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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Intelligence is defined by the ability to optimize, manage and reconcile the currents of physical, economic and even social flows. The strong constraint of immediacy proves to be an opportunity to imagine, propose and deliver solutions on the common basis of optimization techniques.
Metaheuristics for Intelligent Electrical Networks analyzes the use of metaheuristics through independent applications but united by the same methodology.
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Seitenzahl: 330
Veröffentlichungsjahr: 2017
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Table of Contents
Cover
Title
Copyright
Introduction
1 Single Solution Based Metaheuristics
1.1. Introduction
1.2. The descent method
1.3. Simulated annealing
1.4. Microcanonical annealing
1.5. Tabu search
1.6. Pattern search algorithms
1.7. Other methods
1.8. Conclusion
2 Population-based Methods
2.1. Introduction
2.2. Evolutionary algorithms
2.3. Swarm intelligence
2.4. Conclusion
3 Performance Evaluation of Metaheuristics
3.1. Introduction
3.2. Performance measures
3.3. Statistical analysis
3.4. Literature benchmarks
3.5. Conclusion
4 Metaheuristics for FACTS Placement and Sizing
4.1. Introduction
4.2. FACTS devices
4.3. The PF model and its solution
4.4. PSO for FACTS placement
4.5. Application to the placement and sizing of two FACTS
4.6. Conclusion
5 Genetic Algorithm-based Wind Farm Topology Optimization
5.1. Introduction
5.2. Problem statement
5.3. Genetic algorithms and adaptation to our problem
5.4. Application
5.5. Conclusion
6 Topological Study of Electrical Networks
6.1. Introduction
6.2. Topological study of networks
6.3. Topological analysis of the Colombian electrical network
6.4. Conclusion
7 Parameter Estimation of
α
-Stable Distributions
7.1. Introduction
7.2. Lévy probability distribution
7.3. Elaboration of our non-parametric
α
-stable distribution estimator
7.4. Results and comparison with benchmarks
7.5. Conclusion
8
SmartGrid
and
MicroGrid
Perspectives
8.1. New
SmartGrid
concepts
8.2. Key elements for
SmartGrid
deployment
8.3.
SmartGrids
and components technology architecture
Appendix 1
A1.1. Test functions
Appendix 2
A2.1. Application to the multi-objective case
Bibliography
Index
End User License Agreement
Guide
Cover
Table of Contents
Begin Reading
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e1
Metaheuristics Set
coordinated by
Nicolas Monmarché and Patrick Siarry
Volume 10
Metaheuristics for Intelligent Electrical Networks
Frédéric Héliodore
Amir Nakib
Boussaad Ismail
Salma Ouchraa
Laurent Schmitt
First published 2017 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd
27-37 St George’s Road
London SW19 4EU
UK
www.iste.co.uk
John Wiley & Sons, Inc.
111 River Street
Hoboken, NJ 07030
USA
www.wiley.com
© ISTE Ltd 2017
The rights of Frédéric Héliodore, Amir Nakib, Boussaad Ismail, Salma Ouchraa, Laurent Schmitt to be identified as the authors of this work have been asserted by them in accordance with the Copyright,
Designs and Patents Act 1988.
Library of Congress Control Number: 2017946567
British Library Cataloguing-in-Publication Data
A CIP record for this book is available from the British Library
ISBN 978-1-84821-809-3
Introduction
This book is the result of works dedicated to specific applications of metaheuristics in smart electrical grids. From electric transmission, distribution networks to electric microgrids, the notion of intelligence refers to the ability to propose acceptable solutions in an increasingly more restrictive environment. Most often, it refers to decision-making assisting tools designed to support all human action.
Optimization techniques and, in particular, metaheuristics, due to their diversity, their faculty to reproduce natural processes and their good accuracy/execution speed compromise, do enjoy a growing success in the energy world where the diversity of problems and requirements often requires one to intervene and quickly develop acceptable and attractive solutions.
Although development in industrial environments is always constrained by the time factor, value creation continues to be a target and differentiation factors must always be identified. The precise acknowledgment of physical problems remains the unifying element that, coupled with the fields of optimization and statistics, allows for the definition of innovative tools. Furthermore, this is the blueprint that is promoted and that finds its place in the field of “data science”.
The chapters in this book are independent but always follow the same approach. A state-of-the-art of metaheuristics is presented with, in particular:
– path-based heuristics;
– solution population-based methods;
– performance evaluation of metaheuristics.
Applications specific to power systems follow with:
– the optimal placement of FACTS (Flexible Alternative Current Transmission System) to manage reactive power;
– the optimization of the internal topology of a wind farm.
Two examples of the interaction of disciplines are addressed, on the one hand, by introducing the topological complexity of networks and, on the other hand, by getting involved in statistical estimation:
– topological study of electric networks;
– estimation of the parameters of an
α
-stable distribution.
The application domain of the metaheuristics will expand through the development of electric smart networks (SmartGrid and MicroGrid). A presentation of the future challenges is the subject of Chapter 8:
– extension to
SmartGrids
and
MicroGrids
.
