Details

Microgrid Dynamics and Control


Microgrid Dynamics and Control


1. Aufl.

von: Hassan Bevrani, Bruno François, Toshifumi Ise

134,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 18.07.2017
ISBN/EAN: 9781119263708
Sprache: englisch
Anzahl Seiten: 720

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Beschreibungen

<p>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.</p>
<p>Foreword xix</p> <p>Preface xxi</p> <p>Acknowledgments xxvii</p> <p><b>1 Grid-connected Renewable Energy Sources 1</b></p> <p>1.1 Introduction 1</p> <p>1.2 Renewable Power Generation 3</p> <p>1.2.1 Renewable Energy Development 5</p> <p>1.3 Grid-connectedWind Power 6</p> <p>1.3.1 Wind Power GeneratorWithout Power Electronic Converters 7</p> <p>1.3.2 Wind Power Generator Using Partial-Scale Power Electronic Converters 7</p> <p>1.3.3 Wind Power Generator Using Full-Scale Power Electronic Converters 7</p> <p>1.4 Grid-Connected PV Power 35</p> <p>1.4.1 Solar Power Generators with Embedded Energy Storage Systems 36</p> <p>1.4.2 Solar Energy Conversion System: Modeling, Control, and Analysis 38</p> <p>1.4.3 Experimental Results 55</p> <p>1.4.4 Control of Grid-Connected Solar Power Inverters: A Review 59</p> <p>1.5 Summary 66</p> <p>References 66</p> <p><b>2 Renewable Power for Control Support 69</b></p> <p>2.1 Introduction 69</p> <p>2.2 Wind-Energy-based Control Support 73</p> <p>2.2.1 Wind Turbines Inertial Response 73</p> <p>2.2.2 Study on a Real Isolated Power System 77</p> <p>2.2.3 Primary Frequency and Inertial Controls 81</p> <p>2.2.4 Using Secondary Control 89</p> <p>2.3 Renewable Primary Power Reserve 89</p> <p>2.3.1 InstantaneousWind Power Reserve 89</p> <p>2.3.2 An Evaluation on the Real Case Study 92</p> <p>2.3.3 Comparison of the Reserve Allocation Strategies 96</p> <p>2.4 PV-Energy-Based Control Support 102</p> <p>2.5 Integration of Renewable Energy SystemsThrough Microgrids 105</p> <p>2.5.1 A Solution for Renewable Power Penetration 105</p> <p>2.5.2 Microgrids in Future Smart Grids 108</p> <p>2.6 Summary 112</p> <p>References 113</p> <p><b>3 Microgrids: Concept, Structure, and Operation Modes 119</b></p> <p>3.1 Introduction 119</p> <p>3.2 Microgrid Concept and Structure 125</p> <p>3.3 Operation Modes 129</p> <p>3.4 Control Mechanism of the Connected Distributed Generators in a</p> <p>Microgrid 130</p> <p>3.4.1 Speed Control of Classical Distributed Generators 130</p> <p>3.4.2 Control of Inverter-based Distributed Generators 131</p> <p>3.5 Contribution in the Upstream Grid Ancillary Services: Frequency</p> <p>Control Support Example 137</p> <p>3.5.1 Participation in the Frequency Regulation 138</p> <p>3.5.2 Power Dispatching 142</p> <p>3.5.3 Simulation Results 147</p> <p>3.6 Microgrids Laboratory Technologies 147</p> <p>3.6.1 Hardware-in-the-loop-based Microgrid Laboratory 152</p> <p>3.6.2 Participant Laboratories to Provide the Present Book 157</p> <p>3.7 Summary 160</p> <p>References 160</p> <p><b>4 Microgrid Dynamics andModeling 165</b></p> <p>4.1 Introduction 165</p> <p>4.2 Distribution Network (Main Grid) and Connection Modeling 168</p> <p>4.2.1 Distribution Network Modeling 168</p> <p>4.2.2 Modeling of Connection Between the Main Grid and the Microgrid 174</p> <p>4.3 Overall Representation of the Grid-Connected Microgrid 178</p> <p>4.3.1 Microgrid Bus 178</p> <p>4.3.2 Global Architecture Representation 178</p> <p>4.3.3 Microgrid Representation in the Islanded Operation Mode 179</p> <p>4.4 Microgrid Components Dynamics and Modeling 182</p> <p>4.4.1 PV Model 182</p> <p>4.4.2 Energy Storage Systems Modeling 186</p> <p>4.4.3 Power Electronic Converters 193</p> <p>4.5 Simplified Microgrid Frequency Response Model 198</p> <p>4.5.1 Example 1 199</p> <p>4.5.2 Example 2 201</p> <p>4.6 A Detailed State-Space DynamicModel 203</p> <p>4.6.1 MathematicalModeling 203</p> <p>4.6.2 Simulation Example 207</p> <p>4.6.3 Closed-Loop State-Space Model 210</p> <p>4.7 Microgrid Dynamic Modeling and Analysis as a Multivariable System 211</p> <p>4.7.1 State-space Modeling 212</p> <p>4.7.2 Dynamic Analysis 215</p> <p>4.8 Summary 217</p> <p>References 217</p> <p><b>5 Hierarchical Microgrid Control 221</b></p> <p>5.1 Introduction 221</p> <p>5.2 Microgrid Control Hierarchy 225</p> <p>5.2.1 Local Control 227</p> <p>5.2.2 Secondary Control 228</p> <p>5.2.3 Central/Emergency Control 229</p> <p>5.2.4 Global Control 231</p> <p>5.3 Droop Control 233</p> <p>5.3.1 Droop Characteristic in Conventional Power Systems 233</p> <p>5.3.2 Droop Control in Inverter-based Distributed Generators 235</p> <p>5.3.3 Virtual Impedance Control 241</p> <p>5.4 Hierarchical Power Management and Control 243</p> <p>5.4.1 Operation Layers and Control Functions 244</p> <p>5.4.2 Timescale Analyzing and Implementation Constraints 245</p> <p>5.5 Design Example 252</p> <p>5.5.1 Power Dispatching 253</p> <p>5.5.2 Hardware-In-the-Loop Test Results 254</p> <p>5.5.3 Test Procedure 257</p> <p>5.6 Summary 262</p> <p>References 263</p> <p><b>6 DC Microgrid Control 267</b></p> <p>6.1 Introduction 267</p> <p>6.2 DC Microgrid for a Residential Area 270</p> <p>6.2.1 System Configuration and Operation 270</p> <p>6.2.2 Voltage Clamp Control 273</p> <p>6.2.3 Disconnection/Reconnection from/to the Utility Grid 273</p> <p>6.3 Low-voltage Bipolar-type DC Microgrid 275</p> <p>6.4 Stability Evaluation 277</p> <p>6.5 Experimental Study and Results 280</p> <p>6.5.1 Experimental System 280</p> <p>6.5.2 Voltage Sag of the Utility Grid 284</p> <p>6.5.3 Disconnection/Reconnection from/to the Utility Grid 284</p> <p>6.6 A Voltage Control Approach 286</p> <p>6.6.1 Case Study and Voltage Control System 286</p> <p>6.6.2 Energy Storage System Control 290</p> <p>6.7 Simulation Results 294</p> <p>6.7.1 Simulation Results for the Gain-scheduling Control 296</p> <p>6.7.2 Simulation Results for Droop Control 296</p> <p>6.8 Experimental Results 300</p> <p>6.8.1 Case I 301</p> <p>6.8.2 Case II 301</p> <p>6.9 Summary 304</p> <p>References 304</p> <p><b>7 Virtual Synchronous Generators: Dynamic Performance and Characteristics 307</b></p> <p>7.1 Introduction 308</p> <p>7.2 Virtual Synchronous Generator (VSG) and Droop Control 314</p> <p>7.2.1 Droop Control 314</p> <p>7.2.2 Transient Frequency Response 315</p> <p>7.2.3 Active Power Response 323</p> <p>7.2.4 Experimental Results 327</p> <p>7.3 Virtual Synchronous Generator-Based Oscillation Damping 331</p> <p>7.3.1 Mathematical Formulation 331</p> <p>7.3.2 Oscillation DampingMethodology 334</p> <p>7.3.3 Simulation Results 337</p> <p>7.3.4 Experimental Results 341</p> <p>7.4 A Virtual Synchronous Generator Scheme with Emulating More Synchronous Generator Characteristics 344</p> <p>7.4.1 Emulating Synchronous Generator Characteristics 345</p> <p>7.4.2 Stability Analysis and Parameters Design 351</p> <p>7.5 Active Power Performance Analysis in a Microgrid with Multiple Virtual Synchronous Generators 353</p> <p>7.5.1 Closed-Loop State-Space Model 353</p> <p>7.5.2 Oscillation Damping 355</p> <p>7.5.3 Transient Active Power Sharing 356</p> <p>7.6 Summary 358</p> <p>References 358</p> <p><b>8 Virtual Inertia-based Stability and Regulation Support 361</b></p> <p>8.1 Introduction 361</p> <p>8.2 An Enhanced Virtual Synchronous Generator Control Scheme 363</p> <p>8.2.1 Proposed Virtual Synchronous Generator Control Scheme 364</p> <p>8.2.2 Simulation Results 367</p> <p>8.2.3 Experimental Results 373</p> <p>8.3 Virtual Synchronous Generator Control in Parallel Operation with Synchronous Generator 376</p> <p>8.3.1 System Description 377</p> <p>8.3.2 The Proposed Modified Virtual Synchronous Generator Control Scheme 378</p> <p>8.3.3 Parameter Tuning Methods 382</p> <p>8.3.4 Simulation Results 388</p> <p>8.4 Alternating Inertia-based Virtual Synchronous Generator Control 393</p> <p>8.4.1 Control Strategy 393</p> <p>8.4.2 Stability Analysis 397</p> <p>8.4.3 Effect of Alternating Inertia on Dissipated Energy 401</p> <p>8.4.4 Grid Stability Improvement 401</p> <p>8.4.5 Experimental Results 405</p> <p>8.5 Voltage Sag Ride-through Enhancement Using Virtual Synchronous Generator 406</p> <p>8.5.1 Virtual Synchronous Generator Subjected to Voltage Sags 406</p> <p>8.5.2 State Variable Analysis in Phase Plane 407</p> <p>8.5.3 Voltage Sag Ride-through Enhancement 409</p> <p>8.5.4 Simulation Results 411</p> <p>8.5.5 Experimental Results 415</p> <p>8.6 Performance Evaluation of the Virtual Synchronous Generator with More Synchronous Generator Characteristics 421</p> <p>8.6.1 System Configuration and Parameters 422</p> <p>8.6.2 Simulation Results 423</p> <p>8.6.3 Experimental System 425</p> <p>8.7 Summary 430</p> <p>References 432</p> <p><b>9 Robust Microgrid Control Synthesis 435</b></p> <p>9.1 Introduction 435</p> <p>9.2 Case Study and State-Space Model 438</p> <p>9.3 H∞ and Structured Singular Value (μ) Control Theorems 442</p> <p>9.3.1 H∞ ControlTheory 442</p> <p>9.3.2 Structured Singular Value (μ) Control Theory 442</p> <p>9.4 H∞-Based Control Design 444</p> <p>9.4.1 UncertaintyModeling 444</p> <p>9.4.2 H∞ Optimal Controller 446</p> <p>9.4.3 Closed-Loop Nominal Stability and Performance 446</p> <p>9.4.4 Closed-Loop Robust Stability and Performance 446</p> <p>9.5 μ-Based Control Design 447</p> <p>9.5.1 UncertaintyModeling in μ-Synthesis 448</p> <p>9.5.2 D–K Iteration 449</p> <p>9.5.3 Closed-Loop Nominal and Robust Performance 451</p> <p>9.5.4 Robust Stability 451</p> <p>9.6 Order Reduction and Application Results 453</p> <p>9.6.1 Controller Order Reduction 453</p> <p>9.6.2 Application Results 455</p> <p>9.6.3 Comparison withWell-Tuned Proportional-Integral (PI) Controllers 458</p> <p>9.7 Robust Multivariable Microgrid Control Design 465</p> <p>9.7.1 Uncertainty Determination 465</p> <p>9.7.2 Robust Stability and Performance 468</p> <p>9.8 Robust Tuning of VSG Parameters 473</p> <p>9.8.1 The Extended VSG Dynamics 474</p> <p>9.8.2 Case Study and H∞ Control Synthesis 475</p> <p>9.8.3 Robust Tuning of Extended VSG Parameters 478</p> <p>9.8.4 Simulation Results 481</p> <p>9.9 Summary 483</p> <p>References 483</p> <p><b>10 IntelligentMicrogrid Operation and Control 487</b></p> <p>10.1 Introduction 488</p> <p>10.2 Intelligent Control Technologies 491</p> <p>10.2.1 Fuzzy Logic Control 491</p> <p>10.2.2 Artificial Neural Networks 501</p> <p>10.2.3 Genetic Algorithm and Particle Swarm Optimization 504</p> <p>10.2.4 Multiagent System 508</p> <p>10.3 ANN-based Power and Load Forecasting in Microgrids 512</p> <p>10.3.1 PV Power Prediction 514</p> <p>10.3.2 Load Forecasting 515</p> <p>10.3.3 Forecasting Error 517</p> <p>10.4 Intelligent Frequency and Voltage Control in Microgrids 520</p> <p>10.4.1 Fuzzy-logic-based Supervisory Frequency Control 521</p> <p>10.4.2 Fuzzy-based Distribution Voltage Control in DC Microgrids 528</p> <p>10.4.2.1 Proposed Control Strategy 528</p> <p>10.4.2.2 Simulation Results 533</p> <p>10.4.2.3 Experimental Results 537</p> <p>10.4.3 Particle Swarm Optimization (PSO)-based Stability Enhancement in a Microgrid with Virtual Synchronous Generators 538</p> <p>10.4.4 Multiagent-based Secondary Frequency Control 547</p> <p>10.5 Summary 554</p> <p>References 554</p> <p><b>11 Emergency Control and Load Shedding in Microgrids 561</b></p> <p>11.1 Introduction 561</p> <p>11.2 Load Shedding as aWell-known Emergency Control Strategy 564</p> <p>11.3 Load Shedding Algorithm: Example 1 567</p> <p>11.3.1 Proposed Algorithm 567</p> <p>11.3.2 Case Study 569</p> <p>11.3.3 Simulation Results 571</p> <p>11.4 Load Shedding Algorithm: Example 2 572</p> <p>11.4.1 Proposed Algorithm 572</p> <p>11.4.2 Case Study 574</p> <p>11.4.3 Simulation Results 576</p> <p>11.5 Undervoltage–frequency Load Shedding 578</p> <p>11.5.1 Δv–Δf Plane 579</p> <p>11.5.2 Voltage and Frequency Performances 581</p> <p>11.6 Summary 583</p> <p>References 584</p> <p><b>12 Microgrid Planning and EnergyManagement 589</b></p> <p>12.1 Introduction 589</p> <p>12.2 Microgrid Planning: An Example 594</p> <p>12.2.1 Description of Input Parameters 595</p> <p>12.2.2 System Description and Specification 597</p> <p>12.2.3 Numerical Results and Discussion 598</p> <p>12.3 Forecasting Techniques 601</p> <p>12.3.1 PV Power Prediction 601</p> <p>12.3.2 Load Forecasting 602</p> <p>12.3.3 Energy Estimation 604</p> <p>12.3.3.1 Estimation of the Available PV Power 604</p> <p>12.4 Energy Management 605</p> <p>12.4.1 Daily Power Management and Setting of Power References 605</p> <p>12.4.2 Medium-term Energy Management 609</p> <p>12.4.3 Short-term Power Management 612</p> <p>12.4.4 Experimental Tests 613</p> <p>12.5 Emission Reduction and Economical Optimization 624</p> <p>12.5.1 Micro-Gas Turbine (MGT) Fuel Consumption and Emissions 625</p> <p>12.5.2 Day-ahead Optimal Operational Planning 626</p> <p>12.5.3 Experimental Results 632</p> <p>12.6 Day-ahead Optimal Operation and Power Reserve Dispatching 635</p> <p>12.6.1 Scenario 1: Power Reserve Provided by MGTs 637</p> <p>12.6.1.1 Daytime 637</p> <p>12.6.1.2 Nighttime (Discharge the Battery) 638</p> <p>12.6.2 Scenario 2: Power Reserve Provided by Micro Gas Turbines and PV-based Active Generator 638</p> <p>12.6.3 Optimal Reserve Power Dispatching Application for Unit Commitment Problem 642</p> <p>12.7 Robust Energy Consumption Scheduling in Interconnected Microgrids 645</p> <p>12.7.1 Cost Minimization Formulation 648</p> <p>12.7.2 Peak-to-Average Ratio Minimization Formulation 650</p> <p>12.7.3 Simulation Results 652</p> <p>12.8 Summary 658</p> <p>References 659</p> <p>A Appendix 663</p> <p>Index 665</p> <p> </p>
<p> <strong>Hassan Bevrani,</strong> PhD, is a Professor at University of Kurdistan, Kurdistan, Iran. <p><strong>Bruno Francois,</strong> PhD, is a Professor at Centrale Lille, Lille, France. <p><strong>Toshifumi Ise,</strong> PhD, is a Professor at Osaka University, Osaka, Japan.
<p><b>A comprehensive review of microgrid dynamic analysis, control synthesis, and implementations</b> <p>The microgrid (MG) concept provides a quite appealing solution for overcoming the challenges of integrating renewable energy sources (RESs) and distributed generators (DGs) into power grids. Advances in MG control have improved the MGs potential to be integrated into the electrical power grids in a higher capacity. This improvement not only covers their internal control performance, but also includes the support functionalities to enhance the global operation of power grids. <p> <em>Microgrid Dynamics and Control</em> is a comprehensive resource that explores MG technologies in the context of renewable power penetration and addresses the challenging control issues. The authors—noted experts in the field—examine the current and long term academic research to offer a summary of the main achievements and the most relevant information available. In addition, the text draws the authors' practical experiences on MGs, electric network monitoring, control design, and power electronic systems. <p>The text covers MG structure, types, operating modes, modeling, dynamics, and control levels. The physical constraints and engineering aspects of MGs are covered, and developed robust and intelligent control strategies are discussed. This important resource: <ul> <li>Represents several MG modeling, dynamic analysis methodologies and control synthesis approaches that all are examined by real time simulations and experimental studies</li> <li>Covers the MG hierarchical control levels including local, secondary, central/emergency, and global controls to ensure stable, reliable, secure, and economical operation in either grid-connected or islanded operation mode</li> <li>Discusses new outcomes and advances in DC MGs, virtual synchronous generators, energy management and power control</li> </ul> <br> <p> <em>Microgrid Dynamics and Control</em> offers engineers and operators in power grid planning and operation a thorough discussion of the basic principles of MG modeling and provides information on common operating issues.

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