Electrical Energy Storage for Buildings in Smart Grids

Benoît Robyns is Research Director at HEI-Yncréa Lille, and Vice President of Energy and Societal Transition at Lille Catholic University. He is the head of the "Power Systems" team at L2EP.Arnaud Davigny is a lecturer at HEI-Yncréa Lille and researcher at L2EP.Hervé Barry is a lecturer at Lille Catholic University, Faculty of Management, Economics and Sciences.Sabine Kazmierczak is a lecturer at Lille Catholic University, Faculty of Management, Economics and Sciences.Christophe Saudemont is a Professor at HEI-Yncréa Lille and researcher at L2EP.Dhaker Abbes is a lecturer at HEI-Yncréa Lille and researcher at L2EP.Bruno François is a Professor at Ecole Centrale de Lille and researcher at L2EP.

• Foreword xiIntroduction xiiiChapter 1. Storing Electrical Energy in Habitat: Toward "Smart Buildings" and "Smart Cities" 11.1. Toward smarter electrical grids 11.1.1. The move to decentralize electrical grids 11.1.2. Smart grids 21.2. Storage requirements in buildings 41.3. Difficulties in storing electrical energy 51.4. Electricity supply in buildings 71.4.1. Building supply and consumption 71.4.2. Self-production and self-consumption 101.4.3. Micro-grids 111.5. Smart buildings 141.6. Smart cities 181.7. Socio-economic questions 191.7.1. Toward new economic models 191.7.2. Social acceptability 201.8. Storage management 221.9. Methodologies used in developing energy management for storage systems 24Chapter 2. Energy Storage in a Commercial Building 272.1. Introduction 272.2. Managing energy storage in a supermarket 272.2.1. Introduction 272.2.2. System characteristics 282.2.3. Electricity billing 312.2.4. Objectives of the energy management strategy 322.2.5. Fuzzy logic supervisor 332.2.6. Simulation 462.2.7. Performance analysis using indicators 492.3. Conclusion 512.4. Acknowledgments 52Chapter 3. Energy Storage in a Tertiary Building, Combining Photovoltaic Panels and LED Lighting 533.1. Introduction 533.2. DC network architecture 553.3. Energy management 563.3.1. Specification 563.3.2. System inputs/outputs 583.3.3. Functional graph 593.3.4. Determination of membership functions 613.3.5. Operational graph 633.3.6. Fuzzy rules 633.4. Simulation results 663.4.1. Case 1: favorable grid access conditions (GAC) 683.4.2. Case 2: unfavorable GACs 693.4.3. Case 3: variable GAC 703.4.4. Comparison of results 733.5. Conclusion 743.6. Acknowledgments 75Chapter 4. Hybrid Storage Associated with Photovoltaic Technology for Buildings in Non-interconnected Zones 774.1. Introduction 774.2. Photovoltaic systems in buildings and integration into the grid 784.2.1. Context and economic issues 784.2.2. Examples of projects 804.3. Importance of storage in photovoltaic systems 854.3.1. Photovoltaic systems for isolated sites 854.3.2. Photovoltaic systems connected to the grid 854.3.3. Hybrid storage 864.3.4. Electronic conversion structures for hybrid storage 884.4. Photovoltaic generator with hybrid storage system 914.4.1. Case study 914.4.2. Principles and standards for frequency support 934.4.3. Calculating battery wear 974.5. Energy management 994.5.1. Methodology 994.5.2. Operating specifications 1004.5.3. Supervisor structure and determination of input/output 1014.5.4. Functional graphs 1034.5.5. Membership functions 1054.5.6. Operating graphs 1084.5.7. Fuzzy rules 1104.5.8. Evaluation indicators 1134.6. Simulation results 1144.6.1. Supervisor validation 1154.6.2. Life expectancy of storage elements 1204.6.3. Efficiency 1234.6.4. Levelized cost of energy 1264.7. Experimental validation of energy management 1284.7.1. Definition of tests 1284.7.2. Experimental results 1294.8. Conclusion 1324.9. Acknowledgments 134Chapter 5. Economic and Sociological Implications of Smart Grids 1355.1. Introduction 1355.2. Actor diversity in smart grids 1375.3. Economic and sociological implications of smart grids 1385.3.1. Introduction 1385.3.2. Implications of smart grids for the value chain 1415.3.3. The “downstream” role of smart grids 1505.3.4. The “upstream” role of smart grids 1605.3.5. Demand management programs 1665.4. Social acceptability 1695.4.1. Introduction 1695.4.2. Conceptual frameworks: points of reference 1705.4.3. Studies of social acceptability 1745.4.4. Theoretical application of voluntary load reduction within a reference framework 1815.4.5. Quality of the load reduction contract 1915.5. Conclusion 1955.6. Acknowledgments 196Chapter 6. Energy Mutualization for Tertiary Buildings, Residential Buildings and Producers 1976.1. Introduction 1976.2. Energy mutualization between commercial, tertiary and residential buildings, producers and grid managers 1986.2.1. Grid actors 1986.2.2. Energy service aggregator 1996.2.3. Case study: structure of the micro-grid 2016.2.4. Consumption and production profiles of actors in the micro-grid 2036.3. Management of energy mutualization for tertiary buildings, residential buildings and energy producers 2056.3.1. Objectives and constraints of actors in the micro-grid 2066.3.2. Supervisor structure: input and output variables 2106.3.3. Functional graphs 2116.3.4. Membership functions 2126.3.5. Operating graphs 2176.3.6. Fuzzy rules 2176.3.7. Indicators 2216.4. Case study 2216.4.1. Characteristics of the micro-grid 2216.4.2. Scenarios 2226.5. Load reduction 2286.5.1. Load reduction principle 2286.5.2. Introduction to load reduction and acceptability 2296.5.3. Simulation of energy management with load reduction 2316.6. Conclusion 2336.7. Acknowledgments 2336.8. Appendix 1 234Chapter 7. Centralized Management of a Local Energy Community to Maximize Self-consumption of PV Production 2357.1. Introduction 2357.2. Energy management issues in residential neighborhoods 2427.2.1. Electric grid management: basic principles 2427.2.2. The move toward smart grids 2437.2.3. A few applications of micro-grids for managing local energy communities 2467.3. The active PV generator 2497.3.1. Current PV production 2497.3.2. Limits and necessary developments 2497.3.3. Cascade structure 2507.3.4. Domestic application 2517.3.5. Energy management of the DC bus 2547.3.6. Energy management of ultracapacitors 2617.4. Micro-grid management 2637.4.1. Organization of electrical grid management 2637.4.2. Key functions 2647.4.3. Characteristics of local controllers for distributed production 2687.4.4. Fundamentals of power balancing 2687.4.5. Load management 2707.5. Application to the context of a residential electrical network 2707.5.1. From managing domestic demand to managing domestic production 2707.5.2. Residential grids and application of micro-grid concepts 2737.5.3. Energy management of a micro-grid 2777.6. Prediction techniques and data processing 2787.6.1. Predicting PV production 2787.6.2. Load prediction 2797.6.3. Energy estimation 2817.7. Day ahead operational planning and half-hourly power reference calculations 2837.7.1. Objectives 2837.7.2. Constraints 2837.7.3. Determinist algorithm for generator use 2847.7.4. Practical application 2877.8. Medium-term energy management 2897.8.1. Reducing observed deviations 2897.8.2. Energy management to minimize the aging of batteries 2907.9. Short-term energy management 2927.9.1. Primary frequency regulation 2927.9.2. Power balancing strategies in the active generator 2927.10. Experimental testing using real-time simulation 2947.10.1. Benefits of real-time simulation 2947.10.2. The Electrical Power Management Lab 2957.10.3. Experimental implementation 2977.10.4. Analysis of self-consumption in a house 3007.10.5. Increasing the proportion of PV use in a residential grid 3067.11. Review of scientific contributions and methodological summary 3127.12. Concluding thoughts and research perspectives 313Chapter 8. Reversible Charging from Electric Vehicles to Grids and Buildings 3178.1. Introduction 3178.2. Reversible charging of electric vehicles 3198.2.1. Vehicle to Grid 3198.2.2. Vehicle to Home and to Building 3238.2.3. Vehicle to Station and energy hubs 3248.2.4. Energy service aggregator 3258.3. Potential services and energy management of reversible EV fleets 3258.3.1. Services supplied by V2G 3258.3.2. Energy management of a V2G fleet 3288.4. Vehicle to Station: V2S 3408.4.1. Impact and contribution of EVs in a railway station carpark 3408.4.2. V2S: contribution of V2G technology in a station parking lot 3448.5. V2H 3488.6. Conclusion 3528.7. Acknowledgments 3538.8. Appendix 3538.8.1. Detailed functional graphs for the V2G application 353References 355Index 369