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Despite decades of intensive effort, the current solutions for efficiently searching high-dimensional data spaces are not entirely satisfactory. This paper proposes a more efficient global low-density locality sensitive hashing search algorithm (GLDH) based on the minimal cut hyperplane and ensemble learning. The innovation is that a novel global low-density hyperplane candidate set is constructed by the graph cut method, the minimum information gain method and random maximum entropy method are used to greedily select the hyperplane, and the ensemble learning method is used to query the global approximate nearest-neighbors data. This paper proves that the GLDH algorithm produces a low error hyperplane partition. The results of extensive experiments show that the proposed GLDH method performs better than the latest methods when using the same hash coding length for datasets from different fields.

In targeting the most important energy and environmental issues in current society, the development of low-cost, bifunctional electrocatalysts for urea-assisted electrocatalytic hydrogen (H2) production is an urgent and challenging task. In this work, interlaced rosette-like MoS2/Ni3S2/NiFe-layered double hydroxide/nickel foam (LDH/NF) is successfully synthesized by a two-step hydrothermal reaction. Due to its unique interlaced heterostructure, MoS2/Ni3S2/NiFe-LDH/NF exhibits excellent bifunctional catalytic activity towards the urea oxidation reaction (UOR) and the hydrogen evolution reaction (HER) in 1.0 M KOH with 0.5 M urea. In a concurrent two-electrode electrolyser (MoS2/Ni3S2/NiFe-LDH/NF(+,-)), only voltage of 1.343 V is required to reach 50 mA cm−2, which is 216 mV lower than for pure water splitting. Furthermore, after 16 h of urea electrolysis in 1.0 M KOH with 0.5 M urea, the current density remains at 98% of the original value. Thus, the catalyst is not only favorable for H2 production, but also has great significance for the problem of urea-rich wastewater treatment.

To reach a closed-loop material system and meet the urgent requirement of sustainable energy storage technologies, it is essential to incorporate efficient waste management into designing new energy storage materials. Here, a “two birds with one stone” strategy to transform rusty iron products into Prussian blue as high-performance cathode materials, and recover the rusty iron products to their original status, is reported. Owing to the high crystalline and Na+ content, the rusty iron derived Prussian blue shows a high specific capacity of 145 mAh g−1 and excellent cycling stability over 3500 cycles. Through the in situ X-ray diffraction and in situ Raman spectra, it is found that the impressive ion storage capability and stability are strongly related to the suppressed structure distortion during the charge/discharge process. The ion migration mechanism and the possibility to serve as a universal host for other kinds of ions are further illuminated by density functional theory calculations. This work provides a new strategy for recycling wasted materials into high value-added materials for sustainable battery systems, and is adaptable in the nanomedicine, catalysis, sensors, and gas storage applications.

With the increasing penetration of renewables, the modern power system is facing emerging stability issues. A prime example of such issues is the subsynchronous oscillation (SSO) phenomenon observed in large-scale wind farms. It has been studied that hydrogen production equipment (HPE) has the potential to smooth the fluctuation in generated power. However, it is still unclear whether the HPE can be used to mitigate dynamic stability problems induced by wind generators. This study is aimed at filling the gap by exploring the capability of HPE to damp the emerging SSO. Firstly, the overall configuration of an MW-scale HPE is presented. Then its electromagnetic transient model is established for system dynamics studies. Next, a supplementary subsynchronous damping control (SSDC) of HPE is proposed to modulate its power absorption at the subsynchronous frequency, which can improve system damping and stabilise SSO. Finally, the effectiveness of the proposed SSO mitigation strategy is verified on the simulation model of a practical wind power system that suffered actual SSO incidents. The results demonstrated that the HPE with properly designed SSDC, along with suitable capacity and location, can efficiently mitigate the SSO, thus offers a new option to improve the dynamic stability of renewable power systems.

Recently, emerging oscillation issues have been caused by subsynchronous interaction (SSI) between voltage source converters (VSCs) based renewable generators and ac/dc grids. To investigate the dynamics of SSI, several impedance models (IMs) of VSC have been developed in previous studies. They are established in different reference frames and consider the entire or just parts of the control systems. However, it is still an unanswered question whether or not the existing IMs are suitable for SSI analysis and to what extent the IMs with different modeling details affect subsynchronous dynamics. To fill in this gap, this paper, first, reviews the existing IMs of VSC and clarifies their relationship. Then, their frequency characteristics are examined so as to select the proper models for the studies of sub-/supersynchronous and high-frequency dynamics. Next, both zero-pole and IM-based SSI analyses are carried out on a simplified system and a real-world wind-farm system that suffered actual SSI incidents. The results indicate that the outer-loop control has a significant impact on the subsynchronous dynamics, and only those IMs taking full-scale controls and frequency-coupling effects into account can reflect SSI accurately. Finally, both modal analysis and electromagnetic transient simulations have been conducted to verify the theoretical results.

Recently, emerging sub-synchronous oscillation (SSO) issues caused by the interaction between power electronic converters and weak AC grids have provoked serious stability concerns. Impedance-based modelling approaches have been widely employed for stability analysis of such interactions. In this study, a sequence-domain frequency-coupled impedance model (FCIM) and the corresponding stability criterion are proposed. First, a fast identification method of the FCIM is proposed, in which the impedance-frequency curves of the FCIMs at multiple frequencies are measured, followed by identification of their transfer function models. Next, the proposed method is applied to model a practical system, where a SSO event once occurred due to the interactions between direct-drive wind turbines and a weak AC grid. The individual FCIMs of wind turbine generators, steam turbine generators and static var generator in this system are derived. After that, an aggregated FCIM is formed by combining the FCIMs without extra coordinate transformation. Then, the aggregated FCIM-based stability analysis is carried out to investigate the interaction between the wind farms and weak AC grids. In the end, the results of FCIM-based stability analysis are verified by time-domain simulations.

Wireless multimedia sensor networks (WMSNs) have been widely used in environmental monitoring, intelligent transportation, and other scenarios; however, their data have high-dimensional, large-scale, and multitype properties, as well as other characteristics. It is technically difficult to construct an appropriate index structure and query strategy while we perform a highly accurate search. This paper proposes a novel locality-sensitive hashing (LSH) fast Johnson–Lindenstrauss transform (FJLT)-fly locality-sensitive hashing (FLSH) algorithm for WMSN Internet of Things search. In this method, the projection method of FJLT and the winner-takes-all feature selection strategy in the fruity FLSH are considered. The method provides a new solution for the nearest neighbor search of high-dimensional data. We also discuss the distance-keeping property of our algorithm, and prove theoretically that the method proposed in this paper has better distance keeping performance than the traditional dimensionality reduction method. The experimental results show that the proposed algorithm has better generalization, accuracy of the search results, and time efficiency when using the Drosophila olfactory nerve to simulate the LSH process. This method effectively solves the problem of the approximate neighbor query of high-dimensional big data and can be effectively applied to search application on WMSN system.

The increasing penetration of renewables into modern power systems is bringing new oscillatory stability concerns. It is of significance to find all oscillatory modes concerned and evaluate components’ participation into each mode, especially the dominant one. To address this issue, a frequency-domain modal analysis method is developed in this paper. It represents the target system with a networked impedance model and works out the oscillatory modes by locating the zeros of the determinant of the loop impedance matrix or nodal admittance matrix. Loop/nodal participation factors, branch observability, and component sensitivity are derived to give insight into the oscillation, including its origin, oscillation path, and contributive components. The proposed method has been conducted on a simple passive circuit and a practical wind power system that experienced actual subsynchronous resonance incidents. Theoretical results as well as electromagnetic transient simulations have verified its effectiveness. The proposed method has the potential to analyze very large power systems with high penetration of renewables.

With the increasing penetration of renewable power generation (RPG) in modern power systems, subsynchronous oscillation (SSO) induced by the interaction between RPG and the grid is posing a great threat to the system stability and equipment safety. To address this issue, this paper proposes a wide-area monitoring and early-warning system of SSO. It incorporates the locally deployed subsynchronous phasor measurement units (S-PMUs) and a centralized data center & subsynchronous dynamics analyzer (DC&SDA). Several key functions have been developed, including: (1) the subsynchronous state estimation (SSE) to form global view or observability of SSO dynamics, (2) the establishment of subsynchronous power & current flow to locate oscillation source/path, and (3) the real-time evaluation of subsynchronous stability using two complementary criteria, one based on the identification of oscillation damping and the other based on the frequency characteristics of the impedance models. The practicality and performance of the proposed system have been demonstrated with electromagnetic transient (EMT) simulations on a practical system that suffered SSO incidents.

The existing phasor-measurement unit (PMU) and wide-area measurement system (WAMS) based on the fundamental synchrophasors are insufficient to accurately capture the dynamics of sub/super-synchronous resonance or oscillation (SSR/SSO). To address this issue, this study proposes a new method for the simultaneous and precise measurement of the fundamental and multiple sub/super-synchronous harmonic phasors. It improves the classic discrete Fourier transform (DFT)-based method by adding adaptive frequency detection, modal filtration and phasor correction and compensation. Thus, in the context of SSR/SSO, the phasors of both fundamental and interharmonic components can be precisely obtained at local PMUs and the control/data centre of WAMS. The basic procedures and the prototype implementation of the method have been elaborated, and the performance has been examined with simulation signals as well as the field data recorded from an actual SSO incident. The results have verified its high precision, noise immunity and fast response.

Recent years have witnessed emerging oscillatory stability issues in power systems with high-penetration renewables. These issues are generally caused by the dynamic interaction between the AC/DC grid and power electronic converters used for the integration of renewables. Some previous studies have explored the issues with simplified system models containing only a few converters and idealized networks. However, the interactions between many converters and traditional generators/HVDCs have not been fully considered. To fill this gap, this paper first presents the concept of a unified dq frame impedance network model (INM), with which different converters as well as traditional generators/HVDCs can be incorporated to form an integrated s -domain model of a practical system. As the INM is aggregated into a lumped impedance matrix, a new criterion is then proposed to quantify the oscillatory stability, just by analyzing the frequency characteristics of the determinant of the matrix. Finally, the modeling method and the stability criterion are applied to a real-world system with a very high share of renewables and a realistic risk of oscillatory instability. Their effectiveness has been validated by both field measurements and electromagnetic transient simulations.

Recently, an emerging subsynchronous resonance (SSR) issue was observed in series-compensated systems comprising multiple wind farms. However, only simplified single-machine-infinite-bus system models were adopted to investigate the characteristics of this issue in the previous work. As a result, it is unable to reflect the impact on SSR from some critical factors, such as the network topology, the spatial distribution of wind farms, the diversity of wind turbine generators, and the distributed wind speed. To fill in this gap, this paper proposes an impedance network model (INM) based SSR stability analysis method. The impedance models of each wind farm and transmission line are established, and then interconnected according to system topology to form the whole INM. Such INM is further aggregated into lumped impedance. By analyzing the impedance-frequency features of the latter, a new stability criterion is developed to quantify the stability of SSR. The application of the criterion is demonstrated on a practical power system containing multiple wind farms. Both field measurements and time-domain simulations have been presented to validate its effectiveness and accuracy. The proposed method is of great potential in analyzing the SSR issue for very large-scale wind power systems.

The wind speed of high uncertainty has an important impact on the emerging subsynchronous resonance (SSR) caused by the interaction between doubly-fed induction generator (DFIG)-based wind farms and series-compensated transmissions. This paper proposes a piecewise probabilistic collocation method (PPCM) for assessing the probabilistic stability of SSR in terms of the random wind speed. The PPCM can tackle the inherent nonlinearity resulting from the switching among different operational modes of DFIG. Using the proposed PPCM, the more accurate probability density function (PDF) of the damping can be obtained with a small computation burden. Furthermore, for the probabilistic stability assessment of SSR, this paper also develops the Weibull probabilistic model of the wind speed using the two-year statistical data. The results obtained with the proposed method show consistence with those of the Monte Carlo method (MCM). Finally, field data of SSR events in the practical wind farms are also presented to validate the effectiveness of the proposed method and its produced results.

Recently, emerging sub-/super-synchronous oscillation (SSO) issues occurred in large-scale wind power systems, which are caused by the interactions between the power electronic converter based wind turbine generators (WTGs) and the ac/dc grids. In previous studies, the practical system is usually simplified to equivalent system models, which consist of a (several) large-capacity WTGs connected to a radial equivalent line. However, such equivalent models can hardly represent the dynamics of the practical large-scale wind systems. Besides, the impacts on SSO characteristics from such important factors as network topology, steam turbine generators, and high-voltage direct currents have not been clarified yet. To deal with these challenges, this paper proposes a systematic impedance network modeling and quantitative stability analysis method. All system components of the large-scale wind systems are represented with impedance models (IMs) in a unified reference frame, and then, they are interconnected based on the system topology to form the impedance network model (INM) of the whole system. With the INM reduced to an aggregated IM, a stability criterion is developed to assess SSO stability just by analyzing the frequency characteristics of the determinant of the aggregated IM, and a quantitative analysis method is proposed to quantify the damping, frequency, and sensitivity of the SSO mode. The electromagnetic transient simulations on a practical wind system, which suffered actual SSO issues, have validated the effectiveness and accuracy of the proposed method. This paper also conducts comparative analysis on four types of popular stability analysis methods to show the advantages of the proposed method.

Recently, sustained power oscillation at subsynchronous frequency was captured in direct-drive permanent magnetic synchronous generator (PMSG) based wind farms in Xinjiang Uygur Autonomous Region, China. This new type of subsynchronous interaction (SSI) detected in practical systems has never been reported and analyzed before. Therefore, its mechanism and characteristics are not yet clearly clarified. In this paper, a simplified but representative system model with multiple PMSGs interfaced with AC networks is established first based on the actual system and the PMSG model provided by the manufacturer. Then, small-signal eigenanalysis, time-domain simulation, and impedance model analysis are carried out to investigate the interactive dynamics between them. The results show that such interaction between direct-drive PMSG wind farms and weak ac grids characterized by low short-circuit ratio would cause negative-resistance effect for the SSI mode, leading to unstable oscillation. In such cases, the controller of PMSG would saturate soon, resulting in sustained power oscillation in the system. If unfortunately the oscillation frequency matches the torsional mode of any nearby turbogenerator, severe torsional vibration would be excited on the shaft of the latter. The analysis results are finally validated with field measurements of an actual SSI event. To address the problem, a supplementary subsynchronous damping control loop is attached to the controllers of PMSGs to reshape the impedance and thus to stabilize the SSI.

The emerging subsynchronous resonance (SSR) caused by the interaction of wind turbine generators (WTGs) with series compensation has aroused great concerns. For this particular issue, this paper is aimed to fill the gap between theoretical studies and actual observations. By analyzing the field data of 58 SSR events captured in a practical wind power system and examining the observed dynamics with previous theoretical results, the mechanism and characteristics of SSR are revealed in a more explicit and substantial way. The necessary conditions and dominant influential factors are identified and the underlying reasons are discovered. Theoretically derived as well as practically measured impedance models have demonstrated that the converter control of doubly fed induction generator (DFIG) produces negative resistance at the slip frequency and thus causes unstable SSR; while permanent magnet synchronous generators and self-excited induction generators are just passively engaged in those SSR incidents. The distribution of the oscillation frequency has also been examined with field measurements. It is discovered that WTGs at different locations participate into the same SSR mode and their frequencies are not fixed but keep changing with the time, the variation of grid topology, and the number of online generators.

The interaction between controllers of doubly fed induction generators (DFIGs) and fixed series compensations may cause a new type of subsynchronous resonance (SSR), namely subsynchronous control interaction. To mitigate this emerging issue, a novel suppression method, embedding subsynchronous notch filters (SNFs) into DFIG converter controllers, is proposed in this study. By using the impedance-model-based analysis and a quantitative location-dependent performance index, the best location is identified to insert SNFs into the controllers of both rotor-side and grid-side converters. Two specific SNF schemes are recommended for practical use, and a design procedure is developed to tune their parameters. As a case study, they are then applied to a practical series-compensated wind-farm system that suffered from SSR. Both impedance analysis and time-domain simulations have been conducted to investigate their performance. The results verified that they can defuse the interaction between DFIG controllers and series compensation; therefore, successfully eliminating the risk of unstable SSR under all possible operating conditions. The proposed SNF schemes are easy to design and implement, robust to changeable operating conditions and would not affect the normal dynamics of DFIGs. So, they are of great potential in addressing practical SSR issues.

Sub-synchronous control interaction (SSCI) is a stability problem caused by the interaction between the control system of doubly fed induction generator and a series-capacitor compensated electrical network. It, if not properly handled, could lead to system instability. Therefore, effective control measures must be taken to solve this problem. However, a practical control should be capable of depressing SSCI under varied operating conditions with different SSCI frequency. In this paper, the basic modeling and general characteristic of SSCI in Guyuan wind power system is firstly introduced. And the control-design task is formulated into a complex nonlinear optimization problem with many operation conditions. Then, a combination of genetic algorithm and simulated annealing, namely GA-SA, is proposed to solve the nonlinear optimization problem for multi-operation state. Next, simulations using RT-LAB are presented to demonstrate the effectiveness of our proposed control-design method. Finally, a brief conclusion is drawn that GA-SA offers an excellent approach to the optimal design of SSCI controllers.

A new type of subsynchronous resonance (SSR), namely, subsynchronous control interaction (SSCI), was recently observed in doubly-fed induction generators (DFIGs) interfaced with series-compensated power networks. In this paper, a more accurate method based on aggregated RLC circuit model is proposed to intuitively explain and quantitatively evaluate this type of SSR. For a practical power system containing multiple DFIGs and fixed series compensation, an improved impedance model (IM) is derived, which incorporates DFIG's full-scale control system. Around the series-resonant frequency, IM can be further represented with an aggregated RLC circuit model. Its equivalent parameters are worked out and then used for the quantitative assessment of potential SSR risk. The proposed method is applied for SSR analysis of a practical wind farm system in North China that experienced actual SSR incidents. The consistence between the obtained results and field measured data verifies its effectiveness very well. Further, its advantage in accuracy over existing impedance-based approaches is validated by both eigenvalue analysis and time-domain simulations. The method is also used to quantitatively investigate the impact on SSR stability from the various factors, including wind speed, number of online DFIGs and their control parameters.

Shore power is the use of shore-side electricity to satisfy ships’ electricity demand during berthing at ports. It is an effective measure of reducing the emissions produced by auxiliary engines of ships at berth. This paper develops a cooperative optimization method to model the problem of whether to allocate shore power for each berth and which berth is allocated for the stochastic arriving ship. The cooperative optimization method is to minimize the total cost of installing and using shore power systems and maximize the environmental benefit of reducing air pollution and greenhouse gas emissions. Considering the emission of different pollutants can’t be directly accumulated as the objective, different pollutants are uniformly expressed as economic penalties by imposing environmental taxes and then economic penalties are regarded as the objective of environmental benefits. Firstly, the problem is carried out by proposing a multi-objective cooperative optimization model from the perspective that both shipping and port companies take overall benefits of port supply chains as the optimization target. Next, the multi-objective particle swarm optimization algorithm is adopted to resolve the model. Then, a proposed bulk terminal/wharf is taken as an example to conduct experiments for gaining optimal solutions under different carbon pricing policy scenarios. After then, based on the proposed preference-based decision-making method, optimal decisions under different preference are obtained. Finally, in order to analyze the applicability and generalizability of the model, experiments are conducted to analyze the impact of environmental tax rates on results and berthing time on environmental benefits. The results show that optimal solutions can reduce emissions of carbon dioxide, sulfur oxides, nitrous oxides and particulate matters by at least 3.8% while reducing the total cost by 35.9%, compared with the baseline scheme. Meanwhile optimal solutions can reduce emissions by up to 100%, but increase the total cost by 183.7%. Besides, the proposed model has good applicability when the berthing time and environmental tax rates change. In conclusion, the developed method can be widely used for popularizing shore power, promoting port sustainable development, reducing global air pollution and greenhouse gas emissions.

To accurately evaluate the damage caused by subsynchronous resonance (SSR) to a turbo-generator shaft, we have developed a novel mechanical and electrical co-simulation method, wherein the continuous-mass-model-based mechanical system is simulated in a close-loop or coupled way with the electrical power system so that the detailed torque profile along the shaft can be obtained for further analysis of fatigue loss of life. Nonlinear mechanical damping is also modelled to reflect the torsional inter action more precisely. The co-simulation is implemented using commercial electromagnetic transient program and finite element analysis software. A special dynamic data exchange mechanism is designed to make it proceed very efficiently. As a case study, the proposed method has been applied for the root-cause analysis of a recent shaft failure incident in an India power plant. The extensive simulation results have fully demonstrated its effectiveness in acquiring fine-grained torques and its advantages over previous methods. Finally the direct cause of the shaft failure is identified to be the sustained torsional interaction (one type of SSR) between the turbo-generator and its connected series-compensated power system.

There are two critical issues in stabilizing subsynchronous resonance of practical power systems. One is to select an effective yet low-cost control scheme. The other is to optimize the controllers under all possible operating conditions and diversified system disturbances. To address these issues, this article proposes a combined control scheme and a coordinated control design method. The combined scheme is composed of a supplementary excitation damping controller and a voltage source converter based generator terminal subsynchronous damping controller deployed, respectively, on the rotor and stator sides of a generator to take full advantage of a supplementary excitation damping controller (very low cost) and generator terminal subsynchronous damping controller (fast response, flexibility in rating, and deployment). The coordinated control design is implemented through parameter optimization on the linearized system and performance verification with non-linear simulations. The former uses geneti...

Two main contributions of this paper are 1) the energy consumption of ships (ECS) in port is predicted, 2) reduction strategies for energy consumption of ships in port are discussed by the proposed prediction models considering green port. Firstly, 15 characteristics which have impact on the energy consumption of ships are collected by Jingtang Port in China and analysis is conducted. Then, five machine learning models including Gradient Boosting Regression (GBR), Random Forest Regression (RF), BP Network (BP), Liner Regression (LR) and K-Nearest Neighbor Regression (KNN) are developed and 15 features consisting of inherent property of ship and external features of ports are set as inputs. After then, k-folds cross validation is adopted to verify the effectiveness of models. Finally, the feature importance is calculated and the most important features are selected. Besides, experiments are conducted to find the effect of changing several features on energy consumption of ships, and two consumption reduction strategies are discussed. The results show that net tonnage, deadweight tonnage, actual weight and efficiency of facilities are the top 4 features for predicting the energy consumption of ships. In conclusion, when efficiency of facilities is doubled, the energy consumption of ships is reduced by 34.17% at berth and 8.41% in port. The finding of proposed methods and discussed strategies can give references to green port construction.

The contribution of this paper is to provide a method for optimizing installation capacity and operation strategy of a hybrid renewable energy system (HRES) with offshore wind energy for container terminals. A mixed integer optimization model of the HRES is proposed, in which maximum environmental and economic benefits are considered as two objectives, and energy supply and demand balances, energy storage balances, technical constraints and quantity limitations are considered as constraints. However, container terminals typically execute many complicated and stochastic operation processes, and thus represent highly dynamic energy demands. Therefore, a simulation-based optimization algorithm is developed to resolve the optimization model, which consists of a simulation model and an optimization module. The simulation model is constructed to overcome the stochastic characteristics and obtain the hourly energy demands in container terminals, which are fed into the optimization module. While, the optimization module is used to search the solution space and provide the final decisions under three evaluation strategies: cost-saving, low-carbon, and trade-off strategy. Finally, taking a container terminal in Northeast China as an example, optimal results are obtained by the proposed algorithm, which can be used to provide references for power department policy making and green container terminal construction.

With the rapidly growing penetration of wind power, photoelectricity and other renewables, the problems of subsynchronous resonances/oscillations resulting from the interaction between power-electronic converters and the transmission devices have become increasingly prominent. In these cases, there would be continuous subsynchronous power oscillations or sub- and supersynchronous voltage and current harmonics, which have serious impact on the safe and stable operation of the whole system. However, the existing synchrophasor technology based on fundamental frequency phasors failed to meet the requirement of monitoring sub- and supersynchronous oscillations. In this paper, a new method is proposed to track both fundamental phasor and sub- /supersynchronous oscillations. The method can automatically adapt to the change of the frequency of the signals, and is of high precision and fast response. The specific algorithm has been derived and analyzed theoretically, and the measurement accuracy and error characteristics have been investigated by testing signals. The results have verified the effectiveness of the proposed method.

Subsynchronous resonance (SSR) issue, namely subsynchronous control interaction (SSCI), was observed in doubly-fed induction generators (DFIGs) based wind farms connected to fixed series compensation. This paper proposes a novel scheme to deactivate SSR by adding subsynchronous suppression filters (SSFs) to DFIG converter controllers. Based on the impedance model analysis, a quantitative index is defined and implemented to identify the “best” location of converter controllers for embedding a SSF. A specific SSF scheme is recommended for practical application, which is to embed a SSF into d-axis channel in inner current loop of rotor-side converter. This scheme has been applied to a practical series-compensated DFIG-based wind farm system located in North China, which has experienced real SSR events. Both impedance analysis and time-domain simulation have validated the effectiveness of the proposed scheme. This control scheme has a broad application prospect due to its easiness to implement and robustness to changeable operating conditions.