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Wind Power Integration into Power Systems: Stability and Control Aspects
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Wind Power Integration into Power Systems: Stability and Control Aspects

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 33363

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Lasantha Meegahapola

E-Mail Website
Guest Editor
School of Engineering, RMIT University, Melbourne, Australia
Interests: power system stability with wind integration to power systems; power plant modelling and simulation; microgrid stability and control
Special Issues, Collections and Topics in MDPI journals
Dr. Siqi Bu

E-Mail Website
Guest Editor
Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: power system modelling; stability analysis and control; power system planning and operation; grid integration of onshore/offshore wind power generation; VSC/LCC-HVDC system and FACTS/ESS/VSG technology utilisation; plug-in electric vehicle applications

Special Issue Information

Dear Colleagues,

Power network operators are rapidly embracing wind power generation into their power grids to meet the renewable energy targets in power generation. With this substantially increased wind power generation, significantly high instantaneous wind power penetration levels have been reported recently in the power networks of many countries and regions (e.g., Germany, Denmark, Ireland, South Australia) while giving rise to complex power system stability and control issues. More specifically, the main stability issues pertinent to power systems with high wind power penetration are frequency stability, voltage stability, and oscillatory stability. Control techniques such as virtual/emulated inertia and damping controls can be developed to tackle these stability issues, and additional devices, such as energy storage systems, can also be deployed to mitigate the adverse impact of high wind power generation on various system stability problems.

In this context, the guest editors invite experts in this field to contribute original and unpublished papers to this Special Issue dealing with but not limited to the following research areas:

  • Frequency stability analysis with high wind power penetration;
  • Frequency regulation and virtual inertia schemes for low inertia power grids;
  • Voltage stability analysis with high wind power penetration;
  • Voltage management and control with high wind power penetration;
  • Oscillatory stability analysis with wind power generation;
  • Design and optimising energy storage systems for stability improvement;
  • Ancillary services management techniques with high wind power generation;
  • Application of artificial intelligence, and machine learning techniques for stability enhancement;
  • Optimal system planning, scheduling and coordination techniques to enhance with high wind power generation.

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Dr. Lasantha Meegahapola
Dr. Siqi Bu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • power systems
  • power electronics
  • renewable energy
  • energy storage
  • power system control and operation

Published Papers (15 papers)

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Editorial

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4 pages, 177 KiB  
Editorial
Special Issue: “Wind Power Integration into Power Systems: Stability and Control Aspects”
by Lasantha Meegahapola and Siqi Bu
Energies 2021, 14(12), 3680; https://0-doi-org.brum.beds.ac.uk/10.3390/en14123680 - 21 Jun 2021
Cited by 2 | Viewed by 1383
Abstract
Power network operators are rapidly incorporating wind power generation into their power grids to meet the widely accepted carbon neutrality targets and facilitate the transition from conventional fossil-fuel energy sources to the clean and low-carbon renewable energy sources [...] Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)

Research

Jump to: Editorial

22 pages, 43361 KiB  
Article
The LVRT Control Scheme for PMSG-Based Wind Turbine Generator Based on the Coordinated Control of Rotor Overspeed and Supercapacitor Energy Storage
by Xiangwu Yan, Linlin Yang and Tiecheng Li
Energies 2021, 14(2), 518; https://0-doi-org.brum.beds.ac.uk/10.3390/en14020518 - 19 Jan 2021
Cited by 15 | Viewed by 3330
Abstract
With the increasing penetration level of wind turbine generators (WTGs) integrated into the power system, the WTGs are enforced to aid network and fulfill the low voltage ride through (LVRT) requirements during faults. To enhance LVRT capability of permanent magnet synchronous generator (PMSG)-based [...] Read more.
With the increasing penetration level of wind turbine generators (WTGs) integrated into the power system, the WTGs are enforced to aid network and fulfill the low voltage ride through (LVRT) requirements during faults. To enhance LVRT capability of permanent magnet synchronous generator (PMSG)-based WTG connected to the grid, this paper presents a novel coordinated control scheme named overspeed-while-storing control for PMSG-based WTG. The proposed control scheme purely regulates the rotor speed to reduce the input power of the machine-side converter (MSC) during slight voltage sags. Contrarily, when the severe voltage sag occurs, the coordinated control scheme sets the rotor speed at the upper-limit to decrease the input power of the MSC at the greatest extent, while the surplus power is absorbed by the supercapacitor energy storage (SCES) so as to reduce its maximum capacity. Moreover, the specific capacity configuration scheme of SCES is detailed in this paper. The effectiveness of the overspeed-while-storing control in enhancing the LVRT capability is validated under different levels of voltage sags and different fault types in MATLAB/Simulink. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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19 pages, 6768 KiB  
Article
Transition from Electromechanical Dynamics to Quasi-Electromechanical Dynamics Caused by Participation of Full Converter-Based Wind Power Generation
by Jianqiang Luo, Siqi Bu and Jiebei Zhu
Energies 2020, 13(23), 6270; https://0-doi-org.brum.beds.ac.uk/10.3390/en13236270 - 27 Nov 2020
Cited by 4 | Viewed by 1653
Abstract
Previous studies generally consider that the full converter-based wind power generation (FCWG) is a “decoupled” power source from the grid, which hardly participates in electromechanical oscillations. However, it was found recently that strong interaction could be induced which might incur severe resonance incidents [...] Read more.
Previous studies generally consider that the full converter-based wind power generation (FCWG) is a “decoupled” power source from the grid, which hardly participates in electromechanical oscillations. However, it was found recently that strong interaction could be induced which might incur severe resonance incidents in the electromechanical dynamic timescale. In this paper, the participation of FCWG in electromechanical dynamics is extensively investigated, and particularly, an unusual transition of the electromechanical oscillation mode (EOM) is uncovered for the first time. The detailed mathematical models of the open-loop and closed-loop power systems are firstly established, and modal analysis is employed to quantify the FCWG participation in electromechanical dynamics, with two new mode identification criteria, i.e., FCWG dynamics correlation ratio (FDCR) and quasi-electromechanical loop correlation ratio (QELCR). On this basis, the impact of different wind penetration levels and controller parameter settings on the participation of FCWG is investigated. It is revealed that if an FCWG oscillation mode (FOM) has a similar oscillation frequency to the system EOMs, there is a high possibility to induce strong interactions between FCWG dynamics and system electromechanical dynamics of the external power systems. In this circumstance, an interesting phenomenon may occur that an EOM may be dominated by FCWG dynamics, and hence is transformed into a quasi-EOM, which actively involves the participation of FCWG quasi-electromechanical state variables. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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17 pages, 4093 KiB  
Article
Wind Inertial Response Based on the Center of Inertia Frequency of a Control Area
by Alija Mujcinagic, Mirza Kusljugic and Emir Nukic
Energies 2020, 13(23), 6177; https://0-doi-org.brum.beds.ac.uk/10.3390/en13236177 - 24 Nov 2020
Cited by 14 | Viewed by 3004
Abstract
As a result of the increased integration of power converter-connected variable speed wind generators (VSWG), which do not provide rotational inertia, concerns about the frequency stability of interconnected power systems permanently arise. If the inertia of a power system is insufficient, wind power [...] Read more.
As a result of the increased integration of power converter-connected variable speed wind generators (VSWG), which do not provide rotational inertia, concerns about the frequency stability of interconnected power systems permanently arise. If the inertia of a power system is insufficient, wind power plants’ participation in the inertial response should be required. A trendy solution for the frequency stability improvement in low inertia systems is based on utilizing so-called “synthetic” or “virtual” inertia from modern VSWG. This paper presents a control scheme for the virtual inertia response of wind power plants based on the center of inertia (COI) frequency of a control area. The PSS/E user written wind inertial controller based on COI frequency is developed using FORTRAN. The efficiency of the controller is tested and applied to the real interconnected power system of Southeast Europe. The performed simulations show certain conceptual advantages of the proposed controller in comparison to traditional schemes that use the local frequency to trigger the wind inertial response. The frequency response metrics, COI frequency calculation and graphical plots are obtained using Python. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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15 pages, 7527 KiB  
Article
Flexible Kinetic Energy Release Controllers for a Wind Farm in an Islanding System
by Yi-Wei Chen and Yuan-Yih Hsu
Energies 2020, 13(22), 6135; https://0-doi-org.brum.beds.ac.uk/10.3390/en13226135 - 23 Nov 2020
Cited by 1 | Viewed by 1289
Abstract
To improve frequency nadir following a disturbance and avoid under-frequency load shedding, two types of flexible kinetic energy release controllers for the doubly fed induction generator (DFIG) are proposed. The basic idea is to release only a small amount of kinetic energy stored [...] Read more.
To improve frequency nadir following a disturbance and avoid under-frequency load shedding, two types of flexible kinetic energy release controllers for the doubly fed induction generator (DFIG) are proposed. The basic idea is to release only a small amount of kinetic energy stored at the DFIG in the initial transient period (1–3 s after the disturbance). When the frequency dip exceeds a preset threshold, the amount of kinetic energy released is increased to improve the frequency nadir. To achieve the goal of flexible kinetic energy release, a deactivation function based integral controller is first presented. To further improve the dynamic frequency response under parameter uncertainties and external disturbances, a second flexible kinetic energy release controller is designed using a proportional-integral controller, with the gains being adapted in real-time with the particle swarm optimization algorithm. Based on the MATLAB/SIMULINK simulation results for a local power system, it is concluded that the frequency nadir can be maintained around the under-frequency load shedding threshold of 59.6 Hz using the proposed controllers. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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13 pages, 4446 KiB  
Article
Ultra-Short-Term Prediction of Wind Power Based on Error Following Forget Gate-Based Long Short-Term Memory
by Pei Zhang, Chunping Li, Chunhua Peng and Jiangang Tian
Energies 2020, 13(20), 5400; https://0-doi-org.brum.beds.ac.uk/10.3390/en13205400 - 16 Oct 2020
Cited by 12 | Viewed by 1810
Abstract
To improve the accuracy of ultra-short-term wind power prediction, this paper proposed a model using modified long short-term memory (LSTM) to predict ultra-short-term wind power. Because the forget gate of standard LSTM cannot reflect the correction effect of prediction errors on model prediction [...] Read more.
To improve the accuracy of ultra-short-term wind power prediction, this paper proposed a model using modified long short-term memory (LSTM) to predict ultra-short-term wind power. Because the forget gate of standard LSTM cannot reflect the correction effect of prediction errors on model prediction in ultra-short-term, this paper develops the error following forget gate (EFFG)-based LSTM model for ultra-short-term wind power prediction. The proposed EFFG-based LSTM model updates the output of the forget gate using the difference between the predicted value and the actual value, thereby reducing the impact of the prediction error at the previous moment on the prediction accuracy of wind power at this time, and improving the rolling prediction accuracy of wind power. A case study is performed using historical wind power data and numerical prediction meteorological data of an actual wind farm. Study results indicate that the root mean square error of the wind power prediction model based on EFFG-based LSTM is less than 3%, while the accuracy rate and qualified rate are more than 90%. The EFFG-based LSTM model provides better performance than the support vector machine (SVM) and standard LSTM model. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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15 pages, 6993 KiB  
Article
Neural Network-Based Supplementary Frequency Controller for a DFIG Wind Farm
by Ting-Hsuan Chien, Yu-Chuan Huang and Yuan-Yih Hsu
Energies 2020, 13(20), 5320; https://0-doi-org.brum.beds.ac.uk/10.3390/en13205320 - 13 Oct 2020
Cited by 11 | Viewed by 1973
Abstract
An artificial neural network (ANN)-based supplementary frequency controller is designed for a doubly fed induction generator (DFIG) wind farm in a local power system. Since the optimal controller gain that gives highest the frequency nadir or lowest peak frequency is a complicated nonlinear [...] Read more.
An artificial neural network (ANN)-based supplementary frequency controller is designed for a doubly fed induction generator (DFIG) wind farm in a local power system. Since the optimal controller gain that gives highest the frequency nadir or lowest peak frequency is a complicated nonlinear function of load disturbance and system variables, it is not easy to use analytical methods to derive the optimal gain. The optimal gain can be reached through an exhaustive search method. However, the exhaustive search method is not suitable for online applications, since it takes a long time to perform a great number of simulations. In this work, an ANN that uses load disturbance, wind penetration, and wind speed as the inputs and the desired controller gain as the output is proposed. Once trained by a proper set of training patterns, the ANN can be employed to yield the desired gain in a very efficient manner, even when the operating condition is not included in the training set. Therefore, the proposed ANN-based controller can be used for real-time frequency control. Results from MATLAB/SIMULINK simulations performed on a local power system in Taiwan reveal that the proposed ANN can yield a better frequency response than the fixed-gain controller. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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17 pages, 4110 KiB  
Article
Influence of Active Power Output and Control Parameters of Full-Converter Wind Farms on Sub-Synchronous Oscillation Characteristics in Weak Grids
by Yafeng Hao, Jun Liang, Kewen Wang, Guanglu Wu, Tibin Joseph and Ruijuan Sun
Energies 2020, 13(19), 5225; https://0-doi-org.brum.beds.ac.uk/10.3390/en13195225 - 07 Oct 2020
Cited by 7 | Viewed by 1886
Abstract
Active power outputs of a wind farm connected to a weak power grid greatly affect the stability of grid-connected voltage source converter (VSC) systems. This paper studies the impact of active power outputs and control parameters on the subsynchronous oscillation characteristics of full-converter [...] Read more.
Active power outputs of a wind farm connected to a weak power grid greatly affect the stability of grid-connected voltage source converter (VSC) systems. This paper studies the impact of active power outputs and control parameters on the subsynchronous oscillation characteristics of full-converter wind farms connected weak power grids. Eigenvalue and participation factor analysis was performed to identify the dominant oscillation modes of the system under consideration. The impact of active power output and control parameters on the damping characteristics of subsynchronous oscillation is analysed with the eigenvalue method. The analysis shows that when the phase-locked loop (PLL) proportional gain is high, the subsynchronous oscillation damping characteristics are worsened as the active power output increases. On the contrary, when the PLL proportional gain is small, the subsynchronous oscillation damping characteristics are improved as the active power output increases. By adjusting the control parameters in the PLL and DC link voltage controllers, system stability can be improved. Time-domain results verify the analysis and the findings. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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17 pages, 2837 KiB  
Article
A Novel Deep Learning Approach for Wind Power Forecasting Based on WD-LSTM Model
by Bingchun Liu, Shijie Zhao, Xiaogang Yu, Lei Zhang and Qingshan Wang
Energies 2020, 13(18), 4964; https://0-doi-org.brum.beds.ac.uk/10.3390/en13184964 - 22 Sep 2020
Cited by 49 | Viewed by 3248
Abstract
Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve [...] Read more.
Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve accurate prediction of wind power generation in China, a hybrid prediction model based on the combination of Wavelet Decomposition (WD) and Long Short-Term Memory neural network (LSTM) is constructed. Firstly, the nonstationary time series is decomposed into multidimensional components by WD, which can effectively reduce the volatility of the original time series and make them more stable and predictable. Then, the components of the original time series after WD are used as input variables of LSTM to predict the national wind power generation. Forty points were used, 80% as training samples and 20% as testing samples. The experimental results show that the MAPE of WD-LSTM is 5.831, performing better than other models in predicting wind power generation in China. In addition, the WD-LSTM model was used to predict the wind power generation in China under different development trends in the next two years. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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19 pages, 6282 KiB  
Article
A Modified Reynolds-Averaged Navier–Stokes-Based Wind Turbine Wake Model Considering Correction Modules
by Yuan Li, Zengjin Xu, Zuoxia Xing, Bowen Zhou, Haoqian Cui, Bowen Liu and Bo Hu
Energies 2020, 13(17), 4430; https://0-doi-org.brum.beds.ac.uk/10.3390/en13174430 - 27 Aug 2020
Cited by 3 | Viewed by 2191
Abstract
Increasing wind power generation has been introduced into power systems to meet the renewable energy targets in power generation. The output efficiency and output power stability are of great importance for wind turbines to be integrated into power systems. The wake effect influences [...] Read more.
Increasing wind power generation has been introduced into power systems to meet the renewable energy targets in power generation. The output efficiency and output power stability are of great importance for wind turbines to be integrated into power systems. The wake effect influences the power generation efficiency and stability of wind turbines. However, few studies consider comprehensive corrections in an aerodynamic model and a turbulence model, which challenges the calculation accuracy of the velocity field and turbulence field in the wind turbine wake model, thus affecting wind power integration into power systems. To tackle this challenge, this paper proposes a modified Reynolds-averaged Navier–Stokes (MRANS)-based wind turbine wake model to simulate the wake effects. Our main aim is to add correction modules in a 3D aerodynamic model and a shear-stress transport (SST) k-ω turbulence model, which are converted into a volume source term and a Reynolds stress term for the MRANS-based wake model, respectively. A correction module including blade tip loss, hub loss, and attack angle deviation is considered in the 3D aerodynamic model, which is established by blade element momentum aerodynamic theory and an improved Cauchy fuzzy distribution. Meanwhile, another correction module, including a hold source term, regulating parameters and reducing the dissipation term, is added into the SST k-ω turbulence model. Furthermore, a structured hexahedron mesh with variable size is developed to significantly improve computational efficiency and make results smoother. Simulation results of the velocity field and turbulent field with the proposed approach are consistent with the data of real wind turbines, which verifies the effectiveness of the proposed approach. The variation law of the expansion effect and the double-hump effect are also given. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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21 pages, 5836 KiB  
Article
Capacity Planning of Distributed Wind Power Based on a Variable-Structure Copula Involving Energy Storage Systems
by Yurong Wang, Ruolin Yang, Sixuan Xu and Yi Tang
Energies 2020, 13(14), 3602; https://0-doi-org.brum.beds.ac.uk/10.3390/en13143602 - 13 Jul 2020
Cited by 6 | Viewed by 1580
Abstract
Distributed wind power (DWP) needs to be consumed locally under a 110 kV network without reverse power flow in China. To maximize the use of DWP, this paper proposes a novel method for capacity planning of DWP with participation of the energy storage [...] Read more.
Distributed wind power (DWP) needs to be consumed locally under a 110 kV network without reverse power flow in China. To maximize the use of DWP, this paper proposes a novel method for capacity planning of DWP with participation of the energy storage system (ESS) in multiple scenarios by means of a variable-structure copula and optimization theory. First, wind power and local load are predicted at the planning stage by an autoregressive moving average (ARMA) model, then, variable-structure copula models are established based on different time segment strategies to depict the correlation of DWP and load, and the joint typical scenarios of DWP and load are generated by clustering, and a capacity planning model of DWP is proposed considering investment and operation cost, and environmental benefit and line loss cost under typical scenario conditions. Moreover, a collaborative capacity planning model for DWP and ESS is prospectively proposed. Based on the modified IEEE-33 bus system, the results of the case study show that the DWP capacity result is more reasonable after considering the correlation of wind and load by using a variable-structure copula. With consideration of the collaborative planning of DWP and load, the consumption of DWP is further improved, the annual cost of the system is more economical, and the quality of voltage is effectively improved. The study results validate the proposed method and provide effective reference for the planning strategy of DWP. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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14 pages, 1720 KiB  
Article
A Fast-Algorithmic Probabilistic Evaluation on Regional Rate of Change of Frequency (RoCoF) for Operational Planning of High Renewable Penetrated Power Systems
by Jiaxin Wen, Siqi Bu, Bowen Zhou, Qiyu Chen and Dongsheng Yang
Energies 2020, 13(11), 2780; https://0-doi-org.brum.beds.ac.uk/10.3390/en13112780 - 01 Jun 2020
Cited by 7 | Viewed by 1856
Abstract
The high rate of change of frequency (RoCoF) issue incurred by the integration of renewable energy sources (RESs) into a modern power system significantly threatens the grid security, and thus needs to be carefully examined in the operational planning. However, severe fluctuation of [...] Read more.
The high rate of change of frequency (RoCoF) issue incurred by the integration of renewable energy sources (RESs) into a modern power system significantly threatens the grid security, and thus needs to be carefully examined in the operational planning. However, severe fluctuation of regional frequency responses concerned by system operators could be concealed by the conventional assessment based on aggregated system frequency response. Moreover, the occurrence probability of a high RoCoF issue is actually a very vital factor during the system planner’s decision-making. Therefore, a fast-algorithmic evaluation method is proposed to determine the probabilistic distribution of regional RoCoF for the operational planning of a RES penetrated power system. First, an analytical sensitivity (AS) that quantifies the relationship between the regional RoCoF and the stochastic output of the RES is derived based on the generator and network information. Then a linear sensitivity-based analytical method (LSM) is established to calculate the regional RoCoF and the corresponding probabilistic distribution, which takes much less computational time when comparing with the scenario-based simulation (SBS) and involves much less complicated calculation procedure when comparing with the cumulant-based method (CBM). The effectiveness and efficiency of the proposed method are verified in a modified 16-machine 5-area IEEE benchmark system by numerical SBS and analytical CBM. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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17 pages, 7395 KiB  
Article
Analysis and Mitigation of Sub-Synchronous Resonance for Doubly Fed Induction Generator under VSG Control
by Yingzong Jiao, Feng Li, Hui Dai and Heng Nian
Energies 2020, 13(7), 1582; https://0-doi-org.brum.beds.ac.uk/10.3390/en13071582 - 01 Apr 2020
Cited by 10 | Viewed by 2309
Abstract
This paper presents the analysis and mitigation of sub-synchronous resonance (SSR) for doubly fed induction generators (DFIG) under virtual synchronous generator (VSG) control, based on impedance methods. VSGs are considered to have grid-supporting ability and good stability in inductance-based weak grids, and are [...] Read more.
This paper presents the analysis and mitigation of sub-synchronous resonance (SSR) for doubly fed induction generators (DFIG) under virtual synchronous generator (VSG) control, based on impedance methods. VSGs are considered to have grid-supporting ability and good stability in inductance-based weak grids, and are implemented in renewable power generations, including DFIG systems. However, stability analyses of VSGs for DFIG connecting with series capacitor compensation are absent. Therefore, this paper focuses on the analysis and mitigation of SSR for DFIG under VSG control. Impedance modeling of DFIG systems is used to analyze SSR stability. Based on impedance analysis, the influence of VSG control parameters and the configuration of damping factor of reactive power are discussed. Next, a parameter configuration method to mitigate SSR is proposed. Finally, time-domain simulation and fast fourier transform (FFT) results are given to validate the correctness and effectiveness of the impedance model and parameter configuration methods. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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12 pages, 1426 KiB  
Article
Adaptive Multi-Model Switching Predictive Active Power Control Scheme for Wind Generator System
by Hongwei Li, Kaide Ren, Shuaibing Li and Haiying Dong
Energies 2020, 13(6), 1329; https://0-doi-org.brum.beds.ac.uk/10.3390/en13061329 - 12 Mar 2020
Cited by 9 | Viewed by 1962
Abstract
To deal with the randomness and uncertainty of the wind power generation process, this paper proposes the use of the clustering method to complement the multi-model predictive control algorithm for active power control. Firstly, the fuzzy clustering algorithm is adopted to classify actual [...] Read more.
To deal with the randomness and uncertainty of the wind power generation process, this paper proposes the use of the clustering method to complement the multi-model predictive control algorithm for active power control. Firstly, the fuzzy clustering algorithm is adopted to classify actual measured data; then, the forgetting factor recursive least square method is used to establish the multi-model of the system as the prediction model. Secondly, the model predictive controller is designed to use the measured wind speed as disturbance, the pitch angle as the control variable, and the active power as the output. Finally, the parameters and measured data of wind generators in operation in Western China are adopted for simulation and verification. Compared to the single model prediction control method, the adaptive multi-model predictive control method can yield a much higher prediction accuracy, which can significantly eliminate the instability in the process of wind power generation. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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20 pages, 4007 KiB  
Article
Research on DFIG-ES System to Enhance the Fast-Frequency Response Capability of Wind Farms
by Sijia Tu, Bingda Zhang and Xianglong Jin
Energies 2019, 12(18), 3581; https://0-doi-org.brum.beds.ac.uk/10.3390/en12183581 - 19 Sep 2019
Cited by 9 | Viewed by 2626
Abstract
With the increasing penetration of wind power generation, the frequency regulation burden on conventional synchronous generators has become heavier, as the rotor speed of doubly-fed induction generator (DFIG) is decoupled with the system frequency. As the frequency regulation capability of wind farms is [...] Read more.
With the increasing penetration of wind power generation, the frequency regulation burden on conventional synchronous generators has become heavier, as the rotor speed of doubly-fed induction generator (DFIG) is decoupled with the system frequency. As the frequency regulation capability of wind farms is an urgent appeal, the inertia control of DFIG has been studied by many researchers and the energy storage (ES) system has been installed in wind farms to respond to frequency deviation with doubly-fed induction generators (DFIGs). In view of the high allocation and maintenance cost of the ES system, the capacity allocation scheme of the ES system—especially for fast-frequency response—is proposed in this paper. The capacity allocation principle was to make the wind farm possess the same potential inertial energy as that of synchronous generators set with equal rated power. After the capacity of the ES system was defined, the coordinated control strategy of the DFIG-ES system with consideration of wind speed was proposed in order to improve the frequency nadir during fast-frequency response. The overall power reference of the DFIG-ES system was calculated on the basis of the frequency response characteristic of synchronous generators. In particular, once the power reference of DFIG was determined, a novel virtual inertia control method of DFIG was put forward to release rotational kinetic energy and produce power surge by means of continuously modifying the proportional coefficient of maximum power point tracking (MPPT) control. During the deceleration period, the power reference smoothly decreased with the rotor speed until it reached the MPPT curve, wherein the rotor speed could rapidly recover by virtue of wind power so that the secondary frequency drop could be avoided. Afterwards, a fuzzy logic controller (FLC) was designed to distribute output power between the DFIG and ES system according to the rotor speed of DFIG and S o C of ES; thus the scheme enabled the DFIG-ES system to respond to frequency deviation in most cases while preventing the secondary frequency drop and prolonging the service life of the DFIG-ES system. Finally, the test results, which were based on the simulation system on MATLAB/Simulink software, verified the effectiveness of the proposed control strategy by comparison with other control methods and verified the rationality of the designed fuzzy logic controller and proposed capacity allocation scheme of the ES system. Full article
(This article belongs to the Special Issue Wind Power Integration into Power Systems: Stability and Control Aspects)
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