Yinliang Xu, Wei Zhang, Wenxin Liu

Distributed Energy Management of Electrical Power Systems

• Gebundenes Buch

Produktbeschreibung

Go in-depth with this comprehensive discussion of distributed energy management

Distributed Energy Management of Electrical Power Systems provides the most complete analysis of fully distributed control approaches and their applications for electric power systems available today. Authored by four respected leaders in the field, the book covers the technical aspects of control, operation management, and optimization of electric power systems.

In each chapter, the book covers the foundations and fundamentals of the topic under discussion. It then moves on to more advanced applications. Topics reviewed in the book include:
_ System-level coordinated control
_ Optimization of active and reactive power in power grids
_ The coordinated control of distributed generation, elastic load and energy storage systems

Distributed Energy Management incorporates discussions of emerging and future technologies and their potential effects on electrical power systems. The increased impact of renewable energy sources is also covered.

Perfect for industry practitioners and graduate students in the field of power systems, Distributed Energy Management remains the leading reference for anyone with an interest in its fascinating subject matter.

Produktdetails

• IEEE Press Series on Power Engineering
• Verlag: Wiley & Sons / Wiley-IEEE Press
• Artikelnr. des Verlages: 1W119534880
• 1. Auflage
• Seitenzahl: 352
• Erscheinungstermin: 13. Januar 2021
• Englisch
• Abmessung: 235mm x 157mm x 24mm
• Gewicht: 630g
• ISBN-13: 9781119534884
• ISBN-10: 1119534887
• Artikelnr.: 59260732

Autorenporträt

YINLIANG XU, PHD, is now an Associate Professor with Tsinghua-Berkeley Shenzhen Institute, Tsinghua Shenzhen International Graduate School, Tsinghua University, P. R. China. WEI ZHANG, PHD, is a Postdoc Resercher Associate with Department of Civil, Environmental, and Construction Engineering of College of Engineering & Computer Science, University of Central Florida, Orlando, Florida, USA. WENXIN LIU, PHD, is an Associate Professor with the Department of Electrical and Computer Engineering, Lehigh University, Bethlehem, PA, USA. WEN YU, PHD, is a Professor with the Departamento de Control Automatico with the Centro de Investigación y de Estudios Avanzados, Instituto Politécnico Nacional (CINVESTAV-IPN), Mexico City, Mexico.

Inhaltsangabe

About the Authors xiii

Preface xv

Acknowledgment xix

List of Figures xxi

List of Tables xxxi

1 Background 1

1.1 Power Management 1

1.2 Traditional Centralized vs. Distributed Solutions to Power Management 4

1.3 Existing Distributed Control Approaches 5

2 Algorithm Evaluation 9

2.1 Communication Network Topology Configuration 9

2.1.1 Communication Network Design for Distributed Applications 9

2.1.2 N .1 Rule for Communication Network Design 11

2.1.3 Convergence of Distributed Algorithms with Variant Communication Network Typologies 13

2.2 Real-Time Digital Simulation 16

2.2.1 Develop MAS Platform Using JADE 16

2.2.2 Test-Distributed Algorithms Using MAS 18

2.2.2.1 Three-Agent System on the Same Platform 18

2.2.2.2 Two-Agent System with Different Platforms 19

2.2.3 MAS-Based Real-Time Simulation Platform 20

References 22

3 Distributed Active Power Control 23

3.1 Subgradient-Based Active Power Sharing 23

3.1.1 Introduction 24

3.1.2 Preliminaries - Conventional Droop Control Approach 26

3.1.3 Proposed Subgradient-Based Control Approach 27

3.1.3.1 Introduction of Utilization Level-Based Coordination 27

3.1.3.2 Fully Distributed Subgradient-Based Generation Coordination Algorithm 28

3.1.3.3 Application of the Proposed Algorithm 31

3.1.4 Control of Multiple Distributed Generators 33

3.1.4.1 DFIG Control Approach 33

3.1.4.2 Converter Control Approach 34

3.1.4.3 Pitch Angle Control Approach 35

3.1.4.4 PV Generation Control Approach 36

3.1.4.5 Synchronous Generator Control Approach 36

3.1.5 Simulation Analyses 37

3.1.5.1 Case 1 - Constant Maximum Available Renewable Generation and Load 38

3.1.5.2 Case 2 - Variable Maximum Available Renewable Generation and Load 41

3.1.6 Conclusion 45

3.2 Distributed Dynamic Programming-Based Approach for Economic Dispatch in Smart Grids 46

3.2.1 Introduction 46

3.2.2 Preliminary 49

3.2.3 Graph Theory 49

3.2.4 Dynamic Programming 49

3.2.5 Problem Formulation 49

3.2.6 Economic Dispatch Problem 50

3.2.7 Discrete Economic Dispatch Problem 50

3.2.8 Proposed Distributed Dynamic Programming Algorithm 51

3.2.9 Distributed Dynamic Programming Algorithm 52

3.2.10 Algorithm Implementation 53

3.2.11 Simulation Studies 54

3.2.12 Four-generator System: Synchronous Iteration 54

3.2.12.1 Minimum Generation Adjustment Deltapi = 2.5MW 54

3.2.12.2 Minimum Generation Adjustment Deltapi = 1.25MW 57

3.2.13 Four-Generator System: Asynchronous Iteration 59

3.2.13.1 Missing Communication with Probability 59

3.2.13.2 Gossip Communication 60

3.2.14 IEEE 162-Bus System 61

3.2.15 Hardware Implementation 63

3.2.16 Conclusion 64

3.3 Constrained Distributed Optimal Active Power Dispatch 65

3.3.1 Introduction 65

3.3.2 Problem Formulation 67

3.3.3 Distributed Gradient Algorithm 68

3.3.4 Distributed Gradient Algorithm 68

3.3.5 Inequality Constraint Handling 70

3.3.6 Numerical Example 72

3.3.6.1 Case 1 72

3.3.6.2 Case 2 74

3.3.7 Control Implementation 75

3.3.8 Communication Network Design 76

3.3.9 Generator Control Implementation 76

3.3.10 Simulation Studies 77

3.3.11 Real-Time Simulation Platform 78
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