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- Herausgeber: John Wiley & Sons
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- Sprache: Englisch
An essential reference to the modeling techniques of wind turbine systems for the application of advanced control methods This book covers the modeling of wind power and application of modern control methods to the wind power control--specifically the models of type 3 and type 4 wind turbines. The modeling aspects will help readers to streamline the wind turbine and wind power plant modeling, and reduce the burden of power system simulations to investigate the impact of wind power on power systems. The use of modern control methods will help technology development, especially from the perspective of manufactures. Chapter coverage includes: status of wind power development, grid code requirements for wind power integration; modeling and control of doubly fed induction generator (DFIG) wind turbine generator (WTG); optimal control strategy for load reduction of full scale converter (FSC) WTG; clustering based WTG model linearization; adaptive control of wind turbines for maximum power point tracking (MPPT); distributed model predictive active power control of wind power plants and energy storage systems; model predictive voltage control of wind power plants; control of wind power plant clusters; and fault ride-through capability enhancement of VSC HVDC connected offshore wind power plants. Modeling and Modern Control of Wind Power also features tables, illustrations, case studies, and an appendix showing a selection of typical test systems and the code of adaptive and distributed model predictive control. * Analyzes the developments in control methods for wind turbines (focusing on type 3 and type 4 wind turbines) * Provides an overview of the latest changes in grid code requirements for wind power integration * Reviews the operation characteristics of the FSC and DFIG WTG * Presents production efficiency improvement of WTG under uncertainties and disturbances with adaptive control * Deals with model predictive active and reactive power control of wind power plants * Describes enhanced control of VSC HVDC connected offshore wind power plants Modeling and Modern Control of Wind Power is ideal for PhD students and researchers studying the field, but is also highly beneficial to engineers and transmission system operators (TSOs), wind turbine manufacturers, and consulting companies.
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Table of Contents
Cover
Title Page
Copyright
List of Contributors
About the Companion Website
Chapter 1: Status of Wind Power Technologies
1.1 Wind Power Development
1.2 Wind Turbine Generator Technology
1.3 Conclusion
References
Chapter 2: Grid Code Requirements for Wind Power Integration
2.1 Introduction
2.2 Steady-state Operational Requirements
2.3 Low-voltage Ride Through Requirement
2.4 Conclusion
References
Chapter 3: Control of Doubly-fed Induction Generators for Wind Turbines
3.1 Introduction
3.2 Principles of Doubly-fed Induction Generator
3.3 PQ Control of Doubly-fed Induction Generator
3.4 Direct Torque Control of Doubly-fed Induction Generators
3.5 Low-voltage Ride Through of DFIGs
3.6 Conclusions
References
Chapter 4: Optimal Control Strategies of Wind Turbines for Load Reduction
4.1 Introduction
4.2 The Dynamic Model of a Wind Turbine
4.3 Wind Turbine Individual Pitch Control
4.4 Drivetrain Torsional Vibration Control
4.5 Conclusion
References
Chapter 5: Modeling of Full-scale Converter Wind Turbine Generator
5.1 Introduction
5.2 Operating Characteristics of FSC-WTGs
5.3 FSC-WTG Model
5.4 Full Scale Converter Control System
5.5 Grid-connected FSC-WTG Stability Control
5.6 Conclusion
References
Chapter 6: Clustering-based Wind Turbine Generator Model Linearization
6.1 Introduction
6.2 Operational Regions of Power-controlled Wind Turbines
6.3 Simplified Wind Turbine Model
6.4 Clustering-based Identification Method
6.5 Discrete-time PWA Modeling of Wind Turbines
6.6 Case Study
6.7 Conclusion
References
Chapter 7: Adaptive Control of Wind Turbines for Maximum Power Point Tracking
7.1 Introduction
7.2 Generator Control System for WECSs
7.3 Design of Adaptive Controller
7.4 Case Study
7.5 Conclusion
References
Chapter 8: Distributed Model Predictive Active Power Control of Wind Farms
8.1 Introduction
8.2 Wind Farm without Energy Storage
8.3 Wind Farm Equipped with Energy Storage
8.4 Case Study
8.5 Conclusion
References
Chapter 9: Model Predictive Voltage Control of Wind Power Plants
9.1 Introduction
9.2 MPC-based WFVC
9.3 Sensitivity Coefficient Calculation
9.4 Modeling of WTGs and SVCs/SVGs
9.5 Coordination with OLTC
9.6 Formulation of MPC Problem for WFVC
9.7 Case Study
9.8 Conclusion
References
Chapter 10: Control of Wind Farm Clusters
10.1 Introduction
10.2 Active Power and Frequency Control of Wind Farm Clusters
10.3 Reactive Power and Voltage Control of Wind Farms
10.4 Conclusion
References
Chapter 11: Fault Ride Through Enhancement of VSC-HVDC Connected Offshore Wind Power Plants
11.1 Introduction
11.2 Modeling and Control of VSC-HVDC-connected Offshore WPPs
11.3 Feedforward DC Voltage Control based FRT Technique for VSC-HVDC-connected WPP
11.4 Time-domain Simulation of FRT for VSC-HVDC-connected WPPs
11.5 Conclusions
References
Chapter 12: Power Oscillation Damping from VSC-HVDC-connected Offshore Wind Power Plants
12.1 Introduction
12.2 Modelling for Simulation
12.3 POD from Power Electronic Sources
12.4 Implementation on VSC-HVDC-connected WPPs
12.5 Conclusion
Acknowledgement
References
Index
End User License Agreement
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Guide
Cover
Table of Contents
Begin Reading
List of Illustrations
Chapter 1: Status of Wind Power Technologies
Figure 1.1 Global annual installed wind capacity 2005-2015 [4].
Figure 1.2 Global cumulative installed wind capacity 2005-2015 [4].
Figure 1.3 Newly installed capacity during 2015 [4].
Figure 1.4 Cumulative capacities at 2015 [4].
Figure 1.5 Wind power penetration in leading wind markets in 20142015 [6].
Figure 1.6 Structure of Type 1 WTG [8]. Refer to main text for explanation of acronyms.
Figure 1.7 Structure of Type 2 WTG [8]. Refer to main text for explanation of acronyms.
Figure 1.8 Structure of Type 3 WTG [8]. Refer to main text for explanation of acronyms.
Figure 1.9 Structure of Type 4 WTG [8]. Refer to main text for explanation of acronyms.
Chapter 2: Grid Code Requirements for Wind Power Integration
Figure 2.1 Reactive power requirement of the WPP in the UK [4].
Figure 2.2 Reactive power requirement of WPPs in Ireland [5].
Figure 2.3 Reactive power requirement in Denmark for WPPs with a power output range of 1.5–25 MW [7].
Figure 2.4 Reactive power requirement in Denmark for WPPs with a power output greater than 25 MW [7].
Figure 2.5 Requirements of the voltage control range in Denmark for WPPs with a power output greater than 25 MW [7].
Figure 2.6 Reactive power requirement vs. voltage on the HV side of the main transformer of a WPP in Quebec [11].
Figure 2.7 Reactive power requirement vs. active power on the HV side of the main transformer of a WPP in Quebec [11].
Figure 2.8 Active power output according to the system frequency in the UK [4].
Figure 2.9 Power-frequency response curve for wind-following mode in Ireland [5].
Figure 2.10 Frequency control for WPPs in Denmark for minor downward regulation P
Delta
[7].
Figure 2.11 Frequency control for WPPs in Denmark for major downward regulation P
Delta
[7].
Figure 2.12 Time and magnitude limits for Category 3 rapid voltage changes in the UK [4].
Figure 2.13 Voltage recovery example of short-circuit faults cleared within 140 ms by two circuit breakers, as specified in the UK grid code for onshore WPPs [4].
Figure 2.14 Voltage recovery example of short-circuit faults cleared within 140 ms by three circuit breakers, as specified in the UK grid code for onshore WPPs [4].
Figure 2.15 LVRT requirements with voltage dips greater than 140 ms and up to 3 min for onshore WPPs in the UK [4].
Figure 2.16 UK FRT requirements for voltage dips on the LV side of the offshore platform of up to 140 ms [4].
Figure 2.17 UK FRT requirements for balanced voltage dips greater than 140 ms and up to 3 min [4].
Figure 2.18 FRT capability requirements for controllable WPPs in Ireland [5].
Figure 2.19 Danish LVRT requirements for WPPs with active power output greater than 1.5 MW [7].
Figure 2.20 Danish requirement for reactive power supply during LVRT for WPPs with active power output greater than 1.5 MW [7].
Figure 2.21 LVRT requirements in Spain [8].
Figure 2.22 Requirement for reactive power supply during LVRT in Spain [8].
Figure 2.23 LVRT requirements in Sweden for WPPs with installed capacity less than or equal to 100 MW [9].
Figure 2.24 LVRT requirements in Sweden for WPPs with installed capacity larger than 100 MW [9].
Figure 2.25 US LVRT requirements for WPPs [10].
Figure 2.26 LVRT requirements for WPPs in Quebec [11].
Chapter 3: Control of Doubly-fed Induction Generators for Wind Turbines
Figure 3.1 Schematic of a DFIG-based wind power generation system.
Figure 3.2 Equivalent circuit of DFigure U
s
, stator voltage vector; I
s
, stator current vector;
r
s
, stator resistance; , stator leakage reactance; U
r
, rotor voltage vector; I
r
, rotor current vector;
r
r
, rotor resistance; , rotor leakage reactance; E
m
, magnetizing voltage vector; I
m
, magnetizing current vector;
X
m
, magnetizing reactance;
r
m
, magnetizing resistance.
Figure 3.3 Power flow of a DFigure system.
Figure 3.4 Power flow of a DFigure system neglecting losses.
Figure 3.5 Grid-side converter structure.
Figure 3.6 PQ decoupled control strategy of the DFIG.
Figure 3.7 DFigure control diagram before connecting to the grid.
Figure 3.8 DFigure control diagram after connecting to the grid.
Figure 3.9 Universal bridge block.
Figure 3.10 Voltage space vectors.
Figure 3.11 Division of space.
Figure 3.12 Forming a circular flux trajectory.
Figure 3.13 Wind energy conversion system of a DFIG.
Figure 3.14 Electrical system of the DFIG.
Figure 3.15 DTC system of DFIG.
Figure 3.16 Flux sectors and voltage vectors in DTC.
Figure 3.17 Flux trajectory in DTC.
Figure 3.18 Space vectors and flux sectors in new DTC.
Figure 3.19 Flux trajectory in new DTC.
Figure 3.20 Simulation results: (a) conventional DTC; (b) new DTC.
Figure 3.21 Magnitude of flux: (a) conventional DTC; (b) new DTC.
Figure 3.22 Electromagnetic torque: (a) conventional DTC; (b) new DTC.
Figure 3.23 DC-link voltage: (a) conventional DTC; (b) new DTC.
Figure 3.24 Active powers in the DFigure system.
Figure 3.25 Reactive powers in the DFigure system.
Figure 3.26 DFigure with crowbar protection.
Figure 3.27 Passive crowbar circuit: (a) diode rectifier; (b) anti-parallel thyristor.
Figure 3.28 Active crowbar circuit.
Chapter 4: Optimal Control Strategies of Wind Turbines for Load Reduction
Figure 4.1 The normal turbulence model.
Figure 4.2 Force analysis of blade element.
Figure 4.3 The two-mass model of drivetrain .
Figure 4.4 Combined model based on Aerodyn, FAST, and Simulink.
Figure 4.5 Individual pitch control system based on root load measurements.
Figure 4.6 The simplified wind turbine model.
Figure 4.7 The control diagram block of IPC-1p.
Figure 4.8 The control diagram block of IPC-2p
Figure 4.9 Simulation results of individual pitch control: (a) turbulence wind speed; (b) blade root bending moment ; (c) wind wheel pitch moment ; (d) wind wheel yawing moment ; (e) drivetrain torque .
Figure 4.10 Spectrum of blade root bending moment.
Figure 4.11 Simulation waveform of generation power
Figure 4.12 The control diagram block for LQG.
Figure 4.13 The closed-loop poles of system.
Figure 4.14 Simulation results of LQG control: (a) turbulent wind speed; (b) electromagnetic torque; (c) blade 1 bending moment; (d) drivetrain torque; (e) drivetrain torque spectrum.
Figure 4.15 The simulation waveform of generated power.
Chapter 5: Modeling of Full-scale Converter Wind Turbine Generator
Figure 5.1 Structure diagram of FSC-WTG.
Figure 5.2 Structure diagram of direct-drive PMSG-based wind turbine.
Figure 5.3 Structure diagram of FSC-IG based wind turbine.
Figure 5.4 Two-mass model of transmission chain.
Figure 5.5 Drive system two-mass spring and damper model.
Figure 5.6
dq
equivalent models of SCIG: (a) equivalent circuit of
d-axis
: (b) equivalent circuit of
q
-axis.
Figure 5.7 PMSG equivalent circuit: (a) Equivalent circuit of
q
shaft; (b) Equivalent circuit of
d
shaft.
Figure 5.8 Simplified structure and equivalent circuit diagram of full scale converter: (a) simplified structure diagram; (b) equivalent circuit.
Figure 5.9 Control system of an FSC-WTG. SVRT: stator voltage reference frame; (RRF) rotor reference frame (RRF)
Figure 5.10 Block diagram of generator-side inverter control.
Figure 5.11 Vector chart for three generator-side converter control strategies: (a) maximum torque (b) unit power factor: (c) constant stator voltage.
Figure 5.12 Block diagram of generator-side converter control system.
Figure 5.13 Structure diagram of PWM voltage source converter at grid-side.
Figure 5.14 Block diagram of grid-side converter control system.
Figure 5.15 Grid-side converter transient voltage controller.
Figure 5.16 Block diagram of DC voltage coupling control system.
Figure 5.17 Simplified wiring diagram of simulation system.
Figure 5.18 Characteristic curve of wind farm without additional control after grid three-phase short-circuit fault (grounding impedance 10 Ω).
Figure 5.19 Characteristic curve of wind farm with additional transient voltage control at grid three-phase short-circuit fault (grounding impedance 10 Ω).
Figure 5.20 Characteristic curve of wind farm with additional DC voltage coupling control after grid three-phase short-circuit fault (Grounding impedance 10 Ω)
Chapter 6: Clustering-based Wind Turbine Generator Model Linearization
Figure 6.1 Power-controlled wind turbine model.
Figure 6.2 Operational regions of a wind turbine.
Figure 6.3 and
Figure 6.4 Regressors for identification of .
Figure 6.5 Regions of identification.
Figure 6.6 Regions of identification.
Figure 6.7 Regions of identification.
Figure 6.8 Wind speed variation.
Figure 6.9 Power reference during simulation.
Figure 6.10 State variable comparison under low-wind conditions.
Figure 6.11 Output variable comparison under low-wind conditions.
Figure 6.12 State variable comparison under high-wind conditions.
Figure 6.13 Output variable comparison under high-wind conditions.
Chapter 7: Adaptive Control of Wind Turbines for Maximum Power Point Tracking
Figure 7.1 Control system of variable speed WECS [2].
Figure 7.2 Optimal regimes characteristic (ORC) of variable speed WECS [2].
Figure 7.3 Generator control of WECS based on TSR.
Figure 7.4 Estimation of
.
Figure 7.5
curve.
Figure 7.6 Vector control of the SCIG.
Figure 7.7 The closed-loop adaptive controller [16].
Figure 7.8 Root locus for the choice of .
Figure 7.9 Root locus for the choice of .
Figure 7.10 Comparison of actual and estimated wind speed.
Figure 7.11 Comparison of in Scenario 1.
Figure 7.14 Comparison of in Scenario 2.
Figure 7.12 Comparison of in Scenario 1.
Figure 7.13 Comparison of in Scenario 2.
Chapter 8: Distributed Model Predictive Active Power Control of Wind Farms
Figure 8.1 Structure of D-MPC-based wind farm control.
Figure 8.2 Structure of D-MPC based wind farm control equipped with ESS.
Figure 8.3 Convergence comparison with different .
Figure 8.4 Wind speed variation of Wind Turbine 03.
Figure 8.5 Power generation of the wind farm: (a) in high winds; (b) in low winds.
Figure 8.6 Simulation results of WT 03 under the high-wind condition.
Figure 8.7 Simulation results of WT 03 under the low-wind condition.
Chapter 9: Model Predictive Voltage Control of Wind Power Plants
Figure 9.1 Wind farm configuration.
Figure 9.2 Control structure of a wind farm.
Figure 9.3 curve of a full-converter WTG.
Figure 9.4 Working principle of OLTC in MPC.
Figure 9.5 Power output of the wind farm.
Figure 9.6 Voltages of different buses within the wind farm (Scenario 1): (a) , (b) , (c) .
Figure 9.7 Var output of SVG (Scenario 1).
Figure 9.8 Voltages of different buses within the wind farm (Scenario 2): (a) , (b) , (c) .
Figure 9.9 Var output of SVG (Scenario 2).
Figure 9.10 Tap position of OLTC at the main substation (Scenario 2).
Chapter 10: Control of Wind Farm Clusters
Figure 10.1 Absolute production constraint [7].
Figure 10.2 Delta production constraint [7].
Figure 10.3 Balance regulation without and with automatic cancellation.
Figure 10.4 Stop regulation.
Figure 10.5 Power gradient constraint.
Figure 10.6 System protection.
Figure 10.7 Frequency regulation with and without previous downward regulation.
Figure 10.8 Flow of real-time active power control strategy of the wind farm cluster.
Figure 10.9 AGC scheme of a wind farm cluster.
Figure 10.10 Grid structure diagram of Baicheng region.
Figure 10.11 Tuanjie Wind Farm: (a) P–V curve and (b) V–Q curve.
Figure 10.12 Voltage change curve of the Shangyi Wind Power Collection Station.
Figure 10.13 Influence of wind turbine power factor on voltage: (a) POC voltage, (b) voltage curves at 40 km.
Figure 10.14 Reactive optimal control strategy diagram.
Figure 10.15 Secondary voltage control strategy diagram.
Figure 10.16 Wind farm primary voltage control strategy diagram.
Figure 10.17 Overall structure of wind farm reactive voltage control system.
Chapter 11: Fault Ride Through Enhancement of VSC-HVDC Connected Offshore Wind Power Plants
Figure 11.1 Flowchart of EV grid impact study.
Figure 11.2 Reactive current control of grid-side converter during a voltage dip in host power system.
Figure 11.3 Single-line representation of WPP and the WPP-side HVDC-VSC.
Figure 11.4 FRT control based on feedforward DC voltage control
Figure 11.5 Voltages at grid, DC and WPP side for Case 1
Figure 11.6 Active and reactive power at grid, DC and WPP side for Case 1
Figure 11.7 Voltages at grid, DC, and WPP sides for Case 2
Figure 11.8 Active and reactive power at grid, DC, and WPP sides for Case 2
Figure 11.9 Voltages at grid, DC, and WPP sides for Case 3.
Figure 11.10 Active and reactive power at grid, DC, and WPP sides for Case 3.
Figure 11.11 WPP-side converter currents in the
dq
reference frame and the total current.
Chapter 12: Power Oscillation Damping from VSC-HVDC-connected Offshore Wind Power Plants
Figure 12.1 High-level diagram of VSC-HVDC connection for WPPs.
Figure 12.2 VSC-HVDC converter electrical model for POD studies.
Figure 12.3 Generic block diagram of VSC-HVDC converter control.
Figure 12.4 Outer controller for onshore HVDC converter control.
Figure 12.5 Example of outer controller for offshore HVDC converter control.
Figure 12.6 Example of WPP controller.
Figure 12.7 Single-machine–infinite-bus system for simple POD investigations.
Figure 12.8 IEEE modified 12.bus system for POD verification.
Figure 12.9 PSS-like POD controller.
Figure 12.10 Steady-state phasor diagram for single-machine–infinite-bus system.
Figure 12.11 Variation in real and imaginary part of target pole: (a) P
e0
= 0.417 pu and (b) P
e0
= 0.833 pu.
Figure 12.12 Eigenvalue movement for real POD controller and varying gain: (a) K
A
= 1 pu, (b) K
A
= 40 pu.
Figure 12.13 Phasor-like diagram of electrical torques acting on SG rotor.
Figure 12.14 Selected results from non-linear simulation of POD control on IEEE 12.bus system.
Figure 12.15 Generalized closed-loop control block diagram for POD controller.
Figure 12.16 Generic Bode diagrams of open-loop transfer functions with perfect actuator.
List of Tables
Chapter 2: Grid Code Requirements for Wind Power Integration
Table 2.1 Reactive power/power factor requirement
Table 2.2 Continuous voltage operating range
Table 2.3 Frequency operating range
Table 2.4 Transmission system frequency and available active power settings for points A–E in Figure 2.9
Table 2.5 Transmission system frequency and active power ranges appropriate to Figure 2.9
Table 2.6 Limits of rapid voltage changes in the UK grid code [4]
Table 2.7 Requirements of recurring fault conditions in Denmark
Chapter 3: Control of Doubly-fed Induction Generators for Wind Turbines
Table 3.1 Switching Table in conventional DTC method
Table 3.2 Switching Table in new DTC method
Chapter 6: Clustering-based Wind Turbine Generator Model Linearization
Table 6.1 %RMSE under low-wind conditions
Table 6.2 %RMSE under high-wind conditions
Chapter 8: Distributed Model Predictive Active Power Control of Wind Farms
Table 8.1 Simulation statistics
Table 8.2 Simulation statistics
Table 8.3 Simulation statistics
Table 8.4 Simulation statistics
Table 8.5 Simulation statistics
Table 8.6 Simulation statistics
Table 8.7 Simulation statistics
Table 8.8 Simulation statistics
Table 8.9 Simulation statistics
Chapter 10: Control of Wind Farm Clusters
Table 10.1 Wind farm classification for real-time dispatch
Chapter 11: Fault Ride Through Enhancement of VSC-HVDC Connected Offshore Wind Power Plants
Table 11.1 Parameters of VSC-HVDC-connected WPP
Table 11.2 Parameters of the VSC-HVDC-connected WPP
Chapter 12: Power Oscillation Damping from VSC-HVDC-connected Offshore Wind Power Plants
Table 12.1 Control settings for ideal POD controller
Table 12.2 Per-unit SG power and voltage sensitivities to P and Q
Table 12.3 POD control parameters for real POD controller
Table 12.4 Calculated compensation and achieved performance for Q POD and K
A
= 40 pu
Table 12.5 Control parameters and resulting performance for POD implementation on VSC-HVDC-connected WPP in IEEE 12.bus system
Table 12.6 Realistic parameters for WT rotor, generator and shaft
Modeling and Modern Control of Wind Power
Edited by
Qiuwei Wu
Technical University of Denmark, Kgs. Lyngby, Denmark
Yuanzhang Sun
Wuhan University, China
This edition first published 2018
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Library of Congress Cataloging-in-Publication Data:
Names: Wu, Qiuwei, editor. | Sun, Yuanzhang, 1954- editor.
Title: Modeling and modern control of wind power / edited by Qiuwei Wu, Yuanzhang Sun.
Description: Hoboken, NJ : John Wiley & Sons, 2018. | Includes bibliographical references and index. |
Identifiers: LCCN 2017030336 (print) | LCCN 2017043924 (ebook) | ISBN 9781119236405 (pdf) | ISBN 9781119236399 (epub) | ISBN 9781119236269 (cloth)
Subjects: LCSH: Wind power-Mathematical models. | Wind power plants. | Wind turbines.
Classification: LCC TJ820 (ebook) | LCC TJ820 .M63 2017 (print) | DDC 621.31/2136-dc23
LC record available at https://lccn.loc.gov/2017030336
Cover Design: Wiley
Cover Image: © Stockr/Shutterstock
List of Contributors
Yongning Chi
China Electric Power Research Institute
Beijing, China
Lijun Hang
Hangzhou Dianzi University
China
Shuju Hu
Institute of Electrical Engineering
Chinese Academy of Sciences
Kim Høj Jensen
Siemens Wind Power A/S
Denmark
Guojie Li
Shanghai Jiaotong University
Shanghai, China
Yan Li
China Electric Power Research Institute
Beijing, China
Chao Liu
China Electric Power Research Institute
Beijing, China
Jacob Østergaard
Centre for Electric Power and Energy
Department of Electrical Engineering
Technical University of Denmark
Tony Wederberg Rasmussen
Centre for Electric Power and Energy
Department of Electrical Engineering
Technical University of Denmark
Ranjan Sharma
Siemens Wind Power A/S
Denmark
Lei Shi
NARI Technology Co., Ltd
Jiangsu, China
Bin Song
Institute of Electrical Engineering
Chinese Academy of Sciences
Yuanzhang Sun
Wuhan University
Wuhan, China
Haiyan Tang
China Electric Power Research Institute
Beijing, China
Xinshou Tian
China Electric Power Research Institute
Beijing, China
Ningbo Wang
Gansu Electric Power Corporation Wind Power Technology Center
Gansu, China
Linjun Wei
China Electric Power Research Institute
Beijing, China
Qiuwei Wu
Centre for Electric Power and Energy
Department of Electrical Engineering
Technical University of Denmark
Lorenzo Zeni
DONG Energy Wind Power A/S, Denmark
Haoran Zhao
Centre for Electric Power and Energy Department of Electrical Engineering
Technical University of Denmark
Qiang Zhou
Gansu Electric Power Corporation Wind Power Technology Center
Gansu, China
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Chapter 1Status of Wind Power Technologies
Haoran Zhao and Qiuwei Wu
Technical University of Denmark
1.1 Wind Power Development
Although wind power has been utilized by humans for more than 3000 years, the history of wind power for electricity production is only 120 years long.
In July 1887, Professor James Blyth (1839–1906) of Anderson's College, Glasgow built the first windmill for the production of electricity at Marykirk in Kincardineshire, Scotland [1]. The windmill was 10 m high, and was used to charge accumulators to power the lighting in the cottage. Around the same period, a wind turbine was designed and constructed in the winter of 1887-1888 by Charles F. Brush (1849–1929) in Cleveland, USA [2]. The rotor of Brush's wind turbine was 17 m in diameter and had 144 blades. The rated power was 12 kW. It was used either to charge a bank of batteries or to operate up to 100 incandescent light bulbs and various motors in Brush's laboratory.
A pioneer of modern aerodynamics, Poul la Cour (1846–1908) of Askov, Denmark, built the world's first wind tunnels for the purpose of aerodynamic tests to identify the best shape of the blades for turbines. Based on his experiments, he realized that wind turbines with fewer rotor blades were more efficient for electricity production. He designed the first four-blade wind turbine in 1891 [3].
The developments in the 20th century can be divided into two periods. From 1900–1973, the prices of wind-powered electricity were not competitive. The gradual extension of electrical networks and the availability of low-cost fossil fuels lead to the abandonment of wind turbines. Wind turbine generators (WTGs) were mainly used in rural and remote areas. Although several wind turbines in the hundred-kilowatt class were manufactured and installed for testing, due to high capital costs and reliability problems, they were not widely adopted.
The two oil crises in 1973 and 1979, with supply problems and price fluctuations for fossil fuels, spurred the adoption of non-petroleum energy sources. As an alternative to fossil fuels, wind power was once again put on the agenda. European countries and US government started to invest in research into large commercial wind turbines. The world's first multi-megawatt wind turbine was constructed in 1978, and pioneered many technologies now used in modern wind turbines. From 1975 through to the mid-1980s, NASA developed 3.2 MW and 4 MW wind turbines. Although they were sold commercially, none of these were ever put into mass production. When oil prices declined, electricity generated by wind power became uneconomical and many manufacturers left the business.
At the beginning of the 21st century, although fossil fuels were still relatively cheap, concerns over energy security, global warming, and eventual fossil fuel depletion increased, and this led to an expansion of interest in renewable energy. The wind power industry has since achieved rapid development.
From the point of view of global capacity, according to statistics from the Global Wind Energy Council (GWEC), the global annual and cumulative installed wind capacities for the past ten years are as illustrated in Figures 1.1 and 1.2, respectively. In 2015, the global wind power industry installed 63.5 GW of capacity, representing annual market growth of 22%. By the end of 2015, the total installed capacity reached 432.4 GW, representing cumulative market growth of 17%. As estimated by International Energy Agency (IEA), that figure will reach 2016 GW by 2050, representing 12% of global electricity usage [5].
Figure 1.1 Global annual installed wind capacity 2005-2015 [4].
Figure 1.2 Global cumulative installed wind capacity 2005-2015 [4].
From the point of view of development in each country, more than 83 countries around the world were using wind power on a commercial basis by 2010. The top ten countries in terms of 2015-installed and cumulative wind power capacities at 2015 are illustrated in Figures 1.3 and 1.4, respectively. More than half of all new installed wind power was added outside the traditional markets of Europe and North America. Asia has been the world's largest regional market for new wind power development, with capacity additions of 33.9 GW. China maintained its leadership position. China accounted for nearly half of the installations (48.4%) and its total wind power reached 145.1 GW.
Figure 1.3 Newly installed capacity during 2015 [4].
Figure 1.4 Cumulative capacities at 2015 [4].
In many countries, relatively high levels of wind power penetration have been achieved. Figure 1.5 presents the estimated wind power penetration in leading wind markets [6]. The installed capacity is estimated to supply around 40% of Denmark's electricity demand, and between 20% to 30% in Portugal, Ireland, and Spain, respectively. Denmark has a even more ambitious target of 50% by 2020. In the United States, 5.6% of the nation's electricity demand is estimated to be covered by the wind power. On a global basis, the contribution of wind power is estimated to be around 4.3% [6].
Figure 1.5 Wind power penetration in leading wind markets in 20142015 [6].
1.2 Wind Turbine Generator Technology
As at 2015, the largest wind turbine is the 8 MW capacity Vestas V164, for offshore use. By 2014, over 240,000 commercial-sized wind turbines were operating in the world, and these met 4% of the world's electricity demand. WTG-based wind energy conversion systems (WECS) can be divided into the following four main types [7, 8].
1.2.1 Type 1
Type 1 generators are directly grid-connected induction generators (IGs) with fixed rotor resistance. An example is the squirrel cage induction generator (SCIG). As illustrated in Figure 1.6, the wind turbine rotor (WTR) is connected to the IG via a gearbox (GB). Most Type 1 WTGs are equipped with mechanically switched capacitor (MSC) banks, which provide reactive power compensation. As the protection device, the main circuit breaker (CB) disconnects the generator and capacitor from the grid in the event of a fault. Through a step-up transformer (TR), the WTG is connected to the grid.
Figure 1.6 Structure of Type 1 WTG [8]. Refer to main text for explanation of acronyms.
Because of the direct connection to the grid, the IG operates at its natural mechanical characteristic, with an accentuated slope (corresponding to a small slip, normally 1–2%) from the rotor resistance [7]. The rotational speed of the IG is close to the synchronous speed imposed by grid frequency, and is not affected significantly by wind variation.
1.2.2 Type 2
Type 2 generators are directly grid-connected IGs with variable rotor resistance (VRR).
Figure 1.7 illustrates the general structure of a Type 2 WTG. As an evolution of Type 1 WTGs, using regulation through power electronics, the total (internal plus external) rotor resistance is adjustable. In this way, the slip of the generator can be controlled, which affects the slope of the mechanical characteristic. The range of dynamic speed variation is decided by the additional resistance. Usually, the control range is up to 10% over the synchronous speed.
Figure 1.7 Structure of Type 2 WTG [8]. Refer to main text for explanation of acronyms.
1.2.3 Type 3
Type 3 generators are double-fed induction generators (DFIGs). As illustrated in Figure 1.8, the DFIG is an induction generator with the stator windings connected directly to the three-phase, constant-frequency grid and the rotor windings connected to back-to-back voltage source converters (VSCs), including a rotor-side converter (RSC) and grid-side converter (GSC) [9]. They are decoupled with a direct current (DC) link. Conventionally, the RSC controls the generator to regulate the active and reactive power, while the GSC controls the DC-link voltage to ensure DC voltage stability.
Figure 1.8 Structure of Type 3 WTG [8]. Refer to main text for explanation of acronyms.
The power flow of the stator is always from wind turbine to grid. However, the power flow of the rotor is dependent on the operating point:
If the slip is negative (over-synchronous operation), it feeds power into the grid.
If the slip is positive (sub-synchronous operation), it absorbs power from the grid.
In both cases, the power flow in the rotor is approximately proportional to the slip. By regulation of the generator behaviour through the GSC controller, the rotation speed is allowed to operate over a larger, but still restricted range (normally 40%).
1.2.4 Type 4
Type 4 WTGs have the wind turbine connected fully through a power converter. Figure 1.9 shows the general structure of Type 4 WTG. The generator type can be either an induction generator or a synchronous generator. Furthermore, the synchronous generator can be either a wound-rotor synchronous generator (WRSG) or a permanent-magnet synchronous generator (PMSG). Currently, the latter is widely used by the wind turbine industry. The back-to-back VSC configuration is used. The RSC ensures the rotational speed is adjusted within a large range, whereas the GSC transfers the active power to the grid and attempts to cancel the reactive power consumption [7].
Figure 1.9 Structure of Type 4 WTG [8]. Refer to main text for explanation of acronyms.
The PMSG configuration is considered a promising option. Due to its self-excitation property, its gives high power factors and efficiency. As it is supplied by permanent magnets, a PMSG does not require an energy supply for excitation. Moreover, since the salient pole of a PMSG operates at low speeds, the gearbox (Figure 1.9) can be removed. This is a big advantage of PMSG-based WECS, as the gearbox is a sensitive device in wind power systems. The same thing can be achieved using direct driven multipole PMSGs (DD-PMSGs) with large diameters.
1.2.5 Comparison
These four WTG types can also be classified into two categories according to the rotor speed control criterion: fixed-speed wind turbines (FSWTs), including Type 1, and variable-speed wind turbines (VSWTs), including Types 2–4 [10].
FSWTs have the advantage of being simple, robust and reliable, with simple and inexpensive electric systems. They are well-proven in operation. Moreover, they can naturally provide the inertial response. However, as FSWTs have limited controllability of rotational speed, the captured aerodynamic efficiency is restricted. Due to the fixed-speed operation, mechanical stress is important. All fluctuations in wind speed are transmitted into mechanical torque and then, as electrical fluctuations, into the grid.
Due to the regulation of rotor speed within a larger range, VSWTs, especially Types 3 and 4, are highly controllable, allowing maximum power extraction over a large range of wind speeds. In addition, the active and reactive power control can be fully decoupled and implemented separately, and they are therefore they are more flexible. VSWTs dominate the marketplace, especially in the megawatt class. Due to the electrical decoupling between the generator and the grid, they cannot contribute to the power system apparent inertial as conventional synchronous generators [11]. However, the inertial response can be emulated by an additional power or torque loop [12–15].
1.2.6 Challenges with Wind Power Integration
Due to the inherent variability and uncertainty of the wind, the integration of wind power into the grid has brought challenges in several different areas, including power quality, system reliability, stability, and planning. The impact of each is largely dependent on the level of wind power penetration in the grid [16].
Impact on Power Quality
Power quality is evaluated as a deviation from the normal sinusoidal voltage and current waveforms in power system network. Power quality distortions of a power system include flickers and harmonic distortions.
Flickers are periodic voltage and frequency variations, typically of between 0.5 and 25 Hz. The oscillatory output power produced by WTGs can cause flickers in a power system. Fluctuations due to the tower shadow and turbulence effects in the wind may cause flickers too. The IEC 61400-21 standard furnishes a measurement procedure to calculate the flicker impact of wind turbines.
Harmonics can be injected on both the generation and consumer sides. On the consumer side, harmonics are caused by non-linear loads. On the generation side, sources of harmonics include flexible alternating current transmission systems (FACTS), such as reactive power compensators and power electronics devices. The power electronic converters used by VSWTs are considered sources of harmonics.
Impact on System Reliability
The uncertainty of wind generation will increase the requirement for operating reserve, which will in turn increase generation costs. When the wind penetration level is low, the wind power fluctuation is comparable to existing load fluctuations. Committed conventional generators, such as thermal or hydro units, have sufficient load-tracking capability, so no additional operating reserve is required. However, load balancing becomes challenging at high wing-power penetration levels. An extra reserve of 3–6% of the rated capacity of the wind plant is required at 10% wind penetration and 4–8% for 20% wind penetration.
Impact on System Stability
Frequency stability
Conventional synchronous generators can provide inertia response, which plays a significant role in stabilizing system frequency during a transient scenario. The inertia value dictates the frequency deviations due to a sudden change in the generation and load power balance. It affects the eigenvalues and vectors that determine the stability and mode shape of the transient response [17].
The contributions to the system inertia of WTGs are dependent on the WTG type. Due to the direct connection of the power system, fixed-speed induction generators can provide inertia response. Modern VSWTs, whose rotation speed is normally decoupled from grid frequency by a power electronic converter, may decrease the system inertia [18]. With high wind power penetration, this decrease aggravates the grid frequency instability.
Voltage stability
Many power system faults are cleared by the relay protection of the transmission system, either by disconnection or by disconnection and fast reclosure. There is a short period with a voltage drop beyond a specified threshold, followed by a period when the voltage returns. Previously, when the voltage dip occurred, the wind turbine was simply disconnected from the grid. When the fault was cleared and the voltage returned to normal, the wind turbine was reconnected. When the wind power penetration level is low, the impact on system stability is limited. However, with high levels of wind penetration, if the entire wind farm is suddenly disconnected while at full generation, the system will lose further production capability [17]. This can lead to a further large frequency and voltage drop and possibly complete loss of power. It is very important to maintain the connection of WTGs when there are disturbances in the network. Therefore, modern WTGs are required to have the fault ride-through (FRT) capability by grid codes.
Since large wind farms are mainly located in areas far from load centres, the short-circuit ratio (SCR) is small [19], and the grid at the connection point is weak. Voltage fluctuations caused by the intermittent power of the wind farms are large.
Impact on System Planning
As wind resources are often located far from load centres, it is critical to develop sufficient transmission to transport wind power to load centres. Old transmission lines must be updated. On the one hand, transmission planning processes are highly dependent on regional politics. The generation capacity, transmission location and load size are different from one place to another. These disparities make the development of transmission for wind power contentious and complex. On the other hand, in order to transfer variable and unpredictable wind power, new requirements for transmission technology arise [20].
Microgrids are considered as an alternative vision of the future grid, with energy generated and consumed locally. They can significantly reduce the long-distance energy transmission requirement and transmission losses. The electricity grid could be conceptualized as a collection of independent microgrids [20].
1.3 Conclusion
There is potential for wind energy to play an important role in future energy supply. With the development of wind turbine technology, wind power will become more controllable and grid-friendly. It is desirable to make wind farms operate as conventional power plants. To achieve this objective, more advanced control strategies for both wind turbines and wind farms are required.
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