Modern Control of DC-Based Power Systems: A Problem-Based Approach addresses the future challenges of DC Grids in a problem-based context for practicing power engineers who are challenged with integrating DC grids in their existing architecture. This reference uses control theory to address the main concerns affecting these systems, things like generation capacity, limited maximum load demands and low installed inertia which are all set to increase as we move towards a full renewable model. Offering a new approach for a problem-based, practical approach, the book provides a coordinated view of the topic with MATLAB®, Simulink® files and additional ancillary material provided.
Author(s): Marco Cupelli, Antonino Riccobono, Markus Mirz, Mohsen Ferdowsi, Antonello Monti
Publisher: Academic Press
Year: 2018
Language: English
Pages: 302
City: London
Front Cover
Modern Control of DC-Based Power Systems
Copyright Page
Contents
List of Figures
List of Tables
List of Contributors
List of Acronyms
Symbols Used in this Work
Preface
References
Introduction
References
Further Reading
1. Overview—Voltage Stabilization of Constant Power Loads
1.1 Constant Power Load Connected to a DC Bus
1.2 Compensating CPLs by Passive Components
1.3 Compensating CPLs With Load Side Control
1.4 Compensating CPLs With DC Bus Control
1.5 Summary
References
Further Reading
2. Small-Signal Analysis of Cascaded Systems
2.1 MVDC System Considerations Influencing Voltage Stability
2.2 Converter Model
2.2.1 Single Converter—Open Loop
2.2.2 Single Converter—Closed Loop (VMC)
2.2.3 Single Converter Closed Loop (PCMC)
2.3 Cascaded System (VMC)
2.4 Load Models
2.4.1 Constant Power Load Model
2.4.2 First-Order Lag Impedance
2.4.3 First-Order Unstable Impedance
2.4.4 Nonminimum Phase Impedance
2.4.5 Generalized Load Impedance
2.5 Linear Control Design and Validation
2.5.1 Practical PI and PID Control Design
2.5.1.1 Modeling and Design Procedure of Current Mode Control With PI Controllers
2.5.1.2 Modeling and Design Procedure of Voltage Mode Control With PID Controller
2.5.1.3 Simulation Example
2.5.2 Network Analyzer Technique
2.6 Small-Signal Stability Analysis of Cascade Systems
2.6.1 The Nyquist Stability Criterion and Its Practical Usage
2.6.1.1 Simulation Example
2.6.1.1.1 Stable Cases
2.6.1.1.2 Unstable Cases
2.6.2 Online Wideband System Identification Technique
2.6.2.1 The Implementation of the WSI Technique
2.6.2.1.1 PRBS Generation
2.6.2.1.2 Data Acquisition
2.6.2.1.3 Fast Fourier Transform
2.6.2.1.4 Calculation of Nonparametric Impedance
2.6.2.1.5 Fitting Routine
2.6.2.2 Performance of the WSI Technique and Overcoming Practical Challenges
2.6.2.3 Simulation Example
2.7 Summary
References
3. Background
3.1 Frequency Response Approaches
3.2 Nyquist Stability Criterion
3.3 Bode Diagrams
3.4 Linear State-Space
3.4.1 Controllability
3.4.2 Observability
3.4.3 Pole Placement
3.5 Observer
3.6 Droop
3.6.1 Voltage Droop
3.6.2 Influence of Droop Coefficients on the Overall System Dynamics
References
4. Generation Side Control
4.1 MVDC Shipboard Power Systems
4.2 State-Space Model
References
Further Reading
5. Control Approaches for Parallel Source Converter Systems
5.1 Linearizing State Feedback
5.1.1 Procedure of Linearizing State Feedback
5.1.2 Application to MVDC System
5.1.3 Simulation Results
5.1.3.1 Cascaded System
5.1.3.2 Shipboard Power System
5.2 Synergetic Control
5.2.1 Procedure of Synergetic Control
5.2.2 Application to MVDC System
5.2.3 Simulation Results
5.2.3.1 Cascaded System
5.2.3.2 Shipboard Power System
5.3 Immersion and Invariance Control
5.3.1 The Immersion and Invariance Stabilization
5.3.2 Example
5.3.3 Application to MVDC System
5.3.4 Simulation Results
5.3.4.1 Cascaded System
5.3.4.2 Shipboard Power System
5.4 Decentralized Controls
5.4.1 Procedure of Observer-Based Control
5.4.1.1 Linear Quadratic Regulator
5.4.1.2 Kalman Filter
5.4.1.3 Augmented Kalman Filter
5.4.1.4 Shaping Filter
5.4.2 Application to Decentralized Controlled MVDC System (LQG + Virtual Disturbance)
5.4.2.1 LQG – Set-point Trajectory
5.4.2.2 Augmented Local Kalman Filter
5.4.3 Application to Centralized Controlled MVDC System (LQG + Virtual Disturbance)
5.4.4 Simulation Results
5.4.4.1 Cascaded System
5.4.4.2 Shipboard Power System
5.5 Backstepping Based Control
5.5.1 Theory Behind Backstepping
5.5.1.1 Lyapunov
5.5.1.2 Control Lyapunov Function
5.5.2 Procedure of Backstepping
5.5.3 Application to MVDC System – Backstepping With Virtual Disturbance
5.5.4 Simulation Results
5.5.4.1 Cascaded System
5.5.4.2 Shipboard Power System
5.6 Adaptive Backstepping Control
5.6.1 Procedure Adaptive Backstepping
5.6.2 Application to MVDC System – Adaptive Backstepping With Power Estimation
5.6.3 Simulation Results
5.6.3.1 Cascaded System
5.6.3.2 Shipboard Power System
5.7 H∞ Optimal Control (Contributor Sriram Karthik Gurumurthy)
5.7.1 Development of H∞ Control
5.7.2 Preliminaries
5.7.2.1 H2 Norm
5.7.2.2 H∞ Norm
5.7.3 Linear Fractional Transformation
5.7.3.1 H2 Optimal Control Problem
5.7.3.2 H∞ Optimal Control Problem
5.7.4 Weighted Sensitivity H∞ Control
5.7.4.1 Generalized Plant Modeling
5.7.4.2 Description of Weighting Functions
5.7.5 Application to MVDC System
5.7.5.1 Design of Weighting Functions
5.7.6 Simulation Results
5.7.6.1 Cascaded System
5.7.6.2 Shipboard Power System
5.7.6.3 Impact of Measurement Noise
5.8 Sliding Mode Control
5.8.1 Design Approach
5.8.2 Dynamics in the Sliding State
5.8.3 Proof of Robustness
5.8.4 Application to DC–DC Converters
5.8.5 Simulation Results
5.8.5.1 Cascaded System
5.8.5.2 Shipboard Power System
5.9 Summary
References
Further Reading
6. Simulation
6.1 Cascaded System Evaluation
6.2 Shipboard Power System
6.2.1 Load Sharing
6.2.2 Averaged Model
6.2.3 Switched Converter Model
6.3 Summary
References
7. Hardware In the Loop Implementation and Challenges
7.1 Introduction
7.2 The Hardware in the Loop
7.3 Discretization
7.4 Simulation Case Shipboard Power System
References
Further Reading
Index
Back Cover
