Search Results (265)

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

As an innovative solution, the virtual synchronous generator (VSG) facilitates the seamless incorporation of renewable energy into power grids. It also exhibits the ability to reconfigure system inertia and deliver damping effects, thereby assuming a progressively vital role in contemporary power systems. Three-phase voltage imbalance, a common phenomenon in power grids, causes current distortion. Imbalance, a common phenomenon in power grids, causes current distortion in VSG outputs, thereby affecting power quality. Therefore, ensuring symmetrical current injection into the grid has become a critical challenge in grid-connected technology. To resolve this challenge, a dual-module VSG control scheme is introduced, enabling precise regulation of the VSG’s power delivery. This approach effectively distinguishes and separately manages the positive-sequence and negative-sequence power outputs of the VSG. Furthermore, virtual impedance and quasi-PR control are incorporated into the current control loop to achieve zero negative-sequence power output from VSG, ensuring a stable power supply. Simulation results validate the reliability of this approach, providing both a theoretical foundation and practical evidence for its future application. Full article

In areas such as remote, rural, and mountainous regions, supplying low-voltage three-phase power has traditionally required distribution line extension and transformer installation. However, these areas often yield low electricity revenues, making cost recovery difficult for utilities. To address this challenge, this paper proposes a Single-to-Three-Phase Converter (STPC) capable of converting single-phase low-voltage input into three-phase output for use in low-voltage distribution systems. The STPC topology employs a single-phase half-bridge AC–DC stage and a three-phase full-bridge inverter stage using SiC-MOSFETs. To validate the system, simulations and experiments were conducted under various load conditions, including unbalanced, nonlinear, and motor loads. The results show that STPC maintains output stability while minimizing impact on the existing grid. The findings demonstrate STPC’s feasibility as an alternative to conventional line extension and transformer installation, with potential for application in grid-forming and low-voltage distribution current (LVDC) systems. Full article

This paper presents a comprehensive study on the formulation and solution of the power flow problem in bipolar direct current (DC) distribution networks with unbalanced constant power loads. Using the nodal voltage method, a unified nonlinear model is proposed which accurately captures both monopolar and bipolar load configurations as well as the voltage coupling between conductors. The model assumes a solid grounding of the neutral conductor and known system parameters, ensuring reproducibility and physical consistency. Seven iterative algorithms are developed and compared, including three Newton–Raphson-based formulations and four quasi-Newton methods with constant Jacobian approximations. The proposed techniques are validated on two benchmark networks comprising 21 and 85 buses. Numerical results demonstrate that Newton-based methods exhibit quadratic convergence and high accuracy, while quasi-Newton approaches significantly reduce computational time, making them more suitable for large-scale systems. The findings highlight the trade-offs between convergence speed and computational efficiency, and they provide valuable insights for the planning and operation of modern bipolar DC grids. Full article

In order to improve the ability to suppress unbalanced voltage in bipolar DC microgrids, a comprehensive power regulation control of a novel shared energy storage system is proposed for a multi-scenario bipolar DC microgrid. The novel shared energy storage system is composed of an electric spring (ES) with a full-bridge DC/DC converter and non-critical load (NCL) in series, considering demand-side response. The proposed comprehensive power regulation control can enable the bipolar DC microgrid to deal with various scenarios. When operating in stand-alone mode, the unbalanced voltage caused by greater unbalanced power can still be suppressed under the proposed control of the shared energy storage. In case of distributed energy storage (DES) failure on the source side, the shared energy storage can realize DC voltage regulation and maintain system operation by reducing NCL power. In grid-connected operation, the shared energy storage can actively cooperate with the power dispatching of the utility grid for storage reduction of DES on the source side. Thus, the reliability and resilience of the bipolar microgrid have been improved. Finally, to verify the effectiveness of the proposed control strategy, hardware-in-the-loop experimental results are presented in this paper. Full article

This paper presents Enhanced Voltage Sensorless Control for PWM converter with DSOGI-FLL under grid disturbances. Even without grid voltage sensors, the proposed method accurately estimates the grid angle and voltage, which are necessary for power transfer between the DC link of the PWM converter and the grid. The estimated grid voltage obtained through observer design is separated into positive and negative sequence components, and the grid frequency is estimated using the Dual Second-Order Generalized Integrator Quadrature Signal Generator (DSOGI-QSG) and Dual Second-Order Generalized Integrator Frequency-Locked Loop (DSOGI-FLL). The estimated positive and negative sequence voltages were effectively controlled using a dual current controller. The method operates effectively under normal, balanced AC source conditions and in various grid fault scenarios, including unbalanced voltage, harmonic distortion, voltage sag, and frequency step changes. The validity of the proposed method was evaluated through experimental results by using a grid simulator to implement the fault condition. Full article

The charging station (CS) is generally directly off-grid under a grid fault, which has become a key technical bottleneck that restricts the sustainable development of new energy transportation systems. During a grid fault, the CS under the vehicle-to-grid (V2G) mode experiences a reduction in active power due to the current limitation of the voltage source converter (VSC), which may cause the DC voltage to exceed its limitations under unbalanced power. The effect of the active and reactive power of CS in low- and medium-voltage distribution networks on supporting the PCC voltage under the limitation of DC voltage and VSC current has not been analyzed, and a control method for PCC voltage support for CS has not been established. Therefore, a power boundary that avoids the DC overvoltage and AC overcurrent of the CS is defined. A power feasible region for the CS considering fault duration is established. The characteristic that the power feasible region shrinks with the increase in duration is found, and a calculation method for the critical clearing time of a fault to avoid DC overvoltage is proposed. The relationship between PCC voltage and power injected by the CS is analyzed. The property that the control point of maximum voltage support lies at the boundary of the power feasible region is revealed. A control method of PCC voltage support that considers the limitation of DC voltage and VSC current for the CS is proposed. Simulation verification shows that the support capability of CS for PCC voltage during a fault is significantly enhanced by the proposed method while securing the DC voltage. Full article

Grid-connected inverter (GCI) plays a crucial role in facilitating stable and efficient power delivery, especially under severe and complex grid conditions. Harmonic distortions and imbalance of the grid voltages may degrade the grid-injected current quality. Moreover, inductive-capacitance (LC) grid impedance and the grid frequency fluctuation also degrade the current control performance or stability. In order to overcome such an issue, this study presents a frequency-adaptive current control strategy of a GCI based on incomplete state observation under severe grid conditions. When LC grid impedance exists, it introduces additional states in a GCI system model. However, since the state for the grid inductance current is unmeasurable, it yields a limitation in the state feedback control design. To overcome such a limitation, this study adopts a state feedback control approach based on incomplete state observation by designing the controller only with the available states. The proposed control strategy incorporates feedback controllers with ten states, an integral controller, and resonant controllers for the robustness of the inverter operation. To reduce the reliance on additional sensing devices, a discrete-time full-state current observer is utilized. Particularly, with the aim of avoiding the grid frequency dependency of the system model, as well as the complex online discretization process, observer design is developed in the stationary reference frame. Additionally, a moving average filter (MAF)-based phase-locked loop (PLL) is incorporated for accurate frequency detection against distortions of grid voltages. For evaluating the performance of the designed control strategy, simulations and experiments are executed with severe grid conditions, including grid frequency changes, unbalanced grid voltage, harmonic distortion, and LC grid impedance. Full article

The integration of Distributed Energy Resources (DERs) into power grids presents significant challenges to grid performance, requiring innovative solutions for effective operation. Dynamic Operating Envelopes (DOEs) offer a promising approach by optimizing the use of existing infrastructure while ensuring compliance with network constraints. This paper reviews various DOE calculation methodologies, focusing on Optimal Power Flow (OPF)-based methods. Key findings include the role of DOEs in optimizing import and export limits, with critical factors such as forecast accuracy, network modelling, and the effects of mutual phase coupling in unbalanced networks identified as influencing DOE performance. The paper also explores the integration of DOEs into smart grid frameworks, examining both centralized and decentralized control strategies, as well as their potential for providing ancillary services. Challenges in scaling DOEs are also discussed, particularly regarding the need for accurate forecasts, computational resources, communication infrastructure, and balancing efficiency and fairness in resource allocation. Lastly, future research directions are proposed, focusing on the practical application of DOEs to improve grid performance and support network operations, as well as the development of more robust DOE calculation methodologies. This review provides a comprehensive overview of current DOE research and identifies avenues for further exploration and advancement. Full article

In view of the challenges brought by a complex environment, diverse data sources and urban development needs, our study comprehensively reviews the application of algorithms in urban residential vacancy rate observation. First, we explore the definition and measurement of urban residential vacancy rate, pointing out the difficulties in accurately defining vacant houses and obtaining reliable data. Then, we introduce various algorithms such as traditional statistical learning, machine learning, deep learning and ensemble learning, and analyze their applications in vacancy rate observation. The traditional statistical learning algorithm builds a prediction model based on historical data mining and analysis, which has certain advantages in dealing with linear problems and regular data. However, facing the high nonlinear relationships and complexity of the data in the urban residential vacancy rate observation, its prediction accuracy is difficult to meet the actual needs. With their powerful nonlinear modeling ability, machine learning algorithms have significant advantages in capturing the nonlinear relationships of data. However, they require high data quality and are prone to overfitting phenomenon. Deep learning algorithms can automatically learn feature representation, perform well in processing large amounts of high-dimensional and complex data, and can effectively deal with the challenges brought by various data sources, but the training process is complex and the computational cost is high. The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. By comparing these algorithms, we can clarify the advantages and adaptability of different algorithms in different scenarios. Facing the complex environment, the data in the observation of urban residential vacancy rate are affected by many factors. The unbalanced urban development leads to significant differences in residential vacancy rates in different areas. Spatiotemporal heterogeneity means that vacancy rates vary in different geographical locations and over time. The complexity of data affected by various factors means that the vacancy rate is jointly affected by macroeconomic factors, policy regulatory factors, market supply and demand factors and individual resident factors. These factors are intertwined, increasing the complexity of data and the difficulty of analysis. In view of the diversity of data sources, we discuss multi-source data fusion technology, which aims to integrate different data sources to improve the accuracy of vacancy rate observation. The diversity of data sources, including geographic information system (GIS) (Geographic Information System) data, remote sensing images, statistics data, social media data and urban grid management data, requires integration in format, scale, precision and spatiotemporal resolution through data preprocessing, standardization and normalization. The multi-source data fusion algorithm should not only have the ability of intelligent feature extraction and related analysis, but also deal with the uncertainty and redundancy of data to adapt to the dynamic needs of urban development. We also elaborate on the optimization methods of algorithms for different data sources. Through this study, we find that algorithms play a vital role in improving the accuracy of vacancy rate observation and enhancing the understanding of urban housing conditions. Algorithms can handle complex spatial data, integrate diverse data sources, and explore the social and economic factors behind vacancy rates. In the future, we will continue to deepen the application of algorithms in data processing, model building and decision support, and strive to provide smarter and more accurate solutions for urban housing management and sustainable development. Full article

With the evolution of modern power systems, the proportion of renewable energy generation in the grid continues to grow. At the same time, grid operation modes have become increasingly complex and dynamic, leading to heightened uncertainty in disturbance faults. Moreover, power electronic equipment exhibits relatively low-level immunity to disturbances. The issue of frequency stability in power systems is becoming increasingly severe. These factors make the pre-programmed control strategies based on strategy tables, which are widely used as the second line of defense for frequency stability in power systems, prone to mismatches. When a power disturbance occurs, it is crucial to adopt an appropriate emergency load-shedding strategy based on the characteristics of unbalanced power distribution and the network’s frequency profile. In this paper, for a simplified multi-zone equivalent system, the coupling relationship between different load-shedding locations and the system’s frequency response after a disturbance is analyzed. This analysis integrates the power distribution characteristics after the disturbance, a system frequency response (SFR) model, and the frequency distribution law in the network. It is demonstrated that under identical load-shedding amounts and action times, implementing load shedding closer in electrical distance to the disturbance location is more beneficial for stabilizing system frequency. A convolutional neural network (CNN) is employed to localize system faults, and combined with research on the emergency load-shedding amounts based on SFR model parameter identification, a rapid disturbance location-based emergency load-shedding strategy is proposed. This strategy enables prompt and accurate load-shedding actions to enhance the security and stability of the power system. Finally, the effectiveness of the proposed approach is validated using the CEPRI-LF standard arithmetic system. Full article

The Virtual Synchronous Generator (VSG) control strategy has garnered widespread application during the low-voltage ride-through (LVRT) of distributed energy resources integrated into power grids, primarily due to its inertia and damping properties. However, grid voltage dips frequently coincide with unbalanced conditions and harmonic disturbances, against which traditional VSG LVRT control strategies offer limited resilience, resulting in unbalanced and unstable grid-connected currents. Consequently, this impacts the VSG’s support for voltage at the point of common coupling (PCC) during LVRT, potentially leading to control system failure. To tackle this challenge, this paper introduces a VSG LVRT control strategy tailored for complex grid faults. Initially, a mathematical model is developed to analyze the impact on the VSG control system’s grid-connected current when the PCC voltage of the LC filter experiences harmonic-laden unbalanced dips. Subsequently, the traditional dual second-order generalized integrator phase-locked loop (DSOGI-PLL) is enhanced to bolster its filtering capabilities. Additionally, PCC voltage feedforward control is incorporated, with a meticulously derived feedforward function to counteract the disturbances caused by unbalanced grid voltage dips, thereby enhancing the VSG system’s anti-interference ability and stabilizing the grid-connected current. This enables effective VSG LVRT control in the face of complex grid faults and ensures successful LVRT of the grid-connected system. Ultimately, the efficacy of the proposed control strategy is confirmed through PSCAD simulations. Full article

This article introduces a frequency-adaptive control strategy for a three-phase shunt active power filter, aimed at improving energy efficiency and ensuring high power quality in consumer-oriented power systems. The proposed control system utilizes real-time frequency estimation to dynamically adjust the gain of a proportional-integral–resonant (PIR) controller, facilitating precise harmonic compensation under challenging unbalanced grid conditions, such as unbalanced three-phase loads, grid impedance variations, and diverse nonlinear loads like three-phase rectifiers and induction motors. These scenarios often increase total harmonic distortion (THD) at the point of common coupling (PCC), degrading the performance of connected loads and reducing the efficiency of induction motors. The PIR controller integrates both proportional-integral (PI) and proportional-resonant (PR) control features, achieving improved stability and reduced overshoot. A novel voltage sensorless control method is proposed, requiring only current measurements to determine reference currents for the inverter, thereby simplifying the implementation. Validation of the frequency adaptive control scheme through MATLAB/Simulink simulations and real-time experiments on a dSPACE (DS1202) platform demonstrates significant improvements in harmonic compensation, energy efficiency, and system stability across varying grid frequencies. This approach offers a robust consumer-oriented solution for managing power quality, positioning the SAPF as a key technology for advancing sustainable energy management in smart applications. Full article