Electrical Energy Storage for Buildings in Smart Grids

Current developments in the renewable energy field, and the trend toward self-production and self-consumption of energy, has led to increased interest in the means of storing electrical energy; a key element of sustainable development.

This book provides an in-depth view of the environmentally responsible energy solutions currently available for use in the building sector. It highlights the importance of storing electrical energy, demonstrates the many services that the storage of electrical energy can bring, and discusses the important socio-economic factors related to the emergence of smart buildings and smart grids. Finally, it presents the methodological tools needed to build a system of storage-based energy management, illustrated by concrete, pedagogic examples.

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 xi

Introduction xiii

Chapter 1. Storing Electrical Energy in Habitat: Toward “Smart Buildings” and “Smart Cities” 1

1.1. Toward smarter electrical grids 1

1.1.1. The move to decentralize electrical grids 1

1.1.2. Smart grids 2

1.2. Storage requirements in buildings 4

1.3. Difficulties in storing electrical energy 5

1.4. Electricity supply in buildings 7

1.4.1. Building supply and consumption 7

1.4.2. Self-production and self-consumption 10

1.4.3. Micro-grids 11

1.5. Smart buildings 14

1.6. Smart cities 18

1.7. Socio-economic questions 19

1.7.1. Toward new economic models 19

1.7.2. Social acceptability 20

1.8. Storage management 22

1.9. Methodologies used in developing energy management for storage systems 24

Chapter 2. Energy Storage in a Commercial Building 27

2.1. Introduction 27

2.2. Managing energy storage in a supermarket 27

2.2.1. Introduction 27

2.2.2. System characteristics 28

2.2.3. Electricity billing 31

2.2.4. Objectives of the energy management strategy 32

2.2.5. Fuzzy logic supervisor 33

2.2.6. Simulation 46

2.2.7. Performance analysis using indicators 49

2.3. Conclusion 51

2.4. Acknowledgments 52

Chapter 3. Energy Storage in a Tertiary Building, Combining Photovoltaic Panels and LED Lighting 53

3.1. Introduction 53

3.2. DC network architecture 55

3.3. Energy management 56

3.3.1. Specification 56

3.3.2. System inputs/outputs 58

3.3.3. Functional graph 59

3.3.4. Determination of membership functions 61

3.3.5. Operational graph 63

3.3.6. Fuzzy rules 63

3.4. Simulation results 66

3.4.1. Case 1: favorable grid access conditions (GAC) 68

3.4.2. Case 2: unfavorable GACs 69

3.4.3. Case 3: variable GAC 70

3.4.4. Comparison of results 73

3.5. Conclusion 74

3.6. Acknowledgments 75

Chapter 4. Hybrid Storage Associated with Photovoltaic Technology for Buildings in Non-interconnected Zones 77

4.1. Introduction 77

4.2. Photovoltaic systems in buildings and integration into the grid 78

4.2.1. Context and economic issues 78

4.2.2. Examples of projects 80

4.3. Importance of storage in photovoltaic systems 85

4.3.1. Photovoltaic systems for isolated sites 85

4.3.2. Photovoltaic systems connected to the grid 85

4.3.3. Hybrid storage 86

4.3.4. Electronic conversion structures for hybrid storage 88

4.4. Photovoltaic generator with hybrid storage system 91

4.4.1. Case study 91

4.4.2. Principles and standards for frequency support 93

4.4.3. Calculating battery wear 97

4.5. Energy management 99

4.5.1. Methodology 99

4.5.2. Operating specifications 100

4.5.3. Supervisor structure and determination of input/output 101

4.5.4. Functional graphs 103

4.5.5. Membership functions 105

4.5.6. Operating graphs 108

4.5.7. Fuzzy rules 110

4.5.8. Evaluation indicators 113

4.6. Simulation results 114

4.6.1. Supervisor validation 115

4.6.2. Life expectancy of storage elements 120

4.6.3. Efficiency 123

4.6.4. Levelized cost of energy 126

4.7. Experimental validation of energy management 128

4.7.1. Definition of tests 128

4.7.2. Experimental results 129

4.8. Conclusion 132

4.9. Acknowledgments 134

Chapter 5. Economic and Sociological Implications of Smart Grids 135

5.1. Introduction 135

5.2. Actor diversity in smart grids 137

5.3. Economic and sociological implications of smart grids 138

5.3.1. Introduction 138

5.3.2. Implications of smart grids for the value chain 141

5.3.3. The “downstream” role of smart grids 150

5.3.4. The “upstream” role of smart grids 160

5.3.5. Demand management programs 166

5.4. Social acceptability 169

5.4.1. Introduction 169

5.4.2. Conceptual frameworks: points of reference 170

5.4.3. Studies of social acceptability 174

5.4.4. Theoretical application of voluntary load reduction within a reference framework 181

5.4.5. Quality of the load reduction contract 191

5.5. Conclusion 195

5.6. Acknowledgments 196

Chapter 6. Energy Mutualization for Tertiary Buildings, Residential Buildings and Producers 197

6.1. Introduction 197

6.2. Energy mutualization between commercial, tertiary and residential buildings, producers and grid managers 198

6.2.1. Grid actors 198

6.2.2. Energy service aggregator 199

6.2.3. Case study: structure of the micro-grid 201

6.2.4. Consumption and production profiles of actors in the micro-grid 203

6.3. Management of energy mutualization for tertiary buildings, residential buildings and energy producers 205

6.3.1. Objectives and constraints of actors in the micro-grid 206

6.3.2. Supervisor structure: input and output variables 210

6.3.3. Functional graphs 211

6.3.4. Membership functions 212

6.3.5. Operating graphs 217

6.3.6. Fuzzy rules 217

6.3.7. Indicators 221

6.4. Case study 221

6.4.1. Characteristics of the micro-grid 221

6.4.2. Scenarios 222

6.5. Load reduction 228

6.5.1. Load reduction principle 228

6.5.2. Introduction to load reduction and acceptability 229

6.5.3. Simulation of energy management with load reduction 231

6.6. Conclusion 233

6.7. Acknowledgments 233

6.8. Appendix 1 234

Chapter 7. Centralized Management of a Local Energy Community to Maximize Self-consumption of PV Production 235

7.1. Introduction 235

7.2. Energy management issues in residential neighborhoods 242

7.2.1. Electric grid management: basic principles 242

7.2.2. The move toward smart grids 243

7.2.3. A few applications of micro-grids for managing local energy communities 246

7.3. The active PV generator 249

7.3.1. Current PV production 249

7.3.2. Limits and necessary developments 249

7.3.3. Cascade structure 250

7.3.4. Domestic application 251

7.3.5. Energy management of the DC bus 254

7.3.6. Energy management of ultracapacitors 261

7.4. Micro-grid management 263

7.4.1. Organization of electrical grid management 263

7.4.2. Key functions 264

7.4.3. Characteristics of local controllers for distributed production 268

7.4.4. Fundamentals of power balancing 268

7.4.5. Load management 270

7.5. Application to the context of a residential electrical network 270

7.5.1. From managing domestic demand to managing domestic production 270

7.5.2. Residential grids and application of micro-grid concepts 273

7.5.3. Energy management of a micro-grid 277

7.6. Prediction techniques and data processing 278

7.6.1. Predicting PV production 278

7.6.2. Load prediction 279

7.6.3. Energy estimation 281

7.7. Day ahead operational planning and half-hourly power reference calculations 283

7.7.1. Objectives 283

7.7.2. Constraints 283

7.7.3. Determinist algorithm for generator use 284

7.7.4. Practical application 287

7.8. Medium-term energy management 289

7.8.1. Reducing observed deviations 289

7.8.2. Energy management to minimize the aging of batteries 290

7.9. Short-term energy management 292

7.9.1. Primary frequency regulation 292

7.9.2. Power balancing strategies in the active generator 292

7.10. Experimental testing using real-time simulation 294

7.10.1. Benefits of real-time simulation 294

7.10.2. The Electrical Power Management Lab 295

7.10.3. Experimental implementation 297

7.10.4. Analysis of self-consumption in a house 300

7.10.5. Increasing the proportion of PV use in a residential grid 306

7.11. Review of scientific contributions and methodological summary 312

7.12. Concluding thoughts and research perspectives 313

Chapter 8. Reversible Charging from Electric Vehicles to Grids and Buildings 317

8.1. Introduction 317

8.2. Reversible charging of electric vehicles 319

8.2.1. Vehicle to Grid 319

8.2.2. Vehicle to Home and to Building 323

8.2.3. Vehicle to Station and energy hubs 324

8.2.4. Energy service aggregator 325

8.3. Potential services and energy management of reversible EV fleets 325

8.3.1. Services supplied by V2G 325

8.3.2. Energy management of a V2G fleet 328

8.4. Vehicle to Station: V2S 340

8.4.1. Impact and contribution of EVs in a railway station carpark 340

8.4.2. V2S: contribution of V2G technology in a station parking lot 344

8.5. V2H 348

8.6. Conclusion 352

8.7. Acknowledgments 353

8.8. Appendix 353

8.8.1. Detailed functional graphs for the V2G application 353

References 355

Index 369

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