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 grids’, 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.
Table des matières
1. Storage issues
2. State of the art of electrical energy storage
2.1. Introduction
2.2. Hydraulic storage
2.3. Thermal storage
2.4. Compressed air storage
2.5. Chemical storage
2.5.1. Electrochemical storage
2.5.2. Hydrogen storage
2.6. Kinetic storage
2.7. Electromagnetic storage
2.8. Electrostatic storage
2.9. Comparative performance storage technologies
2.10. Bibliography
3. Energy storage valorisation
3.1. Introduction
3.2. General characteristics of the components of an electricalsystem
3.2.1. The production
3.2.2. The consumption
3.2.3. The electrical grid
3.1.3.1. Transport network
3.1.3.2. Distribution network
3.1.3.3. Island network
3.2.4. The electrical grid management
3.3. Services which can be given by the storage
3.3.1. Transport network
3.3.1.1. Mandatory services
3.3.2.2. Complementary services for the TSO
3.3.2.3. Additional services for a centralized producer
3.3.2.4. Additional services for a decentralized producer
3.3.2. Distribution and island networks
3.3.2.1 Storage services for the distributor, the transporter, the producer and the consumer
3.3.2.2 Method for the sharing of distributed storageservices
3.4. Case study
3.5. Bibliography
4. Fuzzy logic for the management of storage associated withrenewable energy
4.1 Introduction
4.2 Introduction to fuzzy logic
4.2.1. Principles of fuzzy reasoning
4.2.2. Fuzzy logic and binary logic
4.2.3. Steps of a fuzzy supervisor
4.3. Wind and kinetic storage system association in islandnetwork with diesel generator
4.3.1. Introduction
4.3.2. Energy management strategy
4.3.3. Fuzzy logic supervisor
4.3.4. Simulation results
4.4. Bibliography
5. Supervisor design methodology of a wind generator associatedwith a storage system
5.1. Introduction
5.2 Variable speed wind generator associated with a kineticstorage system
5.2.1. Introduction
5.2.2. Energy management strategy
5.2.3. Fuzzy logic supervisor
5.2.4. Real time implementation and experimental results
5.3. Bibliography
6. Supervisor design of a hybrid system associating sources andstorage systems
6.1. Introduction
6.2. Supervisor design methodology of a hybrid sourceintegrating a wind generator
6.2.1. Determination of system specifications
6.2.2. Supervisor structure
6.2.3. Determination of functional graphs
6.2.4. Determination of membership functions
6.2.5. Determination of operational graphs
6.2.6. Extraction of the fuzzy rules
6.3. Comparative performance of different variants of hybridsource
6.3.1. Characteristics of the simulated system
6.3.3. Simulations of different variants of hybrid source
6.3.3. Performance comparison of different hybrid sources usingindicators
6.4. Bibliography
A propos de l’auteur
Benoit ROBYNS, Hautes Etudes d’Ingénieur, Lille, France
Bruno FRANCOIS, Ecole Centrale de Lille, France
Gauthier DELILLE, EDF, France
Christophe SAUDEMONT, Hautes Etudes d’Ingénieur, Lille, France
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