Smart Grids and Buildings for Energy and Societal Transition

Benoît Robyns is Director of Research at Junia Lille, Vice-President of Energy and Societal Transition at the Université Catholique de Lille and head of the Power System Team at L2EP, France. Laure Dobigny is an associate professor in the ETH+-ETHICS laboratory at the Université Catholique de Lille, France. Dhaker Abbes is a professor at Junia Lille and a researcher at L2EP, France. Benoit Durillon is a lecturer at Junia Lille and a researcher at L2EP, France. Hervé Barry is a sociologist at the FGES of the Université Catholique de Lille and a member of the Laboratoire Interdisciplinaire des Transitions de Lille (LITL), France. Christophe Saudemont is a professor at Junia Lille and a researcher at L2EP, France.

Foreword by Thierry Magnin xi

Foreword by Audrey Linkenheld xvii

Introduction xxv

Chapter 1. From Transition Challenges to Smart Grids and Smart Buildings 1

1.1. Introduction 1

1.2. Climatic challenges 3

1.3. Four inspiring social and climate scenarios 5

1.4. Sufficiency or prosperity 13

1.4.1. Personal, shared and organizational sufficiency 13

1.4.2. From smart sharing to wise sharing 14

1.4.3. From sufficiency to prosperity 16

1.4.4. Spirituality and ecological transition 19

1.5. Ethical and political issues 22

1.5.1. Ethical issues in the ecological transition 22

1.5.2. Questions of governance or the need to reinvent democracies 23

1.5.3. Eco-anxiety 29

1.6. Bifurcating research 31

1.7. Smarter energy networks 33

1.7.1. From 100% renewable energy to a combination of solutions 33

1.7.2. Towards the decentralization of electricity grids 36

1.7.3. Smart grids, self-generation and self-consumption 38

1.7.4. An increasingly miraculous electricity fairy – yes but? 39

1.8. Smarter buildings in a desirable habitat 45

1.8.1. Buildings and living spaces 45

1.8.2. Building trends in 2050 46

1.8.3. Smart buildings 47

1.9. Smart buildings as nodes of smart grids 50

1.10. Methodological contributions 52

1.11. The question of artificial intelligence 53

1.12. References 54

Chapter 2. Smart City, Smart Building, Smart User: The Imaginaries of Smart and its Dead Ends 59

2.1. Introduction 59

2.2. Reducing energy consumption: changing technologies or changing practices? 60

2.2.1. Limits to energy efficiency 60

2.2.2. Limits of an approach focused (solely) on practices 61

2.2.3. Usage dependence on the technology used 64

2.3. The smart imaginary and its dead ends 67

2.3.1. Technical distancing as a common denominator 68

2.3.2. The smart city or the imaginary of a city without inhabitants 68

2.3.3. The smart building or the imaginary of a building parasitized by its users 70

2.4. Conclusion: in search of the smart user? 71

2.5. References 73

Chapter 3. Forecasting the Production and Consumption of Electrical Energy 77

3.1. Introduction 77

3.2. Variability in production and consumption 78

3.3. Photovoltaic production forecast 80

3.3.1. Satellite image-based forecasting 82

3.3.2. Short-term forecast by camera 83

3.3.3. Neural network prediction 85

3.3.4. Case study: 24-hour production forecast for the photovoltaic power plant at the Université Catholique de Lille 89

3.4. Forecasting electricity consumption 96

3.4.1. Important factors for forecasting electricity consumption 96

3.4.2. Electricity consumption prediction methods 97

3.4.3. Case study: 24-hour forecast of electricity consumption for a block of buildings at the Université Catholique de Lille 98

3.5. Valorization of forecasts and feedback 104

3.5.1. Using forecasts to manage energy for the Université Catholique de Lille smart grid demonstrator 104

3.5.2. Load forecasting in a distribution network at a high-voltage/medium-voltage (HV/MV) source substation 107

3.5.3. The importance of meteorological forecasting 111

3.5.4. The importance of uncertainty analysis 112

3.5.5. Importance of database size and quality 113

3.6. Conclusion 113

3.7. Acknowledgments 114

3.8. References 114

Chapter 4. Taking Actors into Account in Energy Management Strategies 117

4.1. Introduction 117

4.2. A system of actors in an electrical network 120

4.2.1. The role of actors 120

4.2.2. System operator 121

4.2.3. Aggregator 121

4.2.4. Producer 122

4.2.5. Consumer 123

4.2.6. Consumer–producer (prosumer) 124

4.3. Methodology for managing energy flexibility involving actors 124

4.3.1. Defining key concepts 124

4.3.2. Comprehensive methodology for energy supervision 126

4.4. Modeling actor profiles 127

4.4.1. An interdisciplinary approach 127

4.4.2. Existing actor profiles 129

4.4.3. Observable profiles 132

4.4.4. Integrable profiles 132

4.5. Residential actor profiles 134

4.5.1. Return feedback from experimentation/scale-one projects 134

4.5.2. Consumer profile research 135

4.5.3. Sociological approaches for accepting participation in network management 136

4.5.4. Economic approaches for consumer involvement 138

4.5.5. The need for interdisciplinarity 139

4.5.6. Characterizing flexibility 140

4.5.7. Parameters influencing flexibility 144

4.6. Identification of residential actor profiles 147

4.6.1. Introduction 147

4.6.2. A microeconomic approach to price sensitivity 147

4.6.3. A sociological approach to environmental awareness 157

4.7. Profiles of selected residential actors 158

4.7.1. Economical 158

4.7.2. Eco-sensitive 159

4.7.3. Technophiles 159

4.7.4. Indifferent – moderate opportunists 159

4.7.5. Disengaged 159

4.7.6. Discussions 159

4.8. Conclusion 161

4.9. Acknowledgments 162

4.10. References 162

Chapter 5. Energy Supervision of a Local Residential Network with Actor Involvement 169

5.1. Introduction 169

5.2. Energy supervision methodology 170

5.3. Modeling a residential case study 171

5.3.1. Electricity network under consideration 171

5.3.2. Modeling consumption 172

5.3.3. Discussion of model limitations 174

5.4. Day ahead supervision (before D-1) 174

5.4.1. Discussion of predictive supervision 174

5.4.2. Implementing the D-1 supervisor 180

5.4.3. Scope statement 181

5.4.4. Modeling actor profiles 185

5.4.5. Supervisor structure 190

5.4.6. Global optimization and game theory 192

5.4.7. Local optimization using dynamic programming 195

5.5. Real-time supervision 198

5.5.1. Discussion of real-time supervision 198

5.5.2. Implementation of supervision in real time 202

5.5.3. Continuity with D-1 supervisor 202

5.5.4. Fuzzy logic supervisor 203

5.5.5. Indicators 213

5.6. Two-week prospective simulations of the global supervisor 213

5.6.1. Scenarios 213

5.6.2. Results and discussion 215

5.7. Conclusion 221

5.8. Acknowledgments 223

5.9. References 223

Chapter 6. Self-Consumption within a Local Renewable Energy Community 227

6.1. Introduction 227

6.2. Local renewable energy communities 230

6.3. Modeling a tertiary-sector case study 231

6.3.1. Historic block at the Université Catholique de Lille 231

6.3.2. Modeling the electrical network 233

6.4. Distributed energy optimization 234

6.4.1. Introduction 234

6.4.2. Energy exchanges within communities 235

6.4.3. Distributed optimization of energy exchanges with game theory 239

6.4.4. Simulation results 251

6.5. Managing energy exchanges using blockchain technology 258

6.5.1. Introduction 258

6.5.2. The principle of blockchain 259

6.5.3. Development of a local blockchain for managing energy exchanges in the renewable energy community 261

6.5.4. Simulations and results 269

6.6. Interpretations and experience feedback 275

6.7. Conclusion 275

6.8. Acknowledgments 276

6.9. References 277

Chapter 7. Sustainable and Desirable Living Thanks to Smart Buildings 281

7.1. Introduction 281

7.2. Smart building 284

7.2.1. Definition of a smart building 284

7.2.2. Services provided by a smart building 285

7.3. Data processing and building management 295

7.3.1. Introduction 295

7.3.2. Dynamic energy optimization for buildings 296

7.3.3. Indoor and outdoor air quality in a building 306

7.3.4. Blockchain and buildings 309

7.4. Environmental and climate impact of the building 310

7.4.1. Introduction 310

7.4.2. Renovating instead of building new 311

7.4.3. Socio-technical management of a building 313

7.4.4. Sufficiency in residential buildings 315

7.5. Acknowledgments 317

7.6. References 318

Chapter 8. Demonstration Sites 321

8.1. Introduction: full-scale implementation 321

8.2. Technology Readiness Level 322

8.3. Development of a smart grid demonstration site 323

8.3.1. Demonstration projects 325

8.4. An all-in-one demonstration site 327

8.4.1. Introduction 327

8.4.2. Controlling photovoltaic production 327

8.4.3. Integration and control of electric vehicle charging 330

8.4.4. Controlling electrical loads in buildings 335

8.4.5. Electrical energy storage control 343

8.4.6. Communication networks 346

8.4.7. IT developments 347

8.4.8. Perspectives 348

8.5. The contribution of occupants of a service sector site to electricity savings 349

8.5.1. Evolution of the sources of energy consumption reduction 350

8.5.2. Shaving potential at tertiary sites 352

8.5.3. Exploring potential for load shedding in commercial sites 357

8.5.4. Concluding remarks on both case studies 365

8.6. Conclusion 365

8.7. Acknowledgments 366

8.8. References 366

Postface 369

Index 375