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