Xu Zhang

With the advancement of China’s “dual carbon” targets, Desert–Gobi–Wilderness (DGW) regions have become strategic areas for large-scale renewable energy deployment. However, the intermittency and variability of wind and solar resources pose challenges to power system stability, necessitating systematic evaluation of their characteristics and complementarity. This study uses ERA5 reanalysis data (2013–2023) to assess wind and solar resources in the Badain Jaran and Kumtag Deserts. A multi-dimensional framework is developed, incorporating availability, intermittency, variability, and complementarity, and a GIS-based multi-criteria decision-making method is applied for site selection. Results show that the Badain Jaran Desert is characterised by strong wind resources (average wind power density: 235.16 W/m²) and is suitable for wind-dominated development, whereas the Kumtag Desert exhibits superior solar resources (221.08 W/m²), favouring photovoltaic deployment. Significant wind–solar complementarity is identified, particularly in the central-western Badain Jaran and northeastern Kumtag regions. Three high-suitability sites were identified, including two in the Badain Jaran Desert and one in the Kumtag Desert, all characterised by favourable topographic conditions and high engineering feasibility. This study provides a scientific basis and a methodological framework for the planning of wind–solar hybrid systems and coordinated ecological development in DGW regions.

As wind power penetration continues to increase, the sub-synchronous control interaction (SSCI) problem caused by the interaction between doubly fed induction generators (DFIGs) and series-compensated transmission lines has become increasingly prominent, posing a serious threat to power system stability. To address this problem, this research proposes a centralized sub-synchronous oscillation damping controller (CSODC) for wind farms. First, a DFIG impedance model was constructed based on multi-operating-point impedance scanning and a Taylor series expansion, achieving impedance prediction with an error of less than 2% under various power conditions. Subsequently, a CSODC comprising a sub-synchronous damping calculator (SSDC) and a power electronic converter is designed. By optimizing feedback signals, phase shift angles, gain parameters, and filter parameters, dynamic adjustment of controllable impedance in the sub-synchronous frequency band is achieved. Frequency-domain impedance analysis demonstrates that the CSODC significantly enhances the system’s equivalent resistance, reversing it from negative to positive at the resonance frequency point. Time-domain simulations validated the CSODC’s effectiveness in scenarios involving series capacitor switching and wind speed disturbances, demonstrating rapid sub-synchronous current decay. The results confirm that the proposed strategy effectively suppresses sub-synchronous oscillations across multiple scenarios, offering an economical and efficient solution to stability challenges in high-penetration renewable energy grids.

To meet the demands of deep grid integration of renewable energy and long-distance power transmission, this paper presents a hybrid multi-infeed DC system architecture that includes an AC power source (AC), a voltage source converter (VSC), and a modular multilevel converter (MMC). Addressing the limitations of traditional differential protection—such as insufficient sensitivity under high-resistance grounding and susceptibility to false operations under out-of-zone disturbances—this paper introduces an enhanced current differential criterion based on dynamic phasor analysis. By effectively decoupling DC bias and load current components and optimizing the calculation of action and braking quantities, the proposed method enables the rapid and accurate identification of typical faults, including high-resistance grounding, three-phase short circuits, and out-of-zone faults. A multi-scenario simulation platform is built using MATLAB to thoroughly validate the improved criterion. Simulation results demonstrate that the proposed method offers excellent sensitivity, selectivity, and resistance to false operations in multi-infeed complex systems. It achieves fast fault detection (~2.0 ms), strong sensitivity to high-resistance internal faults, and low false tripping under a variety of test scenarios, providing robust support for next-generation DC protection systems.

The large-scale integration of wind power, photovoltaic systems, and energy storage systems (ESSs) into power grids has increasingly influenced the transient stability of power systems due to their dynamic response characteristics. Considering the commercial confidentiality of core control parameters from equipment manufacturers, parameter identification has become a crucial approach for analyzing ESS dynamic behaviors during high-voltage ride-through (HVRT) and low-voltage ride-through (LVRT) and for optimizing control strategies. In this study, we present a multidimensional feature-integrated parameter identification framework for ESSs, combining a multi-scenario voltage disturbance testing environment built on a real-time laboratory platform with field-measured data and enhanced optimization algorithms. Focusing on the control characteristics of energy storage converters, a non-intrusive identification method for grid-connected control parameters is proposed based on dynamic trajectory feature extraction and a hybrid optimization algorithm that integrates an improved particle swarm optimization (PSO) algorithm with gradient-based coordination. The results demonstrate that the proposed approach effectively captures the dynamic coupling mechanisms of ESSs under dual-mode operation (charging and discharging) and voltage fluctuations. By relying on measured data for parameter inversion, the method circumvents the limitations posed by commercial confidentiality, providing a novel technical pathway to enhance the fault ride-through (FRT) performance of energy storage systems (ESSs). In addition, the developed simulation verification framework serves as a valuable tool for security analysis in power systems with high renewable energy penetration.

Focusing on the common problems of phase-locked loop dependence, multiple current sensor requirements, a large number of controllers, and complex settings in traditional parallel active power filter (APF) control methods, this paper proposes a harmonic compensation control strategy based on an improved proportional resonant (PR) controller. The proposed method introduces an instantaneous power theory to construct a reference current model, which relies solely on grid voltage and current signals, does not require load-side current detection and phase-locked loop modules, and effectively simplifies the sensor configuration and system structure. At the same time, compared with the traditional solution that requires PR modules to be configured for each order of harmonics, this study only uses one set of PR controllers for fundamental current tracking, which has advantages in terms of compactness and computing resource occupation. To guide the controller parameter setting, this paper systematically discusses the influence of changes in K_p and K_r on pole distribution and dynamic performance based on discrete domain modeling and root locus analysis methods. The results were verified on the MATLAB/Simulink simulation platform and the 1 kVA experimental platform and compared with the traditional control method that requires the use of phase-locked loops (PLLs), load current sensors, and multiple PR controllers. The simulation and experimental results show that the proposed method has achieved a certain degree of optimization in terms of harmonic suppression effect, dynamic response performance, and system structure complexity.

At present, the equivalent modeling method of wind farms mostly adopts single-machine multiplication equivalence, which has the deficiencies of large model error and difficulty in accurately reflecting the fault transient characteristics of wind farms, which imposes limitations on the security and stability analysis of the power system. For this reason, this paper proposes an equivalent modeling method that can accurately reflect the fault ride-through characteristics of wind farms. Based on the control mechanism of direct-drive wind turbines, this method first analyzes the fault ride-through operating characteristics of wind turbines and establishes a single-machine fault transient model; then, taking the fault ride-through control characteristics of wind turbines as the criteria for subgroups, it calculates the relevant parameters of the group through weighted aggregation and QPSO algorithm, and constructs the fault transient equivalent model of each group; finally, combining with the principle of loss conservation, it integrates and obtains the fault transient equivalent model of the whole wind power field. Finally, the equivalent fault transient model of the whole wind farm is obtained by combining the loss conservation principle. Simulation verification shows that the established equivalent model can accurately reflect the dynamic characteristics of the wind farm, and the maximum percentage error of voltage and active power is no more than 10% in comparison with the corresponding detailed model under the same kind of fault perturbation, which not only meets the requirements of China’s wind farm modeling standards, but also shows higher adaptability and accuracy under different working conditions compared with other equivalent modeling methods. Especially under the extreme three-phase zero-passage fault condition, the maximum error of voltage and active power does not exceed 2%, which provides a reliable basic tool for the safety and stability analysis of wind farms.

The sub-synchronous oscillation accident of large-scale doubly fed wind turbines connected to a grid through series compensation has caused a serious impact on the power system. By optimizing the parameters of the doubly fed wind turbines control system, the system impedance can be effectively improved to solve the problem of sub-synchronous oscillation. However, owing to the complexity of a grid-connected system of doubly fed generators connected to wind turbines and the influence of the time-varying oscillation characteristics of the system, it is often difficult to achieve a successful suppression. To solve this problem, this paper proposes an optimized additional damping method for the rotor- and grid-side controllers, which can achieve efficient suppression of the sub-synchronous oscillation. The parameters of the proposed additional damping method are optimized for all variable operation conditions using a genetic algorithm under the established frequency–domain impedance model. The detailed time–domain simulation model was constructed with the RTLAB platform to verify the proposed method. The experimental results show that the optimized control strategy can effectively and quickly suppress the sub-synchronous oscillation under different operating conditions, and the amplitude suppression rate reached 85.99%, which effectively improved the grid-connected stability of the wind turbines.

The sub-synchronous oscillation accident of large-scale doubly fed wind turbines connected to a grid through series compensation has caused a serious impact on the power system. By optimizing the parameters of the doubly fed fan control system, the system impedance can be effectively improved to solve the problem of sub-synchronous oscillation. However, owing to the complexity of a grid-connected system of doubly fed fans and the influence of the time-varying oscillation characteristics of the system, it is often difficult to achieve a successful suppression. To solve this problem, this paper proposes an optimized additional damping method for the rotor and grid-side controllers, which can achieve efficient suppression of sub-synchronous oscillation. The parameters of the proposed additional damping method are optimized for all variable operation conditions using a genetic algorithm under the established frequency-domain impedance model. The detailed time-domain simulation model was constructed with the RTLAB platform to verify the proposed method. The experimental results show that the optimized control strategy can effectively and quickly suppress the sub-synchronous oscillation under different working conditions, and the amplitude suppression rate reached 85.99%, which effectively improved the grid-connected stability of wind turbines.