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    1. Kultur
    2. Arkitektur

    Electrical Energy Storage in Transportation Systems

    AvBenoît Robyns,Christophe Saudemont

    Inbunden, Engelska, 2016

    1 855 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    This book deals with the management and valuation of energy storage in electric power grids, highlighting the interest of storage systems in grid applications and developing management methodologies based on artificial intelligence tools. The authors highlight the importance of storing electrical energy, in the context of sustainable development, in "smart cities" and "smart transportation", and discuss multiple services that storing electrical energy can bring.Methodological tools are provided to build an energy management system storage following a generic approach. These tools are based on causal formalisms, artificial intelligence and explicit optimization techniques and are presented throughout the book in connection with concrete case studies.

    Produktinformation

    • Utgivningsdatum:2016-08-16
    • Mått:165 x 241 x 28 mm
    • Vikt:671 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:348
    • Förlag:ISTE Ltd and John Wiley & Sons Inc
    • ISBN:9781848219809

    Utforska kategorier

    • Arkitektur inom Kultur
    • Byggnadsteknik inom Naturvetenskap och teknik

    Mer om författaren

    Benoît Robyns is Research Director at the École des Hautes Etudes d'Ingénieur (HEI) in Lille, France.Christophe Saudemont is Professor at the École des Hautes Etudes d'Ingénieur (HEI) in Lille, France.Daniel Hissel is Full Professor at University Bourgogne Franche-Comté in Belfort, France.Xavier Roboam is CNRS Research Director at LAPLACE (Laboratory of plasma and conversion of energy) in Toulouse, France.Bruno Sareni is Full Professor at the University of Toulouse, INP-ENSEEIHT, France and the LAPLACE research laboratory.Julien Pouget is Research Engineer for the French national railway company, SNCF, France.

    Innehållsförteckning

    • Foreword  ixIntroduction  xiChapter 1. Issues in Electrical Energy Storage for Transport Systems 11.1. Storage requirements for transport systems  11.2. Difficulties of storing electrical energy  31.3. The electrical power supply of transport systems  61.4. Storage management 81.4.1. Specifications 111.4.2. Supervisor structure 111.4.3. Functional graphs 111.4.4. Membership functions  121.4.5. Functional graphs 141.4.6. Rules  151.4.7. Indicators  151.4.8. Optimization of supervisor parameters  161.4.9. Type-2 fuzzy logic  171.4.10. Methodologies for the development of energy management in a storage system 17Chapter 2. Local DC Grid with Energy Exchange for Applications in Aviation 192.1. Introduction 192.2. Onboard grid  222.3. Local DC grid 232.4. Supervisor design methodology 262.5. Specifications 272.5.1. Objectives 272.5.2. Constraints 272.5.3. Means of action  272.6. Supervisor structure  282.6.1. Input values  282.6.2. Output values 282.7. Selection of design tools 292.8. Identification of different operating states: the functional graph 312.8.1. General functional graph  312.8.2. Functional subgraphs 332.9. Tools 412.10. Membership functions  412.11. Operational graph  452.12. Fuzzy rules  532.13. Experimental validation 572.13.1. Supervisor implementation  572.13.2. Experimental configuration  622.13.3. Results and analyses  632.14. Fuzzy supervisor optimization 722.14.1. Supervisor optimization methodology based on fuzzy rules 722.14.2. Application at levels N1 and N2 782.15. Conclusion  92Chapter 3. Electric and Hybrid Vehicles 953.1. Introduction 953.2. Storage technologies in hybrids and EVs 993.3. Development of EVs and interaction with electric power grids  1003.3.1. Issues in the development of EVs 1003.3.2. Charge of EVs 1013.3.3. Issues in the electric power grid integration 1023.4. EV charging supervision 1033.4.1. Introduction  1033.4.2. EV charging models 1043.4.3. Electric power distribution grid  1083.4.4. Supervision  1123.4.5. Results 1223.5. The reversible charge of EVs  1253.5.1. Introduction  1253.5.2. Vehicle-to-grid and contribution of the reversible charge to the electric power grids 1253.5.3. Vehicle-to-home and contribution of the reversible charge to buildings 1273.6. Configurations and operating principle of HV  1283.6.1. Hybridization levels 1283.6.2. Configurations of power trains 1293.7. Energy management in a hybrid vehicle  1313.7.1. Introduction  1313.7.2. Fuzzy logic for energy management  1323.7.3. Type-2 fuzzy logic  1323.7.4. Application to the energy management of an EV  1393.8. Conclusion 146Chapter 4. Railway System: Diesel–Electric Hybrid Power Train 1474.1. Introduction 1474.2. Design of an autonomous hybrid locomotive 1514.2.1. Introduction to the issues in design and energy management within the framework of the PLATHEE project  1514.2.2. Frequency management strategy  1574.2.3. Importance and processing of railway assignments  1634.2.4. Sequential design: from dimensioning to analysis 1714.2.5 Implementation of the PLATHEE demonstrator 2004.3. Conclusion 2164.4. Exercise: definition of the energy requirements in the railway sector and application of storage to electric traction 2174.4.1. Kinematic study of a train  2184.4.2. Study on energy profile of a train 2274.4.3. Basic design and comparison of energy storage system technologies for railway applications 2404.5. Appendices 2494.5.1. Technical characteristics of storage sources and components carried on board the PLATHEE 249Chapter 5. Railway System: Hybrid Railway Power Substation 2555.1. Introduction 2555.2. Hybrid railway power substations 2605.2.1. Issues in the railway electrification system  2605.2.2. The HRPS solution  2655.2.3. State-of-the-art of the HRPS  2675.3. Energy management in an HRPS  2795.3.1. Methodology 2795.3.2. Technical specifications 2805.3.3. Supervisor structure 2835.3.4. Determination of the functional graphs of the short-term supervisor  2845.3.5. Membership functions  2895.3.6. Determination of functional graphs  2915.3.7. Fuzzy rules 2955.3.8. Performance indicators 2955.3.9. Modeling and results 2985.3.10. Energy management optimization  3025.4. Experimentation of an HRPS and sensitivity analysis  3095.5. Railway smart grid perspective 3165.6. Conclusion 3185.7. Acknowledgments 318Bibliography  319Index 329