John Wiley & Sons Microgrid Dynamics and Control Cover This book discusses relevant microgrid technologies in the context of integrating renewable energy a.. Product #: 978-1-119-26367-8 Regular price: $144.86 $144.86 Auf Lager

Microgrid Dynamics and Control

Bevrani, Hassan / François, Bruno / Ise, Toshifumi

Cover

1. Auflage September 2017
720 Seiten, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-119-26367-8
John Wiley & Sons

Jetzt kaufen

Preis: 155,00 €

Preis inkl. MwSt, zzgl. Versand

Weitere Versionen

epubpdf

This book discusses relevant microgrid technologies in the context of integrating renewable energy and also addresses challenging issues. The authors summarize long term academic and research outcomes and contributions. In addition, this book is influenced by the authors' practical experiences on microgrids (MGs), electric network monitoring, and control and power electronic systems. A thorough discussion of the basic principles of the MG modeling and operating issues is provided. The MG structure, types, operating modes, modelling, dynamics, and control levels are covered. Recent advances in DC microgrids, virtual synchronousgenerators, MG planning and energy management are examined. The physical constraints and engineering aspects of the MGs are covered, and developed robust and intelligent control strategies are discussed using real time simulations and experimental studies.

Foreword xix

Preface xxi

Acknowledgments xxvii

1 Grid-connected Renewable Energy Sources 1

1.1 Introduction 1

1.2 Renewable Power Generation 3

1.2.1 Renewable Energy Development 5

1.3 Grid-connectedWind Power 6

1.3.1 Wind Power GeneratorWithout Power Electronic Converters 7

1.3.2 Wind Power Generator Using Partial-Scale Power Electronic Converters 7

1.3.3 Wind Power Generator Using Full-Scale Power Electronic Converters 7

1.4 Grid-Connected PV Power 35

1.4.1 Solar Power Generators with Embedded Energy Storage Systems 36

1.4.2 Solar Energy Conversion System: Modeling, Control, and Analysis 38

1.4.3 Experimental Results 55

1.4.4 Control of Grid-Connected Solar Power Inverters: A Review 59

1.5 Summary 66

References 66

2 Renewable Power for Control Support 69

2.1 Introduction 69

2.2 Wind-Energy-based Control Support 73

2.2.1 Wind Turbines Inertial Response 73

2.2.2 Study on a Real Isolated Power System 77

2.2.3 Primary Frequency and Inertial Controls 81

2.2.4 Using Secondary Control 89

2.3 Renewable Primary Power Reserve 89

2.3.1 InstantaneousWind Power Reserve 89

2.3.2 An Evaluation on the Real Case Study 92

2.3.3 Comparison of the Reserve Allocation Strategies 96

2.4 PV-Energy-Based Control Support 102

2.5 Integration of Renewable Energy SystemsThrough Microgrids 105

2.5.1 A Solution for Renewable Power Penetration 105

2.5.2 Microgrids in Future Smart Grids 108

2.6 Summary 112

References 113

3 Microgrids: Concept, Structure, and Operation Modes 119

3.1 Introduction 119

3.2 Microgrid Concept and Structure 125

3.3 Operation Modes 129

3.4 Control Mechanism of the Connected Distributed Generators in a

Microgrid 130

3.4.1 Speed Control of Classical Distributed Generators 130

3.4.2 Control of Inverter-based Distributed Generators 131

3.5 Contribution in the Upstream Grid Ancillary Services: Frequency

Control Support Example 137

3.5.1 Participation in the Frequency Regulation 138

3.5.2 Power Dispatching 142

3.5.3 Simulation Results 147

3.6 Microgrids Laboratory Technologies 147

3.6.1 Hardware-in-the-loop-based Microgrid Laboratory 152

3.6.2 Participant Laboratories to Provide the Present Book 157

3.7 Summary 160

References 160

4 Microgrid Dynamics andModeling 165

4.1 Introduction 165

4.2 Distribution Network (Main Grid) and Connection Modeling 168

4.2.1 Distribution Network Modeling 168

4.2.2 Modeling of Connection Between the Main Grid and the Microgrid 174

4.3 Overall Representation of the Grid-Connected Microgrid 178

4.3.1 Microgrid Bus 178

4.3.2 Global Architecture Representation 178

4.3.3 Microgrid Representation in the Islanded Operation Mode 179

4.4 Microgrid Components Dynamics and Modeling 182

4.4.1 PV Model 182

4.4.2 Energy Storage Systems Modeling 186

4.4.3 Power Electronic Converters 193

4.5 Simplified Microgrid Frequency Response Model 198

4.5.1 Example 1 199

4.5.2 Example 2 201

4.6 A Detailed State-Space DynamicModel 203

4.6.1 MathematicalModeling 203

4.6.2 Simulation Example 207

4.6.3 Closed-Loop State-Space Model 210

4.7 Microgrid Dynamic Modeling and Analysis as a Multivariable System 211

4.7.1 State-space Modeling 212

4.7.2 Dynamic Analysis 215

4.8 Summary 217

References 217

5 Hierarchical Microgrid Control 221

5.1 Introduction 221

5.2 Microgrid Control Hierarchy 225

5.2.1 Local Control 227

5.2.2 Secondary Control 228

5.2.3 Central/Emergency Control 229

5.2.4 Global Control 231

5.3 Droop Control 233

5.3.1 Droop Characteristic in Conventional Power Systems 233

5.3.2 Droop Control in Inverter-based Distributed Generators 235

5.3.3 Virtual Impedance Control 241

5.4 Hierarchical Power Management and Control 243

5.4.1 Operation Layers and Control Functions 244

5.4.2 Timescale Analyzing and Implementation Constraints 245

5.5 Design Example 252

5.5.1 Power Dispatching 253

5.5.2 Hardware-In-the-Loop Test Results 254

5.5.3 Test Procedure 257

5.6 Summary 262

References 263

6 DC Microgrid Control 267

6.1 Introduction 267

6.2 DC Microgrid for a Residential Area 270

6.2.1 System Configuration and Operation 270

6.2.2 Voltage Clamp Control 273

6.2.3 Disconnection/Reconnection from/to the Utility Grid 273

6.3 Low-voltage Bipolar-type DC Microgrid 275

6.4 Stability Evaluation 277

6.5 Experimental Study and Results 280

6.5.1 Experimental System 280

6.5.2 Voltage Sag of the Utility Grid 284

6.5.3 Disconnection/Reconnection from/to the Utility Grid 284

6.6 A Voltage Control Approach 286

6.6.1 Case Study and Voltage Control System 286

6.6.2 Energy Storage System Control 290

6.7 Simulation Results 294

6.7.1 Simulation Results for the Gain-scheduling Control 296

6.7.2 Simulation Results for Droop Control 296

6.8 Experimental Results 300

6.8.1 Case I 301

6.8.2 Case II 301

6.9 Summary 304

References 304

7 Virtual Synchronous Generators: Dynamic Performance and Characteristics 307

7.1 Introduction 308

7.2 Virtual Synchronous Generator (VSG) and Droop Control 314

7.2.1 Droop Control 314

7.2.2 Transient Frequency Response 315

7.2.3 Active Power Response 323

7.2.4 Experimental Results 327

7.3 Virtual Synchronous Generator-Based Oscillation Damping 331

7.3.1 Mathematical Formulation 331

7.3.2 Oscillation DampingMethodology 334

7.3.3 Simulation Results 337

7.3.4 Experimental Results 341

7.4 A Virtual Synchronous Generator Scheme with Emulating More Synchronous Generator Characteristics 344

7.4.1 Emulating Synchronous Generator Characteristics 345

7.4.2 Stability Analysis and Parameters Design 351

7.5 Active Power Performance Analysis in a Microgrid with Multiple Virtual Synchronous Generators 353

7.5.1 Closed-Loop State-Space Model 353

7.5.2 Oscillation Damping 355

7.5.3 Transient Active Power Sharing 356

7.6 Summary 358

References 358

8 Virtual Inertia-based Stability and Regulation Support 361

8.1 Introduction 361

8.2 An Enhanced Virtual Synchronous Generator Control Scheme 363

8.2.1 Proposed Virtual Synchronous Generator Control Scheme 364

8.2.2 Simulation Results 367

8.2.3 Experimental Results 373

8.3 Virtual Synchronous Generator Control in Parallel Operation with Synchronous Generator 376

8.3.1 System Description 377

8.3.2 The Proposed Modified Virtual Synchronous Generator Control Scheme 378

8.3.3 Parameter Tuning Methods 382

8.3.4 Simulation Results 388

8.4 Alternating Inertia-based Virtual Synchronous Generator Control 393

8.4.1 Control Strategy 393

8.4.2 Stability Analysis 397

8.4.3 Effect of Alternating Inertia on Dissipated Energy 401

8.4.4 Grid Stability Improvement 401

8.4.5 Experimental Results 405

8.5 Voltage Sag Ride-through Enhancement Using Virtual Synchronous Generator 406

8.5.1 Virtual Synchronous Generator Subjected to Voltage Sags 406

8.5.2 State Variable Analysis in Phase Plane 407

8.5.3 Voltage Sag Ride-through Enhancement 409

8.5.4 Simulation Results 411

8.5.5 Experimental Results 415

8.6 Performance Evaluation of the Virtual Synchronous Generator with More Synchronous Generator Characteristics 421

8.6.1 System Configuration and Parameters 422

8.6.2 Simulation Results 423

8.6.3 Experimental System 425

8.7 Summary 430

References 432

9 Robust Microgrid Control Synthesis 435

9.1 Introduction 435

9.2 Case Study and State-Space Model 438

9.3 H infinity and Structured Singular Value (mu) Control Theorems 442

9.3.1 H infinity ControlTheory 442

9.3.2 Structured Singular Value (mu) Control Theory 442

9.4 H infinity -Based Control Design 444

9.4.1 UncertaintyModeling 444

9.4.2 H infinity Optimal Controller 446

9.4.3 Closed-Loop Nominal Stability and Performance 446

9.4.4 Closed-Loop Robust Stability and Performance 446

9.5 mu-Based Control Design 447

9.5.1 UncertaintyModeling in mu-Synthesis 448

9.5.2 D-K Iteration 449

9.5.3 Closed-Loop Nominal and Robust Performance 451

9.5.4 Robust Stability 451

9.6 Order Reduction and Application Results 453

9.6.1 Controller Order Reduction 453

9.6.2 Application Results 455

9.6.3 Comparison withWell-Tuned Proportional-Integral (PI) Controllers 458

9.7 Robust Multivariable Microgrid Control Design 465

9.7.1 Uncertainty Determination 465

9.7.2 Robust Stability and Performance 468

9.8 Robust Tuning of VSG Parameters 473

9.8.1 The Extended VSG Dynamics 474

9.8.2 Case Study and H infinity Control Synthesis 475

9.8.3 Robust Tuning of Extended VSG Parameters 478

9.8.4 Simulation Results 481

9.9 Summary 483

References 483

10 IntelligentMicrogrid Operation and Control 487

10.1 Introduction 488

10.2 Intelligent Control Technologies 491

10.2.1 Fuzzy Logic Control 491

10.2.2 Artificial Neural Networks 501

10.2.3 Genetic Algorithm and Particle Swarm Optimization 504

10.2.4 Multiagent System 508

10.3 ANN-based Power and Load Forecasting in Microgrids 512

10.3.1 PV Power Prediction 514

10.3.2 Load Forecasting 515

10.3.3 Forecasting Error 517

10.4 Intelligent Frequency and Voltage Control in Microgrids 520

10.4.1 Fuzzy-logic-based Supervisory Frequency Control 521

10.4.2 Fuzzy-based Distribution Voltage Control in DC Microgrids 528

10.4.2.1 Proposed Control Strategy 528

10.4.2.2 Simulation Results 533

10.4.2.3 Experimental Results 537

10.4.3 Particle Swarm Optimization (PSO)-based Stability Enhancement in a Microgrid with Virtual Synchronous Generators 538

10.4.4 Multiagent-based Secondary Frequency Control 547

10.5 Summary 554

References 554

11 Emergency Control and Load Shedding in Microgrids 561

11.1 Introduction 561

11.2 Load Shedding as aWell-known Emergency Control Strategy 564

11.3 Load Shedding Algorithm: Example 1 567

11.3.1 Proposed Algorithm 567

11.3.2 Case Study 569

11.3.3 Simulation Results 571

11.4 Load Shedding Algorithm: Example 2 572

11.4.1 Proposed Algorithm 572

11.4.2 Case Study 574

11.4.3 Simulation Results 576

11.5 Undervoltage-frequency Load Shedding 578

11.5.1 Deltav-Deltaf Plane 579

11.5.2 Voltage and Frequency Performances 581

11.6 Summary 583

References 584

12 Microgrid Planning and EnergyManagement 589

12.1 Introduction 589

12.2 Microgrid Planning: An Example 594

12.2.1 Description of Input Parameters 595

12.2.2 System Description and Specification 597

12.2.3 Numerical Results and Discussion 598

12.3 Forecasting Techniques 601

12.3.1 PV Power Prediction 601

12.3.2 Load Forecasting 602

12.3.3 Energy Estimation 604

12.3.3.1 Estimation of the Available PV Power 604

12.4 Energy Management 605

12.4.1 Daily Power Management and Setting of Power References 605

12.4.2 Medium-term Energy Management 609

12.4.3 Short-term Power Management 612

12.4.4 Experimental Tests 613

12.5 Emission Reduction and Economical Optimization 624

12.5.1 Micro-Gas Turbine (MGT) Fuel Consumption and Emissions 625

12.5.2 Day-ahead Optimal Operational Planning 626

12.5.3 Experimental Results 632

12.6 Day-ahead Optimal Operation and Power Reserve Dispatching 635

12.6.1 Scenario 1: Power Reserve Provided by MGTs 637

12.6.1.1 Daytime 637

12.6.1.2 Nighttime (Discharge the Battery) 638

12.6.2 Scenario 2: Power Reserve Provided by Micro Gas Turbines and PV-based Active Generator 638

12.6.3 Optimal Reserve Power Dispatching Application for Unit Commitment Problem 642

12.7 Robust Energy Consumption Scheduling in Interconnected Microgrids 645

12.7.1 Cost Minimization Formulation 648

12.7.2 Peak-to-Average Ratio Minimization Formulation 650

12.7.3 Simulation Results 652

12.8 Summary 658

References 659

A Appendix 663

Index 665
Hassan Bevrani, PhD, is a Professor at University of Kurdistan, Kurdistan, Iran.

Bruno Francois, PhD, is a Professor at Centrale Lille, Lille, France.

Toshifumi Ise, PhD, is a Professor at Osaka University, Osaka, Japan.