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E-grāmata: Systemic Design Methodologies for Electrical Energy Systems: Analysis, Synthesis and Management

Edited by (Directeur de Recherches in CNRS, France)
  • Formāts: PDF+DRM
  • Izdošanas datums: 17-Dec-2012
  • Izdevniecība: ISTE Ltd and John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781118569641
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Systemic Design Methodologies for Electrical Energy Systems: Analysis, Synthesis and ManagementPalielināt
  • Formāts: PDF+DRM
  • Izdošanas datums: 17-Dec-2012
  • Izdevniecība: ISTE Ltd and John Wiley & Sons Inc
  • Valoda: eng
  • ISBN-13: 9781118569641
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This book proposes systemic design methodologies applied to electrical energy systems, in particular analysis and system management, modeling and sizing tools.
It includes 8 chapters: after an introduction to the systemic approach (history, basics & fundamental issues, index terms) for designing energy systems, this book presents two different graphical formalisms especially dedicated to multidisciplinary devices modeling, synthesis and analysis: Bond Graph and COG/EMR. Other systemic analysis approaches for quality and stability of systems, as well as for safety and robustness analysis tools are also proposed. One chapter is dedicated to energy management and another is focused on Monte Carlo algorithms for electrical systems and networks sizing.
The aim of this book is to summarize design methodologies based in particular on a systemic viewpoint, by considering the system as a whole. These methods and tools are proposed by the most important French research laboratories, which have many scientific partnerships with other European and international research institutions. Scientists and engineers in the field of electrical engineering, especially teachers/researchers because of the focus on methodological issues, will find this book extremely useful, as will PhD and Masters students in this field.

Preface xi
Chapter 1 Introduction to Systemic Design
1(38)
Stephan Astier
Alain Bouscayrol
Xavier Roboam
1.1 The system and the science of systems
2(10)
1.1.1 First notions of systems and systems theory
3(3)
1.1.2 A brief history of systems theory and the science of systems
6(3)
1.1.3 The science of systems and artifacts
9(3)
1.2 The model and the science of systems
12(3)
1.3 Energy systems: specific and shared properties
15(11)
1.3.1 Energy and its properties
15(4)
1.3.2 Entropy and quality of energy
19(5)
1.3.3 Consequences for energy systems
24(2)
1.4 Systemic design of energy systems
26(6)
1.4.1 The context of systemic design in technology
26(2)
1.4.2 The design process: toward an integrated design
28(4)
1.5 Conclusion: what are the objectives for an integrated design of energy conversion systems?
32(1)
1.6 Glossary of systemic design
33(3)
1.7 Bibliography
36(3)
Chapter 2 The Bond Graph Formalism for an Energetic and Dynamic Approach of the Analysis and Synthesis of Multiphysical Systems
39(50)
Xavier Roboam
Eric Bideaux
Genevieve Dauphin-Tanguy
Bruno Sareni
Stephan Astier
2.1 Summary of basic principles and elements of the formalism
41(5)
2.1.1 Basic elements
41(1)
2.1.2 The elementary phenomena
42(3)
2.1.3 The causality in bond graphs
45(1)
2.2 The bond graph: an "interdisciplinary formalism"
46(10)
2.2.1 "Electro-electrical" conversion
47(4)
2.2.2 Electromechanical conversion
51(1)
2.2.3 Electrochemical conversion
52(3)
2.2.4 Example of a causal multiphysical model: the EHA actuator
55(1)
2.3 The bond graph, tool of system analysis
56(13)
2.3.1 Analysis of models properties
56(2)
2.3.2 Linear time invariant models
58(3)
2.3.3 Simplification of models
61(8)
2.4 Design of systems by inversion of bond graph models
69(15)
2.4.1 Inverse problems associated with the design approach
70(2)
2.4.2 Inversion of systems modeled by bond graph
72(6)
2.4.3 Example of application to design problems
78(6)
2.5 Bibliography
84(5)
Chapter 3 Graphic Formalisms for the Control of Multi-Physical Energetic Systems: COG and EMR
89(36)
Alain Bouscayrol
Jean Paul Hautier
Betty Lemaire-Semail
3.1 Introduction
89(1)
3.2 Which approach should be used for the control of an energetic system?
90(5)
3.2.1 Control of an energetic system
90(1)
3.2.2 Different approaches to the control of a system
91(1)
3.2.3 Modeling and control of an energetic system
92(1)
3.2.4 Toward the use of graphic formalisms of representation
93(2)
3.3 The causal ordering graph
95(12)
3.3.1 Description by COG
95(5)
3.3.2 Structure of control by inversion of the COG
100(5)
3.3.3 Elementary example: control of a DC drive
105(2)
3.4 Energetic Macroscopic Representation
107(9)
3.4.1 Description by EMR
108(3)
3.4.2 Structure of control by inversion of an EMR
111(3)
3.4.3 Elementary example: control of an electrical vehicle
114(2)
3.5 Complementarity of the approaches and extensions
116(4)
3.5.1 Differences and complementarities
117(1)
3.5.2 Example: control of a paper band winder/unwinder
117(2)
3.5.3 Other applications and extensions
119(1)
3.6 Bibliography
120(5)
Chapter 4 The Robustness: A New Approach for the Integration of Energetic Systems
125(34)
Nicolas Retiere
Delphine Riu
Mathieu Sautreuil
Olivier Sename
4.1 Introduction
125(1)
4.2 Control design of electrical systems
126(15)
4.2.1 The control design is an issue of integration
126(4)
4.2.2 The nominal control synthesis
130(5)
4.2.3 The analysis of robustness
135(6)
4.3 Application to an on-board generation system
141(14)
4.3.1 Presentation of a nominal system
141(1)
4.3.2 Modeling and dynamical analysis of the nominal system
141(6)
4.3.3 Analysis of the robustness
147(8)
4.4 Conclusion
155(1)
4.5 Bibliography
155(4)
Chapter 5 Quality and Stability of Embedded Power DC Networks
159(64)
Hubert Piquet
Nicolas Roux
Babak Nahid-Mobarakeh
Serge Pierfederici
Pierre Magne
Jerome Faucher
5.1 Introduction
159(6)
5.1.1 Challenges to quality optimization
160(1)
5.1.2 The difficulty of stability
161(4)
5.2 Production of DC networks: the quality of the distributed energy
165(7)
5.2.1 Combined and specialized electrical architectures
165(2)
5.2.2 AC/DC converters
167(1)
5.2.3 Studying AC/DC interactions
167(2)
5.2.4 Simplified modeling of the HVDC network
169(1)
5.2.5 Methods of causal analysis of AC/DC interactions
170(2)
5.3 Characterization of the input impedances/admittances of equipment
172(18)
5.3.1 Analytical characterization of the input impedance of systems in electrical engineering
173(14)
5.3.2 Experimental and simulation characterization
187(3)
5.4 Analysis of asymptotic stability via methods, based on impedance specifications
190(16)
5.4.1 Introduction
190(1)
5.4.2 Principles: the case of a two-body cascading system
191(15)
5.5 Analysis of asymptotic stability via the Routh-Hurwitz criterion
206(9)
5.5.1 Overview of the Routh-Hurwitz criterion
206(1)
5.5.2 Example, design charts
207(3)
5.5.3 Analysis of network architectures with regard to their stability
210(5)
5.6 Analysis tools for asymptotic global stability - dynamic behavior of an HVDC network subject to large-signal disturbances
215(4)
5.6.1 Introduction
215(1)
5.6.2 Analysis tools for large signal stability
216(3)
5.6.3 Conclusion
219(1)
5.7 Conclusion to the chapter
219(1)
5.8 Bibliography
220(3)
Chapter 6 Energy Management in Hybrid Electrical Systems with Storage
223(64)
Christophe Turpin
Stephan Astier
Xavier Roboam
Bruno Sareni
Hubert Piquet
6.1 Introduction to energy hybridization via the example of hybrid automobiles
224(5)
6.1.1 General information on the architectures of hybrid automobiles
224(1)
6.1.2 Parallel architecture: summation of the mechanical powers
225(1)
6.1.3 Series architecture: summation of the electric powers
226(2)
6.1.4 Series-parallel architecture
228(1)
6.2 Energy management in electric junction hybrid systems with electric energy storage
229(16)
6.2.1 Storage, essential properties, power invertibility, losses
229(4)
6.2.2 Electric junction hybrid systems, electric node
233(1)
6.2.3 Generic hybrid system with an electric node containing storage, energy flow management
234(2)
6.2.4 Strategy for frequency splitting of power via active filtering
236(3)
6.2.5 Electric node and energy degrees of freedom
239(3)
6.2.6 Overview of energy management in electric-junction multisource hybrid systems with storage: energy management strategy
242(3)
6.3 Indicators, criteria and data for the design of hybrid systems
245(5)
6.3.1 Properties of storage units for hybridization
245(2)
6.3.2 Mission properties, energy indicators
247(3)
6.4 Examples in various application areas
250(31)
6.4.1 Example
1. Simple hybridization: emergency generator for an aircraft based on a wind turbine hybridized by supercapacitors
250(6)
6.4.2 Example
2. Simple hybridization: emergency generator for an aircraft based on a fuel cell hybridized with supercapacitors
256(10)
6.4.3 Example
3. Double hybridization: power train of a locomotive based on a combustion engine hybridized by batteries and supercapacitors
266(9)
6.4.4 Example
4. Double hybridization: smoothing of photovoltaic generation via an electrolyzer-fuel cell tandem (H2/O2 battery) and a lead acid battery
275(6)
6.5 Conclusion for energy management in hybrid systems
281(2)
6.6 Bibliography
283(4)
Chapter 7 Stochastic Approach Applied to the Sizing of Energy Chains and Power Systems
287(38)
Patrick Guerin
Geoffroy Roblot
Laurence Miegeville
7.1 Introduction
287(2)
7.2 Standard principle of the power report
289(5)
7.2.1 Maximum current
290(1)
7.2.2 Load factor Ku
290(1)
7.2.3 Diversity factor Ks
291(1)
7.2.4 Enhancement factor Ka
292(1)
7.2.5 Application
292(2)
7.3 Stochastic approach
294(3)
7.3.1 Observation
294(1)
7.3.2 Principle of the stochastic approach
295(2)
7.4 Modeling of the loads
297(5)
7.4.1 Different types of loads
298(1)
7.4.2 Modeling using a specification
299(2)
7.4.3 Modeling using experimental readings
301(1)
7.5 Simulation of the power flows
302(10)
7.5.1 Analytical method
302(2)
7.5.2 Monte Carlo method
304(2)
7.5.3 Application to an "on-board" power system
306(6)
7.6 Probabilistic and dynamic approach
312(7)
7.6.1 Modeling of the loads or associated electrical quantities
312(4)
7.6.2 Simulation of the power flows
316(1)
7.6.3 Application to the embedded network
317(2)
7.7 Conclusion
319(2)
7.8 Bibliography
321(4)
Chapter 8 Probabilistic Approach for Reliability of Power Systems
325(46)
Yvon Besanger
Jean-Pierre Rognon
8.1 Contextual elements
325(6)
8.2 Basic concepts of the Monte Carlo simulation
331(9)
8.2.1 Monte Carlo method
331(1)
8.2.2 Simulation
331(1)
8.2.3 Basic statistical concepts and definitions
331(2)
8.2.4 Monte Carlo simulation
333(7)
8.3 Variance reduction
340(23)
8.3.1 Justification and principles
340(2)
8.3.2 Comparative study of the variance reduction methods
342(21)
8.4 Illustrative example
363(4)
8.5 Conclusion
367(1)
8.6 Bibliography
368(3)
List of Authors 371(2)
Index 373
Xavier Roboam is full researcher as Director of Research at CNRS, Toulouse, France.
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