Search Results (244)

The rapid integration of solar power into distribution grids has intensified challenges related to frequency instability caused by fluctuating renewable generation. These unexpected frequency variations are difficult to capture using traditional or supervised methods because they emerge from nonlinear, rapidly changing inverter grid interactions and often lack labelled examples. To address this, the present work introduces a unique, frequency-centric framework for unsupervised detection and root cause analysis of grid anomalies using high-resolution micro-Phasor Measurement Unit ($\mu$PMU) data. Unlike previous studies that focus primarily on voltage phasors or rely on predefined event labels, this work employs SpectralNet, a deep spectral clustering approach, integrated with autoencoder-based feature learning to model the nonlinear interactions between frequency, ROCOF, voltage, and current. These methods are particularly effective for unexpected frequency variations because they learn intrinsic, hidden structures directly from the data and can group abnormal frequency behavior without prior knowledge of event types. The proposed model autonomously identifies distinct root causes such as unbalanced loads, phase-specific faults, and phase imbalances behind hazardous frequency deviations. Experimental validation on a real solar-integrated distribution feeder in the UK demonstrates that the framework achieves superior cluster compactness and interpretability compared to traditional methods like K-Means, GMM, and Fuzzy C-Means. The findings highlight SpectralNet’s capability to uncover subtle, nonlinear patterns in $\mu$PMU data, offering an adaptive, data-driven tool for enhancing grid stability and situational awareness in renewable-rich power systems. Full article

This paper presents a novel multi-loop control strategy for Vienna rectifiers that eliminates coordinate transformations while achieving superior performance under adverse grid conditions. Unlike conventional $dq$-frame controllers that suffer from computational complexity and degraded performance during unbalanced conditions, the proposed $abc$-frame scheme achieves a power factor of $98\%$ with total harmonic distortion (THD) below $5\%$ across all operating conditions. The system exhibits a settling time under 120 μs for $90\%$ load transients and ensures robust operation during Type A voltage sags while maintaining a $94\%$ power factor. Furthermore, it guarantees zero steady-state neutral point deviation. The controller employs a dual-loop architecture with high-gain current tracking and PI-based voltage regulation, validated through extensive PSIM/C++ co-simulations at 120 kw. Comparative analysis demonstrates a $35\%$ reduction in computational burden relative to $dq$-frame alternatives, while fully complying with IEEE-519:2022 standards. These results highlight the proposed method as a practical and robust solution for industrial rectification applications requiring grid-fault tolerance. Full article

Under unbalanced grid conditions, the three-phase Vienna rectifier exhibits significant voltage fluctuations in dc-link and asymmetric input currents. Traditional control methods cannot simultaneously suppress the voltage ripples in dc-link and balance the input currents. Therefore, a weighted control strategy based on the degree of current imbalance is proposed in this paper. The strategy is implemented within a dual closed-loop architecture, featuring a finite-set model predictive control (FS-MPC) method in the current loop and a sliding mode control (SMC) method in the voltage loop. In the current loop, the two control objectives of voltage in dc-link and input current are weighted, and the weighting factor is dynamically adjusted based on the degree of current imbalance. This strategy can simultaneously achieve control for input current symmetry and dc-link voltage balance under unbalanced grid conditions. Finally, a 2 kW Vienna rectifier experimental platform was independently constructed. Simulation and experimental results indicate that under unbalanced grid conditions, the proposed control strategy achieves approximately 10% lower total harmonic distortion (THD) and maintains DC-link voltage fluctuation within 5 V, compared to traditional control methods. Full article

The ongoing decarbonisation of power systems is displacing synchronous generators (SGs) with converter-based plants, requiring a consistent assessment of grid-following inverters (GFLIs) and grid-forming inverters (GFMIs). Using an openly available four-bus root-mean-square (RMS) benchmark modelled in DIgSILENT PowerFactory, this work compares three generation configurations: (i) a single local SG connected at the point of common coupling; (ii) the same generator combined with a GFLI; and (iii) the generator combined with a GFMI. These configurations are evaluated under three disturbance scenarios: (1) a balanced load step, (2) an unbalanced double line-to-ground fault at low short-circuit ratio (SCR) with temporary islanding and single-shot auto-reclose, and (3) full islanding with under-frequency load shedding (UFLS), partial resynchronisation, and staged restoration. For the tested tuning ranges and within this RMS benchmark, the grid-forming configuration behaves as a low-impedance source at the point of common coupling in the phasor sense, yielding higher frequency nadirs during active-power disturbances and faster positive-sequence voltage recovery under weak and unbalanced conditions than the SG-only and SG+GFLI cases. During islanding, it supports selective UFLS, secure resynchronisation, and orderly load restoration. Rather than introducing new control theory, this work contributes a reproducible RMS benchmarking framework that integrates low-SCR operation, unbalance, and restoration sequences with a documented cross-technology tuning procedure. The findings indicate system-level improvements in frequency resilience and voltage recovery for the tested benchmark relative to the alternative configurations, while recognising that instantaneous device-level effects and broader generality will require electromagnetic-transient (EMT) or hybrid EMT/RMS validation in future work. Full article

The safe and stable operation of ultra-high-voltage (UHV) transmission lines is fundamental to ensuring efficient and large-capacity power delivery. Critical fittings, as essential load-bearing components connecting towers, conductors, and insulator strings, are highly susceptible to damage under complex ice–wind conditions, thereby posing significant threats to grid security. To address the prevalent issues of jumper spacer breakage and conductor abrasion observed in field maintenance, a systematic finite element analysis model incorporating bundled conductors, jumper structures, and associated fittings was established. This model enabled comprehensive investigation of the effects of non-uniform ice accretion, wind loading, and ice-shedding impacts on the bearing characteristics of critical fittings. Through high-throughput computational simulations, a large-scale dataset capturing the bearing characteristics of jumper spacers was constructed. Based on this dataset, a damage risk assessment model under complex ice–wind conditions was developed using a multi-layer feedforward deep neural network (MLF-DNN). The results indicated that wind loading had a relatively minor influence on jumper spacers, whereas ice accretion and ice-shedding impacts were the dominant factors leading to damage. In particular, non-uniform ice-shedding readily induced unbalanced forces among sub-conductors, significantly increasing stress levels in jumper spacers and resulting in substantial risk. The proposed risk assessment model demonstrated high predictive accuracy and strong generalization capability, providing effective support for rapid evaluation and early warning of damage to fittings in UHV transmission lines under complex ice–wind environments. Full article

If unplanned off-grid events occur in microgrids, stable operation is disrupted. In particular, dynamic unbalanced loads, power pulse, and voltage changes also lead to system instability. To overcome these issues, this paper develops a smooth droop control strategy for multi-functional inverters. By introducing a QPR (quasi-proportional resonant) controller, the load voltage regulator is designed to compensate for the harmonic and unbalanced voltages of microgrids. Compared with traditional strategies, the proposed multi-functional inverter can reduce voltage pulses by more than 60%, and the off-grid voltage THD (total harmonic distortion) is decreased from 7% to less than 3%. At the same time, dynamic unbalanced loads and non-linear dynamic loads are both considered, and the derived strategy achieves smoother grid-connected and off-grid switching. In grid-connected mode (the microgrid connects to the distribution network at the PCC), the peak voltages and overshoots across transitions are definitely decreased, and continuous monitoring shows that the grid’s current THD stays steadily below 3%. This meets compatibility requirements, avoids harmonic interference on distribution networks, and follows the core principle of IEC TS 62898-1:2023. The simulation and experimental results verify the effectiveness of the proposed multi-function inverter control strategy for grid-connected inverters. Full article

This paper presents the validation of a voltage balancing converter for a bipolar DC microgrid designed to ensure reliable operation in both grid-connected and islanded modes. This microgrid includes unipolar constant power loads (CPL), a unipolar Battery Energy Storage System (BESS), and local PV generation. The BESS converter employs a V–I droop strategy using only inductor current feedback, reducing sensing requirements while maintaining plug-and-play capability and ensuring smooth transitions between connected and islanded modes. In such a microgrid, the voltage balancing converter regulates the differential voltages under severe unbalanced load conditions and during transients caused by changes in unipolar loads and sources. The experimental results validate the voltage balancing strategy across various scenarios in a small-scale prototype. The results show tight voltage regulation under unbalanced conditions, and smooth transitions during load transients and unintentional islanding, even if there is no dc voltage source in one of the poles of the bipolar dc bus. For both conditions, the imbalance between the unipolar voltages is less than 0.5% of the total bipolar voltage. Full article

This paper presents an optimized control strategy based on a Doubly Fed Induction Generator (DFIG) and Gravity Energy Storage System (GESS) for AC voltage support in unbalanced grid conditions. The presented control aims to achieve precise rotational speed control, voltage stabilization, and harmonic component suppression. The optimization strategy responds to voltage and frequency fluctuations in an unbalanced grid. Based on Grid-Forming (GFM) control, it adjusts the DFIG’s operating state in real time. This ensures stable voltage support and mitigates harmonic distortion caused by the unbalanced grid. Simulation results, under a weak grid (SCR = 3) and unbalanced (0.9 p.u. voltage sag) conditions, validate the strategy, which reduces rotor current THD from 12.57% to 1.71% and maintains precise speed tracking during a 0.8 p.u. to 0.7 p.u. load change. The results demonstrate that the presented control method effectively improves grid power quality. It also enhances system stability and reliability. This approach provides strong support for integrating renewable energy into unbalanced grids. Full article

Under overmodulation conditions, the capacitor voltages of half-bridge and full-bridge submodules in hybrid modular multilevel converters (MMCs) may become unbalanced. This imbalance not only gives rise to overvoltage stress on submodule capacitors, jeopardizing equipment safety, but also degrades power quality and may even trigger operational instability. To address this issue, this paper proposes a minimum second harmonic circulating current injection method based on Bayesian Adaptive Direct Search (BADS) within the overall framework of model predictive control for MMCs. The method efficiently solves complex objective functions by alternately performing local Bayesian optimization and global grid search. Optimal second harmonic injection values under different modulation indices are obtained through offline computation and curve fitting. This approach achieves dynamic capacitor voltage balancing across a wide modulation range while minimizing operational losses caused by harmonic currents. Full article

Peer-to-peer (P2P) energy trading has emerged as a novel approach to enhancing the coordination and utilization of distributed energy resources (DERs) within modern power distribution networks. This study presents a techno-economic analysis of different DER characteristics, focusing on the integration of photovoltaic (PV) systems and energy storage systems (ESS) within a community-based P2P energy trading framework in Aswan, Egypt, under a time-of-use (ToU) electricity tariff. Eight distinct cases are evaluated to assess the impact of different DER characteristics on P2P energy trading performance and an unbalanced low-voltage (LV) distribution network by varying the PV capacity, ESS capacity, and ESS charging power. To the best of the authors’ knowledge, this is the first study to comprehensively examine the effects of different DER characteristics on P2P energy trading and the associated impacts on an unbalanced distribution network. The findings demonstrate that integrating PV and ESS can substantially reduce operational costs—by 37.19% to 68.22% across the analyzed cases—while enabling more effective energy exchanges among peers and with the distribution system operator (DSO). Moreover, DER integration reduced grid energy imports by 30.09% to 63.21% and improved self-sufficiency, with 30.10% to 63.21% of energy demand covered by community DERs. However, the analysis also reveals that specific DER characteristics—particularly those with low PV capacity (1.5 kWp) and high ESS charging rates (e.g., ESS 13.5 kWh with 2.5 kW inverter)—can significantly increase transformer and line loading, reaching up to 19.90% and 58.91%, respectively, in Case 2. These setups also lead to voltage quality issues, such as increased voltage unbalance factors (VUFs), peaking at 1.261%, and notable phase voltage deviations, with the minimum Vb dropping to 0.972 pu and maximum Vb reaching 1.083 pu. These findings highlight the importance of optimal DER sizing and characteristics to balance economic benefits with technical constraints in P2P energy trading frameworks. Full article

The paper proposes a parallel transformerless (TL) static synchronous series compensator (SSSC) for the control of power flow along the power distribution lines under balanced or unbalanced voltages. This new SSSC configuration offers the advantages of a fast dynamic response, light weight, and high efficiency. By connecting multiple SSSCs in parallel, the current rating is increased, which improves the grid power transfer capabilities and flexibility. However, there may be circulating current flowing between the parallel-connected inverters, hence causing losses. A modified model predictive control scheme is thus developed, which ensures that the proposed SSSC accurately tracks the reference currents while effectively mitigating the circulating current. The model and cost function of the controller are derived and analyzed in the paper. A real-time simulation of a power line with the parallel TL SSSC controlled by a hardware-in-loop (HIL) DSP is developed to validate the performance of this device under both balanced and unbalanced line voltages. Full article

The rapid evolution of modern power systems, driven by the large-scale integration of renewable energy sources and the emergence of smart grids, presents new challenges in maintaining grid stability, power quality, and control reliability. As critical interfacing elements, three-phase pulse width modulation (PWM) converters must now ensure resilient and efficient operation under increasingly adverse and dynamic grid conditions. This paper proposes an adaptive neural network-based virtual flux (VF) estimator for sensorless predictive direct power control (PDPC) of PWM converters under nonideal grid voltage conditions. The proposed estimator is realized using an adaptive linear neuron (ADALINE) configured as a quadrature signal generator, offering robustness against grid voltage disturbances such as voltage unbalance, DC offset and harmonic distortion. In parallel, a PDPC scheme based on the extended pq theory is developed to reject active-power oscillations and to maintain near-sinusoidal grid currents under unbalanced conditions. The resulting VF-based PDPC (VF-PDPC) strategy is validated via real-time simulations on the OPAL-RT platform. Comparative analysis confirms that the ADALINE-based estimator surpasses conventional VF estimation techniques. Moreover, the VF-PDPC achieves superior performance over conventional PDPC and extended pq theory-based PDPC strategies, both of which rely on physical voltage sensors, confirming its robustness and effectiveness under non-ideal grid conditions. Full article

This work proposes an effective control technique for enhancing the stability of Doubly Fed Induction Generator-Based Wind Turbines (DFIG-WTs) connected to the grid during voltage sag and swell events, ensuring the reliable and efficient operation of wind energy systems integrated with the grid. The proposed approach integrates a Dynamic Voltage Restorer (DVR) in series with a Wind Turbine Generator (WTG) output terminal to enhance the Fault Ride-Through (FRT) capability during grid disturbances. To develop a flexible control strategy for both unbalanced and balanced fault conditions, a combination of feedforward and feedback control based on a sliding mode control (SMC) for DVR converters is used. This hybrid strategy allows for precise voltage regulation, enabling the series compensator to inject the required voltage into the grid, thereby ensuring constant generator terminal voltages even during faults. The SMC enhances the system’s robustness by providing fast, reliable regulation of the injected voltage, effectively mitigating the impact of grid disturbances. To further enhance system performance, Model Predictive Control (MPC) is implemented for the Rotor-Side Converter (RSC) within the back-to-back converter (BTBC) configuration. The main advantages of the predictive control method include eliminating the need for linear controllers, coordinate transformations, or modulators for the converter. Additionally, it ensures the stable operation of the generator even under severe operating conditions, enhancing system robustness and dynamic response. To validate the proposed control strategy, a comprehensive simulation is conducted using a 2 MW DFIG-WT connected to a 120 kV grid. The simulation results demonstrate that the proposed control approach successfully limits overcurrent in the RSC, maintains electromagnetic torque and DC-link voltage within their rated values, and dynamically regulates reactive power to mitigate voltage sags and swells. This allows the WTG to continue operating at its nominal capacity, fully complying with the strict requirements of modern grid codes and ensuring reliable grid integration. Full article

With the increasing penetration of distributed generation and the diversification of electrical equipment, distribution networks face issues like three-phase unbalance and harmonic currents, while the voltage stability and inertia of the grid-connected system also decrease. A certain amount of energy storage is needed in a Distribution Static Synchronous Compensator (DSTATCOM) to manage power quality and actively support voltage and inertia in the network. This paper first addresses the limitations of traditional $dq0$ compensation algorithms in effectively filtering out negative-sequence twice-frequency components. An improved $dq0$ compensation algorithm is proposed to reduce errors in detecting positive-sequence fundamental current under unbalanced three-phase conditions. Second, considering the impedance ratio characteristics of the distribution network, while reactive power voltage regulation is common, active power regulation is more effective in high-resistance distribution networks. A grid-forming model-based active and reactive power coordinated voltage regulation method is proposed. This method uses synchronous control to establish a virtual three-phase voltage internal electromotive force, forming a comprehensive compensation strategy that combines power quality improvement and active voltage support, exploring the potential of energy storage DSTATCOM applications in distribution networks. Finally, simulation and experimental results demonstrate the effectiveness of the proposed control method. Full article

The rapid adoption of electric vehicles (EVs) and the increasing use of photovoltaic (PV) generation have introduced new operational challenges for unbalanced power distribution systems. These include elevated power losses, voltage imbalances, and adverse environmental impacts. This study proposed a hybrid objective optimization framework to address these issues by minimizing real and reactive power losses, voltage deviations, voltage imbalance indexes, and CO₂ emissions. Nineteen simulation cases were analyzed under various configurations incorporating EV integration, PV deployment, reactive power compensation, and zonal control strategies. An improved gray wolf optimizer (IGWO) was employed to determine optimal placements and control settings. Among all cases, Case 16 yielded the lowest objective function value, representing the most effective trade-off between technical performance, voltage stability, and sustainability. The optimized configuration significantly improved the voltage balance, reduced system losses, and maintained the average voltage within acceptable limits. Additionally, all optimized scenarios achieved meaningful reductions in CO₂ emissions compared to the base case. The results were validated with an objective function $\left(F_{best}\right)$ as a reliable composite performance index and demonstrated the effectiveness of coordinated zone-based optimization. This approach provides practical insights for future smart grid planning under dynamic, renewable, rich, and EV-dominated operating conditions. Full article