Distributed Control and Optimization Technologies in Smart Grid Systems [texte imprimé] /
Fanghong Guo, Auteur . -
USAÂ : Taylor, 2017 . - 192p : couv.ill.fug.tab.indx ; 16*24.
ISBN : 978-1-03-233933-7 : 14 600,00 da
Langues : Anglais (
eng)
| Résumé : |
The book aims to equalize the theoretical involvement with industrial practicality and build a bridge between academia and industry by reducing the mathematical difficulties. It provides an overview of distributed control and distributed optimization theory, followed by specific details on industrial applications to smart grid systems, with a special focus on micro grid systems. Each of the chapters is written and organized with an introductory section tailored to provide the essential background of the theories required. The text includes industrial applications to realistic renewable energy systems problems and illustrates the application of proposed toolsets to control and optimization of smart grid system |
| Note de contenu : |
Preface
1 Introduction
1.1 Background & Motivation
1.2 Objectives and Scope
1.3 Microgrid
1.4 Control Strategies of MGs
1.5 Major Contributions of the Book
1.6 Organization of the Book
2 Preliminaries
2.1 Graph Theory
2.2 Distributed Finite-time Average Consensus Algorithm
2.3 Finite-time Control
2.4 Multi-agent Optimization
3 Distributed Voltage and Frequency Restoration Control
3.1 Introduction
3.2 Modeling of MG
3.3 Distributed Secondary Controller Design
3.4 Simulation Results
4 Distributed Voltage Unbalance Compensation
4.1 Introduction
4.2 Distributed Cooperative Secondary Control Scheme for Voltage ¿Unbalance Compensation
4.3 Case Studies
5 Distributed Single-Area Economic Dispatch
5.1 Introduction
5.2 Problem Formulation
5.3 Total Load Demand Discovery
5.4 Distributed Economic Dispatch
5.5 Case Studies
6 Distributed Multi-Area Economic Dispatch
6.1 Introduction
6.2 Problem Formulation
6.3 Distributed Optimization Algorithm
6.4 Convergence analysis
6.5 Economic Dispatch in Multi-area Power System
7 Distributed Optimal Energy Scheduling
7.1 Introduction
7.2 Problem Formulation
7.3 Distributed Optimal Energy Scheduling
7.4 Case Studies
8 Conclusion and Future Works
8.1 Conclusion
8.2 Recommendations for Future Research |
Distributed Control and Optimization Technologies in Smart Grid Systems
