 representative scenarios after convergence and distributional-fidelity tests. A stochastic optimization model is developed to coordinate photovoltaic inverters, battery energy storage systems, demand-side flexibility, and reactive compensation devices while satisfying network power-flow, voltage-security, storage, and communication-delay-aware implementation constraints. To mitigate extreme voltage deviation events, the framework incorporates a Conditional Value-at-Risk formulation that penalizes tail-risk voltage violations and maintains voltages within a preferred operating band of $0.97$–$1.03$ p.u. Case studies on a modified IEEE 33-bus rural distribution system with $2.00$ MW of photovoltaic capacity and $2.50$ MWh of battery storage demonstrate consistent performance improvements across deterministic, risk-neutral stochastic, chance-constrained, and robust baselines. The proposed strategy reduces peak branch loading from $0.95$ in the deterministic benchmark to $0.72$, while the $95\mathrm{th}$ percentile voltage deviation risk decreases from $0.0071$ p.u.${}^2$ to $0.0020$ p.u.${}^2$. Sensitivity, scenario-convergence, scalability, and seasonal representative-day analyses further confirm that the CVaR layer suppresses rare but severe voltage excursions without imposing excessive curtailment or computational burden. Full article

Aiming at the problems of the severe active–reactive power coupling, insufficient adaptive inertia–damping regulation, and degraded dynamic performance of virtual synchronous generators (VSGs) under the operating conditions of a weak grid, high resistance-to-reactance ratio, and large power angle, this paper proposes a cooperative control strategy that combines reactive power feedforward decoupling with adaptive damping–inertia regulation. First, a small-signal power model of the VSG is established, and a dynamic relative gain array is employed to quantitatively analyze the effects of the resistance-to-reactance ratio and power angle on power coupling characteristics, revealing that large power angles and high resistance-to-reactance ratios significantly aggravate active–reactive power coupling. Based on this analysis, a reactive-power-oriented feedforward decoupling strategy is designed to suppress the cross-coupling between reactive power and power angle while preserving the intrinsic inertia support characteristics of the active power loop. Eigenvalue migration analysis further demonstrates that the proposed reactive-power-oriented decoupling provides higher damping ratios and larger stability margins than conventional full active–reactive power decoupling. Furthermore, a deep deterministic policy gradient-based adaptive damping–inertia control method is developed by incorporating frequency deviation, power fluctuation, voltage deviation, and coupling degree into the state space, enabling the online coordinated optimization of virtual inertia and damping coefficients. The hardware-in-the-loop experimental results verify that the proposed strategy effectively suppresses active–reactive power coupling, reduces power overshoot and oscillation, enhances frequency support capability and dynamic response speed, and maintains superior stability under weak grid conditions. Sensitivity analysis under grid impedance estimation errors further confirms its strong robustness against parameter uncertainty, while tests under composite disturbance scenarios demonstrate excellent transient performance. The proposed strategy provides an effective solution for improving the grid-connected operation performance and adaptability of VSGs in low-inertia power systems. Full article

Hydro-dominant distribution grids with high penetrations of distributed photovoltaic (PV) generation exhibit a clear operational asymmetry. PV output changes rapidly at the minute scale, whereas hydropower regulation is constrained by reservoir water balance, turbine ramping capability, and hydraulic safety limits. During high-inflow periods, mandatory hydropower generation further reduces the downward regulation margin and restricts midday PV accommodation. To address this issue, this paper develops an asymmetry-aware adaptive bi-level planning framework for photovoltaic hosting capacity (PVHC) assessment. A db4 discrete wavelet transform is used to decompose PV output into low-frequency energy trends and high-frequency fluctuation components. The upper layer performs hourly economic dispatch while maintaining reservoir water balance, and the lower layer conducts minute-level constrained tracking under ramping and vibration-zone avoidance constraints. A bisection-type capacity-search procedure is then used to identify the PVHC boundary by jointly checking curtailment, ramping, frequency proxy, voltage, line-loading, point-of-common-coupling exchange, and vibration-zone residence constraints. Case studies based on a 15 min PV dataset from a 30 MW station, hydropower operation records, and a modified 15-node feeder in Southwest China show that hydrological asymmetry materially affects PV accommodation. The obtained PVHC ranges from 53.17 MW under the most restrictive high-proxy condition to 65.33 MW under low-proxy operation. Compared with the no-coordination case, representative-month PVHC increases from 49.80 MW to 65.33 MW, while the simulated residence time within the predefined vibration-prone zone decreases from 447 min to 0 min. These results indicate that PVHC evaluation in hydro-dominant feeders should jointly consider electrical constraints, hydrological asymmetry, and hydraulic safety limits. Full article

With global demand for renewable energy increasing, the penetration of photovoltaic (PV) systems in power networks has risen significantly, introducing new challenges to microgrid stability. This study focuses on solar inverters using grid-forming (GFM) control, investigating their performance in black-start scenarios and in stabilizing microgrids with battery energy storage systems (BESSs). A MATLAB Simulink microgrid model integrating PV, BESS, and GFM inverters was developed to simulate scenarios including black start, load variation, grid synchronization, and power adjustment. Control techniques such as droop control, proportional–integral (PI) control, Clarke and Park transformations, and phase-locked loops (PLLs) were applied for precise regulation of voltage, frequency, and power. Results show that GFM inverters effectively stabilize voltage and frequency during load changes and PV grid connection, maintaining voltage between 0.96–1.003 p.u. and frequency within 59.87–60.07 Hz. The findings confirm the feasibility of GFM control for coordinated PV–BESS operation and support stable microgrid operation under high renewable penetration. Full article

The integration of photovoltaic (PV) generation with alkaline water electrolyzers (AWE) in DC microgrids offers a highly promising pathway for green hydrogen production. However, the inherent volatility of solar power often induces transient voltage ripples and power surges, degrading the electrolyzer stack and destabilizing the common DC bus. To overcome this, this study proposes a hierarchical multimodal coordinated control strategy tailored for a four-port (PV–Storage–Grid–Hydrogen) DC microgrid. The proposed framework leverages multi-port synergetic coordination among the PV array, battery storage, and grid-interfacing converters to actively buffer extreme power mismatches, thereby ensuring the constant regulation of the DC bus voltage. Through comprehensive time-domain simulations under worst-case step-change boundary conditions, the large-signal transient stability of the proposed strategy is quantitatively verified. Under extreme disturbances, the system successfully confines DC bus voltage deviations to within safe operational boundaries with a rapid settling time, effectively avoiding typical inverter overvoltage trip thresholds. Furthermore, the adaptive power regulation algorithm maintains precise steady-state power tracking. By utilizing a gradient-based flag variable, the system seamlessly transitions between maximum power point tracking (MPPT) and active power-limiting modes, ensuring continuous equipment protection, stable high-purity hydrogen yield, and uninterrupted microgrid stability. Full article

In the context of the new power system, modular multilevel converter high-voltage direct current (MMC-HVDC) has become a key technical solution for the large-scale grid integration of wind power. However, when a fault occurs in the AC grid at the system receiving end, the high-voltage direct current (HVDC) system faces challenges such as wind power redundancy, DC overvoltage, and equipment overcurrent. To address this, this paper proposes an energy storage-coordinated fault ride-through (FRT) control strategy suitable for different fault scenarios. The strategy optimizes the allocation of energy storage capacity according to the state of charge (SOC) of the energy storage units (ESUs), preventing individual ESUs from prematurely shutting down and reducing energy dissipation. Finally, a comparison with a conventional DC dissipation resistor scheme on the PSCAD/EMTDC platform demonstrates that the proposed strategy provides smoother power regulation characteristics and smaller DC voltage fluctuations, thereby enhancing the economic efficiency and reliability of system operation. Full article

The large-scale integration of distributed photovoltaics (DPVs) into the distribution network exacerbates voltage fluctuations and substantially increases network losses. To improve the voltage quality and economic efficiency of distribution networks, a Volt/Var optimization (VVO) model is established. Coordinating multiple heterogeneous devices, the model aims to minimize the total voltage deviation, the total network losses, and the regulation cost of discrete equipment simultaneously. Considering multi-constraint coupling characteristics, a quantitative method is proposed to evaluate the reactive power regulation potential of DPVs under intricate operating conditions. Then, the multi-strategy integrated rime optimization algorithm (MSIRIME) is utilized for the model solution. Fuch chaotic mapping generates uniformly distributed and ergodic initial populations. A dual-branch search mechanism combining the snow ablation optimizer with the rime optimization significantly enhances global exploration capabilities. The guided learning strategy balances exploration and exploitation for high-dimensional VVO, preventing local optima. Case tests on a modified IEEE 33-bus system demonstrate that the proposed model exhibits excellent effectiveness and robustness. Moreover, MSIRIME exhibits better optimization performance than some classic and recently proposed strategies, reducing the average network losses and voltage deviation over 30 independent runs by at least 5.87% and 52.22%, respectively, relative to those of the compared methods. Full article

The increasing penetration of distributed generation (DG) in distribution systems poses significant operational challenges, including increased power losses, voltage profile deviations, and variations in short-circuit currents. These issues may compromise network safety, reliability, and the selectivity of protection schemes under different operating scenarios. This paper proposes a hybrid optimization methodology for the optimal placement and sizing of DG, aiming to minimize active power losses while ensuring voltage regulation and keeping short-circuit currents within permissible limits. An integrated approach is proposed that combines a mesh-to-radial network reconfiguration strategy with a modified Ant Lion Optimization algorithm, known as ALO-DG, enabling the simultaneous optimization of network topology and the allocation of distributed generators at candidate buses. The problem is formulated taking into account power balance constraints, voltage limits, distribution network capacity limits, and short-circuit current limits. The proposed methodology achieved substantial reductions in active power losses in the IEEE 33-bus and 69-bus test systems, reaching 84.42% and 91.56%, respectively. These improvements were accompanied by enhanced voltage profiles while preserving the radial operating structure of the distribution networks. Furthermore, the proposed hybrid methodology serves as a tool for the planning and operation of distribution systems with high DG penetration, particularly in scenarios where grid security and protection coordination are critical considerations. Full article

The increasing penetration of renewable energy sources and converter-interfaced loads has intensified the need for fast and reliable grid-support services. Although electric vehicle (EV) battery chargers have emerged as promising resources for Vehicle-to-Grid (V2G) applications, existing solutions typically focus on individual services such as virtual inertia or frequency regulation, while limited attention has been given to the coordinated provision of multiple ancillary services within a unified framework. Furthermore, the use of batteries alone for fast frequency support may accelerate battery degradation due to frequent high-power transients. To address these challenges, this paper proposes a hybrid energy storage-based EV battery charger architecture and a coordinated multi-timescale control strategy capable of simultaneously providing virtual inertia support, long-term frequency regulation, reactive power compensation, and harmonic mitigation. The proposed approach utilizes a DC-link capacitor to deliver fast inertial response while the battery supplies sustained frequency support, thereby reducing battery stress and improving energy management efficiency. An enhanced frequency estimation method based on a phase-locked loop combined with a low-pass filter is also introduced to improve dynamic performance. Simulation results demonstrate the effectiveness of the proposed strategy under various grid disturbances. The system achieves an equivalent virtual inertia constant of approximately 1.85 s and delivers up to 786 W of transient inertial support within 80 ms during frequency events. The enhanced frequency estimation method significantly reduces transient overshoot, while harmonic compensation limits the grid current and voltage total harmonic distortion to 1.50% and 3.23%, respectively. In addition, the controller provides up to 400 VAR of reactive power support during voltage disturbances while maintaining stable battery operation. These results demonstrate that the proposed EV battery charger can function as a multifunctional grid-support resource, enhancing frequency stability, voltage regulation, power quality, and overall V2G capability in future smart grids. Full article

With the integration of high-penetration distributed renewable energy sources and grid-forming inverters, AC microgrids face significant challenges in maintaining autonomous voltage and frequency stability. While traditional droop control can achieve autonomous power allocation, it introduces inherent steady-state deviations when load change. To address this, this paper proposes a distributed secondary control strategy for AC microgrids based on a consensus algorithm, aiming to achieve high-precision coordinated correction of voltage and frequency and improve power quality. In the proposed strategy, each grid-forming inverter autonomously generates dynamic secondary compensation signals based solely on local measurements and limited information exchange with neighboring nodes, eliminating the need for a central controller and enhancing robustness, scalability, and fault tolerance. Stability is proven via Lyapunov function construction. Simulation results show that the strategy effectively eliminates steady-state errors, with frequency deviations within ±0.01 Hz and voltage deviations below 0.5% of the rated value. Rapid and precise regulation is achieved under various load disturbances and network conditions, validating its effectiveness and application potential. Full article

Portable industrial X-ray flaw detectors operating in outdoor environments predominantly rely on small diesel generators for power supply. However, the inherent grid frequency drift of such weak grids induces critical phase-shift mismatches in conventional fixed-delay controllers, leading to voltage loss-of-control. This study aims to develop a robust, frequency-adaptive power drive system to overcome these operational challenges. A dynamic zero-crossing capture mechanism is proposed to extract real-time grid frequency variations, enabling instantaneous phase-shift feedforward compensation. This mechanism is integrated with an adaptive incremental proportional–integral–derivative (PID) controller that utilizes grid-condition recognition to dynamically schedule gains and neutralize frequency disturbances. Furthermore, a linear voltage soft-start strategy is incorporated to coordinate downstream constant-current regulation, preventing inrush currents. Concurrently, an offline downtime perception mechanism executes autonomous stepped-voltage conditioning to prevent cold high-voltage breakdowns. Simulation and hardware experimental results demonstrate that under continuous generator frequency drift, the adaptive control maintains a steady-state voltage error below 1%, suppresses the voltage ripple factor to 1.11%, and limits tube current fluctuations to 4.2%. The proposed system effectively mitigates weak-grid instability, ensuring reliable high-voltage generation and extending component lifespan for demanding non-destructive testing (NDT) applications. Full article