Distributed Optimal Control of Large-Scale Wind Farm Clusters : Optimal Active and Reactive Power Control, and Fault Ride Through

Distributed Optimal Control of Large-Scale Wind Farm Clusters: Optimal Active and Reactive Power Control, and Fault Ride Through, a new volume in the Elsevier Wind Energy Engineering series, explores the latest advances in distributed optimal control of large-scale wind farm clusters, also describin...

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Bibliographic Details
Corporate Author:	ScienceDirect (Online service)
Format:	eBook
Language:	English
Published:	Academic Press, 2025.
Series:	Wind energy engineering series
Subjects:	Wind power plants. Centrales éoliennes. wind power plants. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Intro
Distributed Optimal Control of Large-Scale Wind Farm Clusters
Copyright
Contents
Foreword
Part One: Introduction
Chapter One: Introduction of large-scale wind power integration
1.1. Centralized and distributed/decentralized optimal operation
1.2. Active power control, active and reactive power control, voltage control
1.2.1. Voltage control
1.2.2. Fatigue load suppression
1.3. Synthetic inertial response
1.4. Enhancing high-voltage ride-through
1.5. Hierarchical event-triggered coordinated control
References
Part Two: Optimal active power control of large-scale wind farm clusters
Chapter Two: Bi-level decentralized active power control for large-scale wind farm cluster
2.1. Introduction
2.2. Bi-level control architecture
2.2.1. Configuration of a voltage-source-converter high-voltage-direct-current connected WFC
2.2.2. Concept of the bi-level DAPC
2.3. Consensus-based distributed active power dispatch for WFC
2.3.1. Graph theory
2.3.2. Distributed estimation of available wind power of wind farms
2.3.3. Distributed active power dispatch of WFC
2.4. Centralized MPC-based active power control of a wind farm
2.4.1. Predictive model of a WT
2.4.2. MPC formulation
2.4.3. Objective function
2.4.4. Constraints
2.5. Case study
2.5.1. Test system
2.5.2. Upper-level control performance
2.5.3. Lower-level control performance
2.6. Conclusion
References
Chapter Three: Optimal active power control based on MPC for DFIG-based wind farm equipped with distributed energy storag ...
3.1. Introduction
3.2. Control scheme architecture
3.2.1. Wind farm configuration
3.2.2. Control concept
3.3. DFIG system model
3.3.1. RSC model
3.3.2. GSC model
3.3.3. ESS model
3.3.4. WT mechanical system model ESS model
3.3.5. Wind farm model.
3.4. Coordinated control for wind farm equipped with distributed ESSs
3.4.1. Energy management for ESSs
3.4.2. Objective function for the first stage
3.4.3. Objective function for the second stage
3.5. Case study
3.5.1. Test system
3.5.2. Control performance
3.6. Discussion
3.7. Conclusion
Appendix A. Optimal active power control for a wind farm without ESSs
References
Chapter Four: Hierarchical active power control of DFIG-based
4.1. Introduction
4.2. Control scheme architecture
4.2.1. Wind farm configuration
4.2.2. Control concept
4.3. DFIG system model
4.3.1. RSC model
4.3.2. ESS model
4.3.3. WT mechanical system model
4.3.4. Wind farm model
4.4. Hierarchical control based on ADMM
4.4.1. Objective function
4.4.2. Mode 1
4.4.3. Mode 2
4.4.4. Constraints
4.4.5. Hierarchical active power control based on ADMM
4.5. Case study
4.5.1. Dynamic control performance
4.5.2. Static performance
4.6. Conclusion
References
Chapter Five: Hierarchical optimal control for synthetic inertial response of wind farm based on alternating direction me ...
5.1. Introduction
5.2. Control architecture
5.2.1. Configuration of a wind farm
5.2.2. Control concept
5.3. Synthetic inertial response model for wind farm
5.3.1. Synthetic inertial response controller
5.3.2. WT model
5.3.3. Wind energy loss
5.3.4. Wind farm model
5.3.5. Objective function
5.4. Hierarchical solution method for the synthetic inertial response
5.4.1. ADMM-based hierarchical optimization problem
5.4.1.1. Formulation
5.4.2. Hierarchical solution method based on ADMM
5.5. Case study
5.5.1. Test system
5.5.2. Control performance
5.6. Conclusion
References
Part Three: Optimal active and reactive power control of large-scale wind farm clusters.
Chapter Six: Bi-level decentralized active and reactive power control for large-scale wind farm cluster
6.1. Introduction
6.2. Bi-level control architecture
6.2.1. Configuration of a WFC
6.2.2. Concept of the bi-level DARPC
6.3. Consensus-based distributed active power and reactive power dispatch for WFC
6.3.1. Graph theory
6.3.2. Distributed active power control of WFC
6.3.3. Distributed reactive power control of WFC
6.3.3.1. Equivalent model of WFC
6.3.3.2. Reactive power reference calculation with OLTC
6.3.3.3. Reactive power control based on consensus protocol
6.4. Centralized MPC-based active and reactive power control of wind farm
6.4.1. Modeling of wind farm
6.4.2. Sensitivity coefficient calculation
6.4.3. MPC formulation for active and reactive power control of wind farm
6.4.3.1. Objective function
6.4.3.2. Constraints
6.5. Case study
6.5.1. Test system
6.5.2. Control performance under normal operation
6.6. Conclusion
Appendix
CARPC method
References
Chapter Seven: Two-tier combined active and reactive power controls for VSC-HVDC-connected large-scale wind farm cluster ...
7.1. Introduction
7.2. Distributed active and reactive power control structures
7.2.1. Structure of a VSC-HVDC-connected WFC
7.2.2. TCARPC concept
7.3. Distributed active and reactive power controls for WFC
7.3.1. Distributed active power control of WFC
7.3.2. Voltage sensitivity calculation
7.3.3. Predictive model of WFs
7.3.4. MPC formulation
7.3.5. ADMM-based solution method
7.4. Hierarchical active and reactive power controls for WFS
7.4.1. Modeling of WF
7.4.2. MPC formulation
7.4.3. ADMM-based solution
7.5. Case study
7.5.1. Control performance
7.6. Conclusion
References.
Chapter Eight: Distributed optimal active and reactive power control for wind farms based on ADMM
8.1. Introduction
8.2. DARPC control architecture
8.2.1. Configuration of the wind farm
8.2.2. Concept of the ADMM-based DARPC
8.3. Centralized problem formulation
8.3.1. Linearized DistFlow model of the WF
8.3.2. Optimization problem formulation for the WF
8.4. Distributed optimal control method
8.4.1. Decomposed optimization subproblem
8.4.2. Distributed solution method based on ADMM
8.4.3. Iterative solution process
8.5. Simulation results
8.5.1. Test system
8.5.2. Control performance of the DARPC scheme
8.6. Conclusion
References
Chapter Nine: ADMM-based distributed active and reactive power control for regional AC power grid with wind farms
9.1. Introduction
9.2. Control strategy architecture
9.2.1. System configuration
9.2.2. Strategy concept
9.3. TS optimization model
9.3.1. The objective function in TS
9.3.2. The constraints in TS
9.3.3. Convex relaxation of OPF in TS
9.3.4. Transformation of the objective function
9.3.5. Transformation of the constraints
9.4. WF optimization model
9.5. ADMM formulation for the whole system
9.6. Case study
9.6.1. Test system
9.6.2. Control performance
9.7. Conclusion
References
Part Four: Optimal voltage control of large-scale wind farm clusters
Chapter Ten: Distributed voltage control based on ADMM for large-scale wind farm cluster connected to VSC-HVDC
10.1. Introduction
10.2. DVC control architecture
10.2.1. Configuration of a VSC-HVDC connected WFC
10.2.2. Control concept
10.3. Distribution control design for WFC
10.3.1. Model of WFC connected to VSC-HVDC
10.3.2. Sensitivity coefficient calculation
10.3.3. Sensitivity coefficient calculation.
10.3.4. Sensitivity coefficient calculation
10.4. Wind farm control with ADMM
10.4.1. Modeling of wind farm
10.4.2. Modeling of wind farm
10.4.3. Objective function for wind farm voltage control
10.4.4. Voltage control based on ADMM
10.5. Case study
10.5.1. Test system
10.5.2. Control performance
10.6. Conclusion
References
Chapter Eleven: Distributed optimal voltage control for VSC-HVDC-connected large-scale wind farm cluster based on analyti ...
11.1. Introduction
11.2. Control architecture
11.2.1. Configuration of WFC
11.2.2. Control concept
11.3. Voltage control of large-scale WFC
11.3.1. WFCVSC and WT model
11.3.2. Objective function
11.4. Distributed solution method based on ATC
11.4.1. Optimization problem of the WFCVSC controller
11.4.2. Optimization problem of the Sub-WF controller
11.4.3. ATC-based solution method
11.5. Case study
11.5.1. Test system
11.5.2. Control performance
11.6. Conclusion
References
Chapter Twelve: Adaptive droop-based hierarchical optimal voltage control scheme for VSC-HVDC-connected offshore wind farm
12.1. Introduction
12.2. Control architecture
12.2.1. WF topology
12.2.1.1. Control concept
12.3. Wind farm model with droop control
12.3.1. WFVSC and WT model
12.3.2. Wind farm model
12.3.3. MPC-based droop control optimization problem formulation
12.4. Optimization problem with droop control
12.4.1. Constraint
12.4.2. Stability analysis
12.4.3. ADMM-based hierarchical solution
12.5. Case study
12.5.1. Test system
12.5.2. Control performance
12.6. Discussion
12.7. Conclusion
References
Chapter Thirteen: Distributed optimal voltage control strategy for AC grid with DC connection and offshore wind farms bas ...
13.1. Introduction
13.2. Control strategy architecture.