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Electrical Energy Storage for Buildings in Smart Grids.

By: Contributor(s): Material type: TextTextPublisher: Newark : John Wiley & Sons, Incorporated, 2019Copyright date: ©2019Edition: 1st edDescription: 1 online resource (401 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781119058670
Subject(s): Genre/Form: Additional physical formats: Print version:: Electrical Energy Storage for Buildings in Smart GridsDDC classification:
  • 621.31/26
LOC classification:
  • TJ165 .R639 2019
Online resources:
Contents:
Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword -- Introduction -- 1. Storing Electrical Energy in Habitat: Toward "Smart Buildings" and "Smart Cities" -- 1.1. Toward smarter electrical grids -- 1.1.1. The move to decentralize electrical grids -- 1.1.2. Smart grids -- 1.2. Storage requirements in buildings -- 1.3. Difficulties in storing electrical energy -- 1.4. Electricity supply in buildings -- 1.4.1. Building supply and consumption -- 1.4.2. Self-production and self-consumption -- 1.4.3. Micro-grids -- 1.5. Smart buildings -- 1.6. Smart cities -- 1.7. Socio-economic questions -- 1.7.1. Toward new economic models -- 1.7.2. Social acceptability -- 1.8. Storage management -- 1.9. Methodologies used in developing energy management for storage systems -- 2. Energy Storage in a Commercial Building -- 2.1. Introduction -- 2.2. Managing energy storage in a supermarket -- 2.2.1. Introduction -- 2.2.2. System characteristics -- 2.2.3. Electricity billing -- 2.2.4. Objectives of the energy management strategy -- 2.2.5. Fuzzy logic supervisor -- 2.2.6. Simulation -- 2.2.7. Performance analysis using indicators -- 2.3. Conclusion -- 2.4. Acknowledgments -- 3. Energy Storage in a Tertiary Building, Combining Photovoltaic Panels and LED Lighting -- 3.1. Introduction -- 3.2. DC network architecture -- 3.3. Energy management -- 3.3.1. Specification -- 3.3.2. System inputs/outputs -- 3.3.3. Functional graph -- 3.3.4. Determination of membership functions -- 3.3.5. Operational graph -- 3.3.6. Fuzzy rules -- 3.4. Simulation results -- 3.4.1. Case 1: favorable grid access conditions (GAC) -- 3.4.2. Case 2: unfavorable GACs -- 3.4.3. Case 3: variable GAC -- 3.4.4. Comparison of results -- 3.5. Conclusion -- 3.6. Acknowledgments -- 4. Hybrid Storage Associated with Photovoltaic Technology for Buildings in Non-interconnected Zones.
4.1. Introduction -- 4.2. Photovoltaic systems in buildings and integration into the grid -- 4.2.1. Context and economic issues -- 4.2.2. Examples of projects -- 4.3. Importance of storage in photovoltaic systems -- 4.3.1. Photovoltaic systems for isolated sites -- 4.3.2. Photovoltaic systems connected to the grid -- 4.3.3. Hybrid storage -- 4.3.4. Electronic conversion structures for hybrid storage -- 4.4. Photovoltaic generator with hybrid storage system -- 4.4.1. Case study -- 4.4.2. Principles and standards for frequency support -- 4.4.3. Calculating battery wear -- 4.5. Energy management -- 4.5.1. Methodology -- 4.5.2. Operating specifications -- 4.5.3. Supervisor structure and determination of input/output -- 4.5.4. Functional graphs -- 4.5.5. Membership functions -- 4.5.6. Operating graphs -- 4.5.7. Fuzzy rules -- 4.5.8. Evaluation indicators -- 4.6. Simulation results -- 4.6.1. Supervisor validation -- 4.6.2. Life expectancy of storage elements -- 4.6.3. Efficiency -- 4.6.4. Levelized cost of energy -- 4.7. Experimental validation of energy management -- 4.7.1. Definition of tests -- 4.7.2. Experimental results -- 4.8. Conclusion -- 4.9. Acknowledgments -- 5. Economic and Sociological Implications of Smart Grids -- 5.1. Introduction -- 5.2. Actor diversity in smart grids -- 5.3. Economic and sociological implications of smart grids -- 5.3.1. Introduction -- 5.3.2. Implications of smart grids for the value chain -- 5.3.3. The "downstream" role of smart grids -- 5.3.4. The "upstream" role of smart grids -- 5.3.5. Demand management programs -- 5.4. Social acceptability -- 5.4.1. Introduction -- 5.4.2. Conceptual frameworks: points of reference -- 5.4.3. Studies of social acceptability -- 5.4.4. Theoretical application of voluntary load reduction within a reference framework -- 5.4.5. Quality of the load reduction contract -- 5.5. Conclusion.
5.6. Acknowledgments -- 6. Energy Mutualization for Tertiary Buildings, Residential Buildings and Producers -- 6.1. Introduction -- 6.2. Energy mutualization between commercial, tertiary and residential buildings, producers and grid managers -- 6.2.1. Grid actors -- 6.2.2. Energy service aggregator -- 6.2.3. Case study: structure of the micro-grid -- 6.2.4. Consumption and production profiles of actors in the micro-grid -- 6.3. Management of energy mutualization for tertiary buildings, residential buildings and energy producers -- 6.3.1. Objectives and constraints of actors in the micro-grid -- 6.3.2. Supervisor structure: input and output variables -- 6.3.3. Functional graphs -- 6.3.4. Membership functions -- 6.3.5. Operating graphs -- 6.3.6. Fuzzy rules -- 6.3.7. Indicators -- 6.4. Case study -- 6.4.1. Characteristics of the micro-grid -- 6.4.2. Scenarios -- 6.5. Load reduction -- 6.5.1. Load reduction principle -- 6.5.2. Introduction to load reduction and acceptability -- 6.5.3. Simulation of energy management with load reduction -- 6.6. Conclusion -- 6.7. Acknowledgments -- 6.8. Appendix 1 -- 7. Centralized Management of a Local Energy Community to Maximize Self-consumption of PV Production -- 7.1. Introduction -- 7.2. Energy management issues in residential neighborhoods -- 7.2.1. Electric grid management: basic principles -- 7.2.2. The move toward smart grids -- 7.2.3. A few applications of micro-grids for managing local energy communities -- 7.3. The active PV generator -- 7.3.1. Current PV production -- 7.3.2. Limits and necessary developments -- 7.3.3. Cascade structure -- 7.3.4. Domestic application -- 7.3.5. Energy management of the DC bus -- 7.3.6. Energy management of ultracapacitors -- 7.4. Micro-grid management -- 7.4.1. Organization of electrical grid management -- 7.4.2. Key functions.
7.4.3. Characteristics of local controllers for distributed production -- 7.4.4. Fundamentals of power balancing -- 7.4.5. Load management -- 7.5. Application to the context of a residential electrical network -- 7.5.1. From managing domestic demand to managing domestic production -- 7.5.2. Residential grids and application of micro-grid concepts -- 7.5.3. Energy management of a micro-grid -- 7.6. Prediction techniques and data processing -- 7.6.1. Predicting PV production -- 7.6.2. Load prediction -- 7.6.3. Energy estimation -- 7.7. Day ahead operational planning and half-hourly power reference calculations -- 7.7.1. Objectives -- 7.7.2. Constraints -- 7.7.3. Determinist algorithm for generator use -- 7.7.4. Practical application -- 7.8. Medium-term energy management -- 7.8.1. Reducing observed deviations -- 7.8.2. Energy management to minimize the aging of batteries -- 7.9. Short-term energy management -- 7.9.1. Primary frequency regulation -- 7.9.2. Power balancing strategies in the active generator -- 7.10. Experimental testing using real-time simulation -- 7.10.1. Benefits of real-time simulation -- 7.10.2. The Electrical Power Management Lab -- 7.10.3. Experimental implementation -- 7.10.4. Analysis of self-consumption in a house -- 7.10.5. Increasing the proportion of PV use in a residential grid -- 7.11. Review of scientific contributions and methodological summary -- 7.12. Concluding thoughts and research perspectives -- 8. Reversible Charging from Electric Vehicles to Grids and Buildings -- 8.1. Introduction -- 8.2. Reversible charging of electric vehicles -- 8.2.1. Vehicle to Grid -- 8.2.2. Vehicle to Home and to Building -- 8.2.3. Vehicle to Station and energy hubs -- 8.2.4. Energy service aggregator -- 8.3. Potential services and energy management of reversible EV fleets -- 8.3.1. Services supplied by V2G.
8.3.2. Energy management of a V2G fleet -- 8.4. Vehicle to Station: V2S -- 8.4.1. Impact and contribution of EVs in a railway station carpark -- 8.4.2. V2S: contribution of V2G technology in a station parking lot -- 8.5. V2H -- 8.6. Conclusion -- 8.7. Acknowledgments -- 8.8. Appendix -- 8.8.1. Detailed functional graphs for the V2G application -- References -- Index -- Other titles from iSTE in Energy -- EULA.
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Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword -- Introduction -- 1. Storing Electrical Energy in Habitat: Toward "Smart Buildings" and "Smart Cities" -- 1.1. Toward smarter electrical grids -- 1.1.1. The move to decentralize electrical grids -- 1.1.2. Smart grids -- 1.2. Storage requirements in buildings -- 1.3. Difficulties in storing electrical energy -- 1.4. Electricity supply in buildings -- 1.4.1. Building supply and consumption -- 1.4.2. Self-production and self-consumption -- 1.4.3. Micro-grids -- 1.5. Smart buildings -- 1.6. Smart cities -- 1.7. Socio-economic questions -- 1.7.1. Toward new economic models -- 1.7.2. Social acceptability -- 1.8. Storage management -- 1.9. Methodologies used in developing energy management for storage systems -- 2. Energy Storage in a Commercial Building -- 2.1. Introduction -- 2.2. Managing energy storage in a supermarket -- 2.2.1. Introduction -- 2.2.2. System characteristics -- 2.2.3. Electricity billing -- 2.2.4. Objectives of the energy management strategy -- 2.2.5. Fuzzy logic supervisor -- 2.2.6. Simulation -- 2.2.7. Performance analysis using indicators -- 2.3. Conclusion -- 2.4. Acknowledgments -- 3. Energy Storage in a Tertiary Building, Combining Photovoltaic Panels and LED Lighting -- 3.1. Introduction -- 3.2. DC network architecture -- 3.3. Energy management -- 3.3.1. Specification -- 3.3.2. System inputs/outputs -- 3.3.3. Functional graph -- 3.3.4. Determination of membership functions -- 3.3.5. Operational graph -- 3.3.6. Fuzzy rules -- 3.4. Simulation results -- 3.4.1. Case 1: favorable grid access conditions (GAC) -- 3.4.2. Case 2: unfavorable GACs -- 3.4.3. Case 3: variable GAC -- 3.4.4. Comparison of results -- 3.5. Conclusion -- 3.6. Acknowledgments -- 4. Hybrid Storage Associated with Photovoltaic Technology for Buildings in Non-interconnected Zones.

4.1. Introduction -- 4.2. Photovoltaic systems in buildings and integration into the grid -- 4.2.1. Context and economic issues -- 4.2.2. Examples of projects -- 4.3. Importance of storage in photovoltaic systems -- 4.3.1. Photovoltaic systems for isolated sites -- 4.3.2. Photovoltaic systems connected to the grid -- 4.3.3. Hybrid storage -- 4.3.4. Electronic conversion structures for hybrid storage -- 4.4. Photovoltaic generator with hybrid storage system -- 4.4.1. Case study -- 4.4.2. Principles and standards for frequency support -- 4.4.3. Calculating battery wear -- 4.5. Energy management -- 4.5.1. Methodology -- 4.5.2. Operating specifications -- 4.5.3. Supervisor structure and determination of input/output -- 4.5.4. Functional graphs -- 4.5.5. Membership functions -- 4.5.6. Operating graphs -- 4.5.7. Fuzzy rules -- 4.5.8. Evaluation indicators -- 4.6. Simulation results -- 4.6.1. Supervisor validation -- 4.6.2. Life expectancy of storage elements -- 4.6.3. Efficiency -- 4.6.4. Levelized cost of energy -- 4.7. Experimental validation of energy management -- 4.7.1. Definition of tests -- 4.7.2. Experimental results -- 4.8. Conclusion -- 4.9. Acknowledgments -- 5. Economic and Sociological Implications of Smart Grids -- 5.1. Introduction -- 5.2. Actor diversity in smart grids -- 5.3. Economic and sociological implications of smart grids -- 5.3.1. Introduction -- 5.3.2. Implications of smart grids for the value chain -- 5.3.3. The "downstream" role of smart grids -- 5.3.4. The "upstream" role of smart grids -- 5.3.5. Demand management programs -- 5.4. Social acceptability -- 5.4.1. Introduction -- 5.4.2. Conceptual frameworks: points of reference -- 5.4.3. Studies of social acceptability -- 5.4.4. Theoretical application of voluntary load reduction within a reference framework -- 5.4.5. Quality of the load reduction contract -- 5.5. Conclusion.

5.6. Acknowledgments -- 6. Energy Mutualization for Tertiary Buildings, Residential Buildings and Producers -- 6.1. Introduction -- 6.2. Energy mutualization between commercial, tertiary and residential buildings, producers and grid managers -- 6.2.1. Grid actors -- 6.2.2. Energy service aggregator -- 6.2.3. Case study: structure of the micro-grid -- 6.2.4. Consumption and production profiles of actors in the micro-grid -- 6.3. Management of energy mutualization for tertiary buildings, residential buildings and energy producers -- 6.3.1. Objectives and constraints of actors in the micro-grid -- 6.3.2. Supervisor structure: input and output variables -- 6.3.3. Functional graphs -- 6.3.4. Membership functions -- 6.3.5. Operating graphs -- 6.3.6. Fuzzy rules -- 6.3.7. Indicators -- 6.4. Case study -- 6.4.1. Characteristics of the micro-grid -- 6.4.2. Scenarios -- 6.5. Load reduction -- 6.5.1. Load reduction principle -- 6.5.2. Introduction to load reduction and acceptability -- 6.5.3. Simulation of energy management with load reduction -- 6.6. Conclusion -- 6.7. Acknowledgments -- 6.8. Appendix 1 -- 7. Centralized Management of a Local Energy Community to Maximize Self-consumption of PV Production -- 7.1. Introduction -- 7.2. Energy management issues in residential neighborhoods -- 7.2.1. Electric grid management: basic principles -- 7.2.2. The move toward smart grids -- 7.2.3. A few applications of micro-grids for managing local energy communities -- 7.3. The active PV generator -- 7.3.1. Current PV production -- 7.3.2. Limits and necessary developments -- 7.3.3. Cascade structure -- 7.3.4. Domestic application -- 7.3.5. Energy management of the DC bus -- 7.3.6. Energy management of ultracapacitors -- 7.4. Micro-grid management -- 7.4.1. Organization of electrical grid management -- 7.4.2. Key functions.

7.4.3. Characteristics of local controllers for distributed production -- 7.4.4. Fundamentals of power balancing -- 7.4.5. Load management -- 7.5. Application to the context of a residential electrical network -- 7.5.1. From managing domestic demand to managing domestic production -- 7.5.2. Residential grids and application of micro-grid concepts -- 7.5.3. Energy management of a micro-grid -- 7.6. Prediction techniques and data processing -- 7.6.1. Predicting PV production -- 7.6.2. Load prediction -- 7.6.3. Energy estimation -- 7.7. Day ahead operational planning and half-hourly power reference calculations -- 7.7.1. Objectives -- 7.7.2. Constraints -- 7.7.3. Determinist algorithm for generator use -- 7.7.4. Practical application -- 7.8. Medium-term energy management -- 7.8.1. Reducing observed deviations -- 7.8.2. Energy management to minimize the aging of batteries -- 7.9. Short-term energy management -- 7.9.1. Primary frequency regulation -- 7.9.2. Power balancing strategies in the active generator -- 7.10. Experimental testing using real-time simulation -- 7.10.1. Benefits of real-time simulation -- 7.10.2. The Electrical Power Management Lab -- 7.10.3. Experimental implementation -- 7.10.4. Analysis of self-consumption in a house -- 7.10.5. Increasing the proportion of PV use in a residential grid -- 7.11. Review of scientific contributions and methodological summary -- 7.12. Concluding thoughts and research perspectives -- 8. Reversible Charging from Electric Vehicles to Grids and Buildings -- 8.1. Introduction -- 8.2. Reversible charging of electric vehicles -- 8.2.1. Vehicle to Grid -- 8.2.2. Vehicle to Home and to Building -- 8.2.3. Vehicle to Station and energy hubs -- 8.2.4. Energy service aggregator -- 8.3. Potential services and energy management of reversible EV fleets -- 8.3.1. Services supplied by V2G.

8.3.2. Energy management of a V2G fleet -- 8.4. Vehicle to Station: V2S -- 8.4.1. Impact and contribution of EVs in a railway station carpark -- 8.4.2. V2S: contribution of V2G technology in a station parking lot -- 8.5. V2H -- 8.6. Conclusion -- 8.7. Acknowledgments -- 8.8. Appendix -- 8.8.1. Detailed functional graphs for the V2G application -- References -- Index -- Other titles from iSTE in Energy -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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