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Special Issue "Wind Generators Modelling and Control"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: 31 December 2017

Special Issue Editor

Guest Editor
Prof. Marco Mussetta

Politecnico di Milano—Energy Department—Via Lambruschini 4, 20156 Milano, Italy
Website | E-Mail
Interests: optimization; computational intelligence; photovoltaics; wind energy; antennas

Special Issue Information

Dear Colleagues,

We invite submissions to a Special Issue of the journal Energies on the topic of “Wind Generators Modelling and Control”.

Wind power is among the world's fastest growing renewable sources, with significant impacts on power quality, electrical grid stability, and reliability. Indeed, major challenges are involved in the modeling, control, and general operation of these systems; for example, due to sudden wind power variations and unpredictability, without proper modeling and intelligent coordination control, these wind generation systems cannot function effectively.

To address these issues, it is necessary to focus on the performance, modeling, and control of different wind generators, i.e., the squirrel-cage induction generator (SCIG), the doubly-fed induction generator (DFIG), the permanent-magnet synchronous generator (PMSG), and their integration in traditional electrical grids and novel smart grids. Therefore, relevant research topics are represented by wind generator modeling techniques, both in transient and steady-state, as well as control systems, based on traditional (PI, PID) or novel control strategies (e.g., Fuzzy Logic, Neural network, etc.), with particular attention to grid disturbances, fault ride-through (FRT) and low voltage ride through (LVRT) techniques, and protection devices for power electronic converters.

This Special Issue would like to encourage original contributions regarding recent developments and ideas in wind generator modeling and control. Potential topics include, but are not limited to: Wind generator technologies, wind turbines control, wind generator diagnostics, grid interconnection, fault ride-through operation, protection devices (both on rotor and stator side), reliability, operations and maintenance, and smart-grid integration.

Prof. Marco Mussetta
Guest Editor

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 papers will be 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 monthly 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 1500 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

  • wind power
  • wind turbines
  • wind farms
  • offshore wind energy
  • numerical modeling
  • power electronics
  • Fuzzy Logic Control
  • neural network
  • smart grid
  • power system

Published Papers (15 papers)

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Research

Open AccessArticle Adaptive State Feedback—Theory and Application for Wind Turbine Control
Energies 2017, 10(12), 2145; doi:10.3390/en10122145 (registering DOI)
Received: 1 October 2017 / Revised: 27 November 2017 / Accepted: 11 December 2017 / Published: 15 December 2017
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Abstract
A class of adaptive disturbance tracking controllers (ADTCs) is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant.
[...] Read more.
A class of adaptive disturbance tracking controllers (ADTCs) is augmented with disturbance and state estimation and adaptive state feedback, in which a controller and estimator, which are designed on the basis of a lower-order model, are used to control a higher-order nonlinear plant. The ADTC requires that the plant be almost strict positive real (ASPR) to ensure stability. In this paper, we show that the ASPR property of a plant is retained with the addition of disturbance and state estimation and state feedback, thereby ensuring the stability of the augmented system. The proposed adaptive controller with augmentation is presented in the context of maximum power extraction from a wind turbine in a low-wind-speed operation region. A simulation and comparative study on the National Renewable Energy Laboratory’s (NREL’s) 5 MW nonlinear wind turbine model with an existing baseline Proportional-Integral-Derivative(PID) controller shows that the proposed controller is more effective than the existing baseline PID controller. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle A Naive Bayesian Wind Power Interval Prediction Approach Based on Rough Set Attribute Reduction and Weight Optimization
Energies 2017, 10(11), 1903; doi:10.3390/en10111903
Received: 19 October 2017 / Revised: 13 November 2017 / Accepted: 15 November 2017 / Published: 19 November 2017
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Abstract
Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power
[...] Read more.
Intermittency and uncertainty pose great challenges to the large-scale integration of wind power, so research on the probabilistic interval forecasting of wind power is becoming more and more important for power system planning and operation. In this paper, a Naive Bayesian wind power prediction interval model, combining rough set (RS) theory and particle swarm optimization (PSO), is proposed to further improve wind power prediction performance. First, in the designed prediction interval model, the input variables are identified based on attribute significance using rough set theory. Next, the Naive Bayesian Classifier (NBC) is established to obtain the prediction power class. Finally, the upper and lower output weights of NBC are optimized segmentally by PSO, and are used to calculate the upper and lower bounds of the optimal prediction intervals. The superiority of the proposed approach is demonstrated by comparison with a Naive Bayesian model with fixed output weight, and a rough set-Naive Bayesian model with fixed output weight. It is shown that the proposed rough set-Naive Bayesian-particle swarm optimization method has higher coverage of the probabilistic prediction intervals and a narrower average bandwidth under different confidence levels. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle An Extended System Frequency Response Model Considering Wind Power Participation in Frequency Regulation
Energies 2017, 10(11), 1797; doi:10.3390/en10111797
Received: 22 September 2017 / Revised: 16 October 2017 / Accepted: 1 November 2017 / Published: 8 November 2017
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Abstract
With increasing penetration of wind power into the power system, wind power participation in frequency regulation is regarded as a beneficial strategy to improve the dynamic frequency response characteristics of power systems. The traditional power system frequency response (SFR) model, which only includes
[...] Read more.
With increasing penetration of wind power into the power system, wind power participation in frequency regulation is regarded as a beneficial strategy to improve the dynamic frequency response characteristics of power systems. The traditional power system frequency response (SFR) model, which only includes synchronous generators, is no longer suitable for power systems with high penetrated wind power. An extended SFR model, based on the reduced-order model of wind turbine generator (WTG) and the traditional SFR model, is presented in this paper. In the extended SFR model, the reduced-order model of WTG with combined frequency control is deduced by employing small signal analysis theory. Afterwards, the stability analysis of a closed-loop control system for the extended SFR model is carried out. Time-domain simulations using a test system are performed to validate the effectiveness of the extended SFR model; this model can provide a simpler, clearer and faster way to analyze the dynamic frequency response characteristic for a high-wind integrated power systems. The impact of additional frequency control parameters and wind speed disturbances on the system dynamic frequency response characteristics are investigated. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Critical Speed Control for a Fixed Blade Variable Speed Wind Turbine
Energies 2017, 10(11), 1699; doi:10.3390/en10111699
Received: 12 September 2017 / Accepted: 23 October 2017 / Published: 25 October 2017
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Abstract
A critical speed controller for avoiding a certain rotational speed is presented. The controller is useful for variable speed wind turbines with a natural frequency in the operating range. The controller has been simulated, implemented and tested on an open site 12 kW
[...] Read more.
A critical speed controller for avoiding a certain rotational speed is presented. The controller is useful for variable speed wind turbines with a natural frequency in the operating range. The controller has been simulated, implemented and tested on an open site 12 kW vertical axis wind turbine prototype. The controller is based on an adaptation of the optimum torque control. Two lookup tables and a simple state machine provide the control logic of the controller. The controller requires low computational resources, and no wind speed measurement is needed. The results suggest that the controller is a feasible method for critical speed control. The skipping behavior can be adjusted using only two parameters. While tested on a vertical axis wind turbine, it may be used on any variable speed turbine with the control of generator power. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Short-Circuit Fault Tolerant Control of a Wind Turbine Driven Induction Generator Based on Sliding Mode Observers
Energies 2017, 10(10), 1611; doi:10.3390/en10101611
Received: 11 August 2017 / Revised: 22 September 2017 / Accepted: 6 October 2017 / Published: 14 October 2017
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Abstract
The installed energy production capacity of wind turbines is growing intensely on a global scale, making the reliability of wind turbine subsystems of greater significance. However, many faults like Inter-Turn Short-Circuit (ITSC) may affect the turbine generator and quickly lead to a decline
[...] Read more.
The installed energy production capacity of wind turbines is growing intensely on a global scale, making the reliability of wind turbine subsystems of greater significance. However, many faults like Inter-Turn Short-Circuit (ITSC) may affect the turbine generator and quickly lead to a decline in supplied power quality. In this framework, this paper proposes a Sliding Mode Observer (SMO)-based Fault Tolerant Control (FTC) scheme for Induction Generator (IG)-based variable-speed grid-connected wind turbines. First, the dynamic models of the wind turbine subsystems were developed. The control schemes were elaborated based on the Maximum Power Point Tracking (MPPT) method and Indirect Rotor Flux Oriented Control (IRFOC) method. The grid control was also established by regulating the active and reactive powers. The performance of the wind turbine system and the stability of injected power to the grid were hence analyzed under both healthy and faulty conditions. The robust developed SMO-based Fault Detection and Isolation (FDI) scheme was proved to be fast and efficient for ITSC detection and localization.Afterwards, SMO were involved in scheming the FTC technique. Accordingly, simulation results assert the efficacy of the proposed ITSC FTC method for variable-speed wind turbines with faulty IG in protecting the subsystems from damage and ensuring continuous connection of the wind turbine to the grid during ITSC faults, hence maintaining power quality. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Estimating Health Condition of the Wind Turbine Drivetrain System
Energies 2017, 10(10), 1583; doi:10.3390/en10101583
Received: 4 September 2017 / Revised: 30 September 2017 / Accepted: 10 October 2017 / Published: 12 October 2017
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Abstract
Condition Monitoring (CM) has been considered as an effective method to enhance the reliability of wind turbines and implement cost-effective maintenance. Thus, adopting an efficient approach for condition monitoring of wind turbines is desirable. This paper presents a data-driven model-based CM approach for
[...] Read more.
Condition Monitoring (CM) has been considered as an effective method to enhance the reliability of wind turbines and implement cost-effective maintenance. Thus, adopting an efficient approach for condition monitoring of wind turbines is desirable. This paper presents a data-driven model-based CM approach for wind turbines based on the online sequential extreme learning machine (OS-ELM) algorithm. A physical kinetic energy correction model is employed to normalize the temperature change to the value at the rated power output to eliminate the effect of variable speed operation of the turbines. The residual signal, obtained by comparing the predicted values and practical measurements, is processed by the physical correction model and then assessed with a Bonferroni interval method for fault diagnosis. Models have been validated using supervisory control and data acquisition (SCADA) data acquired from an operational wind farm, which contains various types of temperature data of the gearbox. The results show that the proposed method can detect more efficiently both the long-term aging characteristics and the short-term faults of the gearbox. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Advanced Reactive Power Reserve Management Scheme to Enhance LVRT Capability
Energies 2017, 10(10), 1540; doi:10.3390/en10101540
Received: 7 September 2017 / Revised: 27 September 2017 / Accepted: 27 September 2017 / Published: 5 October 2017
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Abstract
Abstract: To increase the utilization of wind power in the power system, grid integration standards have been proposed for the stable integration of large-scale wind power plants. In particular, fault-ride-through capability, especially Low-Voltage-Ride-Through (LVRT), has been emphasized, as it is related to
[...] Read more.
Abstract: To increase the utilization of wind power in the power system, grid integration standards have been proposed for the stable integration of large-scale wind power plants. In particular, fault-ride-through capability, especially Low-Voltage-Ride-Through (LVRT), has been emphasized, as it is related to tripping in wind farms. Therefore, this paper proposes the Wind power plant applicable-Effective Reactive power Reserve (Wa-ERPR), which combines both wind power plants and conventional generators at the Point of Interconnection (POI). The reactive power capability of the doubly-fed induction generator wind farm was considered to compute the total Wa-ERPR at the POI with reactive power capability of existing generators. By using the Wa-ERPR management algorithm, in case of a violation of the LVRT standards, the amount of reactive power compensation is computed using the Wa-ERPR management scheme. The proposed scheme calculates the Wa-ERPR and computes the required reactive power, reflecting the change of the system topology pre- and post-contingency, to satisfy the LVRT criterion when LVRT regulation is not satisfied at the POI. The static synchronous compensator (STATCOM) with the capacity corresponding to calculated amount of reactive power through the Wa-ERPR management scheme is applied to the POI. Therefore, it is confirmed that the wind power plant satisfies the LVRT criteria by securing the appropriate reactive power at the POI, by applying of the proposed algorithm. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessFeature PaperCommunication Analytical Derivation of Electrical-Side Maximum Power Line for Wind Generators
Energies 2017, 10(10), 1498; doi:10.3390/en10101498
Received: 16 August 2017 / Revised: 18 September 2017 / Accepted: 25 September 2017 / Published: 26 September 2017
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Abstract
In order to enhance the maximum power point tracking (MPPT) speed of solar generators, offline calculated maximum power line (MPL) is often used as a feed-forward signal added to the output of MPPT controller. MPL is nonlinear static electrical characteristic of renewable energy
[...] Read more.
In order to enhance the maximum power point tracking (MPPT) speed of solar generators, offline calculated maximum power line (MPL) is often used as a feed-forward signal added to the output of MPPT controller. MPL is nonlinear static electrical characteristic of renewable energy generators connecting all the maximum power points for given temperature. In this letter, electrical side MPL is derived for a typical wind turbine generator (WTG). It is shown that MPLs of solar and wind generators possess similar structure, supporting the similarity between the two energy conversion processes. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle A Novel Sliding Mode Control Scheme for a PMSG-Based Variable Speed Wind Energy Conversion System
Energies 2017, 10(10), 1476; doi:10.3390/en10101476
Received: 5 August 2017 / Revised: 10 September 2017 / Accepted: 12 September 2017 / Published: 24 September 2017
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Abstract
This work proposes a novel control scheme for a variable speed wind turbine system based on the permanent magnet synchronous generator. Regions II and III for a wind speed profile are considered, hence the control is designed for maximizing the generated power from
[...] Read more.
This work proposes a novel control scheme for a variable speed wind turbine system based on the permanent magnet synchronous generator. Regions II and III for a wind speed profile are considered, hence the control is designed for maximizing the generated power from the wind turbine when the wind speed is below the nominal wind speed, and to saturate the generated power when the wind speed is above its nominal value in order to avoid damage to the system. Based on nonlinear models, the control scheme is also designed for introducing robustness to the closed-loop system. The pitch angle reference signal is also designed based on a mathematical model of the system, yielding in that way to a great performance of the wind turbine as predicted by the numeric simulations. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Generic Type 3 Wind Turbine Model Based on IEC 61400-27-1: Parameter Analysis and Transient Response under Voltage Dips
Energies 2017, 10(9), 1441; doi:10.3390/en10091441
Received: 31 July 2017 / Revised: 12 September 2017 / Accepted: 14 September 2017 / Published: 19 September 2017
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Abstract
This paper analyzes the response under voltage dips of a Type 3 wind turbine topology based on IEC 61400-27-1. The evolution of both active power and rotational speed is discussed in detail when some of the most relevant control parameters, included in the
[...] Read more.
This paper analyzes the response under voltage dips of a Type 3 wind turbine topology based on IEC 61400-27-1. The evolution of both active power and rotational speed is discussed in detail when some of the most relevant control parameters, included in the mechanical, active power and pitch control models, are modified. Extensive results are also included to explore the influence of these parameters on the model dynamic response. This work thus provides an extensive analysis of the generic Type 3 wind turbine model and provides an estimation of parameters not previously discussed in the specific literature. Indeed, the International Standard IEC 61400-27-1, recently published in February 2015, defines these generic dynamic simulation models for wind turbines, but does not provide values for the parameters to simulate the response of these models. Thus, there is a pressing need to establish correlations between IEC generic models and specific wind turbine manufacturer models to estimate suitable parameters for simulation purposes. Extensive results and simulations are also included in the paper. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle An Electro-Geometric Model for Lightning Shielding of Multiple Wind Turbines
Energies 2017, 10(9), 1272; doi:10.3390/en10091272
Received: 20 July 2017 / Revised: 18 August 2017 / Accepted: 24 August 2017 / Published: 26 August 2017
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Abstract
Wind turbine blades being struck by lightning is one of the most urgent problems facing wind farms. In order to reduce the probability of lightning accidents on wind farms, this paper presents a new electro-geometric model for multiple turbines. In this new model,
[...] Read more.
Wind turbine blades being struck by lightning is one of the most urgent problems facing wind farms. In order to reduce the probability of lightning accidents on wind farms, this paper presents a new electro-geometric model for multiple turbines. In this new model, based on the physical model of lightning leader development, the striking distance range of the blade tip receptor is calculated, taking into account the influence of the charged particles around the blade. Lightning shielding amongst multiple turbines is provided in combination with the traditional electro-geometric model, and a criterion formula is obtained for mutual shielding for multiple turbines. The influence of environmental factors, such as temperature, atmospheric pressure, air humidity, and altitude, on lightning shielding on large-scale wind farms is also analyzed by studying the lightning shielding distance between wind turbines. The calculation shows that the larger the relative air density and the absolute humidity, and the lower the altitude, and the larger the lightning shielding distance between wind turbines. The method proposed in this paper provides a theoretical basis for the lightning protection on wind farms under different environmental conditions. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Fault Prediction and Diagnosis of Wind Turbine Generators Using SCADA Data
Energies 2017, 10(8), 1210; doi:10.3390/en10081210
Received: 13 April 2017 / Revised: 31 July 2017 / Accepted: 10 August 2017 / Published: 15 August 2017
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Abstract
The fast-growing wind power industry faces the challenge of reducing operation and maintenance (O&M) costs for wind power plants. Predictive maintenance is essential to improve wind turbine reliability and prolong operation time, thereby reducing the O&M cost for wind power plants. This study
[...] Read more.
The fast-growing wind power industry faces the challenge of reducing operation and maintenance (O&M) costs for wind power plants. Predictive maintenance is essential to improve wind turbine reliability and prolong operation time, thereby reducing the O&M cost for wind power plants. This study presents a solution for predictive maintenance of wind turbine generators. The proposed solution can: (1) predict the remaining useful life (RUL) of wind turbine generators before a fault occurs and (2) diagnose the state of the wind turbine generator when the fault occurs. Moreover, the proposed solution implies low-deployment costs because it relies solely on the information collected from the widely available supervisory control and data acquisition (SCADA) system. Extra sensing hardware is needless. The proposed solution has been deployed and evaluated in two real-world wind power plants located in China. The experimental study demonstrates that the RUL of the generators can be predicted 18 days ahead with about an 80% prediction accuracy. When faults occur, the specific type of generator fault can be diagnosed with an accuracy of 94%. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System
Energies 2017, 10(8), 1098; doi:10.3390/en10081098
Received: 7 June 2017 / Revised: 20 July 2017 / Accepted: 23 July 2017 / Published: 26 July 2017
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Abstract
A feasible control strategy is proposed to control a doubly fed induction generator based on the wind energy converter system (DFIG-WECS). The main aim is to enhance the steady state and dynamic performance under the condition of the parameter perturbations and external disturbances
[...] Read more.
A feasible control strategy is proposed to control a doubly fed induction generator based on the wind energy converter system (DFIG-WECS). The main aim is to enhance the steady state and dynamic performance under the condition of the parameter perturbations and external disturbances and to satisfy the stator power response of the system. Within the proposed control method, the control scheme for the rotor side converter (RSC) is developed on the model predictive control. Firstly, the self-adaptive reference trajectory is established from the deduced discrete state-space equation of the generator. Then, the rotor voltage is calculated by minimizing the global performance index under the current prediction steps at the sampling instant. Through the control scheme for the grid side converter (GSC) and wind turbine, we have re-applied the conventional control. The effectiveness of the proposed control strategy is verified via time domain simulation of a 150 kW-575 V DFIG-WECS using Matlab/Simulink. The simulation result shows that the control of the DFIG with the proposed control method can enhance the steady and dynamic response capability better than the conventional ones when the system faces errors due to the parameter perturbations, external disturbances and the rotor speed. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Optimal Power Transmission of Offshore Wind Power Using a VSC-HVdc Interconnection
Energies 2017, 10(7), 1046; doi:10.3390/en10071046
Received: 4 April 2017 / Revised: 6 July 2017 / Accepted: 17 July 2017 / Published: 20 July 2017
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Abstract
High-voltage dc transmission based on voltage-source converter (VSC-HVdc) is quickly increasing its power rating, and it can be the most appropriate link for the connection of offshore wind farms (OWFs) to the grid in many locations. This paper presents a steady-state operation model
[...] Read more.
High-voltage dc transmission based on voltage-source converter (VSC-HVdc) is quickly increasing its power rating, and it can be the most appropriate link for the connection of offshore wind farms (OWFs) to the grid in many locations. This paper presents a steady-state operation model to calculate the optimal power transmission of an OWF connected to the grid through a VSC-HVdc link. The wind turbines are based on doubly fed induction generators (DFIGs), and a detailed model of the internal OWF grid is considered in the model. The objective of the optimization problem is to maximize the active power output of the OWF, i.e., the reduction of losses, by considering the optimal reactive power allocation while taking into account the restrictions imposed by the available wind power, the reactive power capability of the DFIG, the DC link model, and the operating conditions. Realistic simulations are performed to evaluate the proposed model and to execute optimal operation analyses. The results show the effectiveness of the proposed method and demonstrate the advantages of using the reactive control performed by DFIG to achieve the optimal operation of the VSC-HVdc. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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Open AccessArticle Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm
Energies 2017, 10(6), 812; doi:10.3390/en10060812
Received: 22 April 2017 / Revised: 7 June 2017 / Accepted: 13 June 2017 / Published: 15 June 2017
PDF Full-text (1728 KB) | HTML Full-text | XML Full-text
Abstract
Short-term wind power forecasting is a technique which tells system operators how much wind power can be expected at a specific time. Due to the increasing penetration of wind generating resources into the power grids, short-term wind power forecasting is becoming an important
[...] Read more.
Short-term wind power forecasting is a technique which tells system operators how much wind power can be expected at a specific time. Due to the increasing penetration of wind generating resources into the power grids, short-term wind power forecasting is becoming an important issue for grid integration analysis. The high reliability of wind power forecasting can contribute to the successful integration of wind generating resources into the power grids. To guarantee the reliability of forecasting, power curves need to be analyzed and a forecasting method used that compensates for the variability of wind power outputs. In this paper, we analyzed the reliability of power curves at each wind speed using logistic regression. To reduce wind power forecasting errors, we proposed a short-term wind power forecasting method using support vector machine (SVM) based on linear regression. Support vector machine is a type of supervised leaning and is used to recognize patterns and analyze data. The proposed method was verified by empirical data collected from a wind turbine located on Jeju Island. Full article
(This article belongs to the Special Issue Wind Generators Modelling and Control)
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