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 xiForeword by Audrey Linkenheld xviiIntroduction xxvChapter 1. From Transition Challenges to Smart Grids and Smart Buildings 11.1. Introduction 11.2. Climatic challenges 31.3. Four inspiring social and climate scenarios 51.4. Sufficiency or prosperity 131.4.1. Personal, shared and organizational sufficiency 131.4.2. From smart sharing to wise sharing 141.4.3. From sufficiency to prosperity 161.4.4. Spirituality and ecological transition 191.5. Ethical and political issues 221.5.1. Ethical issues in the ecological transition 221.5.2. Questions of governance or the need to reinvent democracies 231.5.3. Eco-anxiety 291.6. Bifurcating research 311.7. Smarter energy networks 331.7.1. From 100% renewable energy to a combination of solutions 331.7.2. Towards the decentralization of electricity grids 361.7.3. Smart grids, self-generation and self-consumption 381.7.4. An increasingly miraculous electricity fairy – yes but? 391.8. Smarter buildings in a desirable habitat 451.8.1. Buildings and living spaces 451.8.2. Building trends in 2050 461.8.3. Smart buildings 471.9. Smart buildings as nodes of smart grids 501.10. Methodological contributions 521.11. The question of artificial intelligence 531.12. References 54Chapter 2. Smart City, Smart Building, Smart User: The Imaginaries of Smart and its Dead Ends 592.1. Introduction 592.2. Reducing energy consumption: changing technologies or changing practices? 602.2.1. Limits to energy efficiency 602.2.2. Limits of an approach focused (solely) on practices 612.2.3. Usage dependence on the technology used 642.3. The smart imaginary and its dead ends 672.3.1. Technical distancing as a common denominator 682.3.2. The smart city or the imaginary of a city without inhabitants 682.3.3. The smart building or the imaginary of a building parasitized by its users 702.4. Conclusion: in search of the smart user? 712.5. References 73Chapter 3. Forecasting the Production and Consumption of Electrical Energy 773.1. Introduction 773.2. Variability in production and consumption 783.3. Photovoltaic production forecast 803.3.1. Satellite image-based forecasting 823.3.2. Short-term forecast by camera 833.3.3. Neural network prediction 853.3.4. Case study: 24-hour production forecast for the photovoltaic power plant at the Université Catholique de Lille 893.4. Forecasting electricity consumption 963.4.1. Important factors for forecasting electricity consumption 963.4.2. Electricity consumption prediction methods 973.4.3. Case study: 24-hour forecast of electricity consumption for a block of buildings at the Université Catholique de Lille 983.5. Valorization of forecasts and feedback 1043.5.1. Using forecasts to manage energy for the Université Catholique de Lille smart grid demonstrator 1043.5.2. Load forecasting in a distribution network at a high-voltage/medium-voltage (HV/MV) source substation 1073.5.3. The importance of meteorological forecasting 1113.5.4. The importance of uncertainty analysis 1123.5.5. Importance of database size and quality 1133.6. Conclusion 1133.7. Acknowledgments 1143.8. References 114Chapter 4. Taking Actors into Account in Energy Management Strategies 1174.1. Introduction 1174.2. A system of actors in an electrical network 1204.2.1. The role of actors 1204.2.2. System operator 1214.2.3. Aggregator 1214.2.4. Producer 1224.2.5. Consumer 1234.2.6. Consumer–producer (prosumer) 1244.3. Methodology for managing energy flexibility involving actors 1244.3.1. Defining key concepts 1244.3.2. Comprehensive methodology for energy supervision 1264.4. Modeling actor profiles 1274.4.1. An interdisciplinary approach 1274.4.2. Existing actor profiles 1294.4.3. Observable profiles 1324.4.4. Integrable profiles 1324.5. Residential actor profiles 1344.5.1. Return feedback from experimentation/scale-one projects 1344.5.2. Consumer profile research 1354.5.3. Sociological approaches for accepting participation in network management 1364.5.4. Economic approaches for consumer involvement 1384.5.5. The need for interdisciplinarity 1394.5.6. Characterizing flexibility 1404.5.7. Parameters influencing flexibility 1444.6. Identification of residential actor profiles 1474.6.1. Introduction 1474.6.2. A microeconomic approach to price sensitivity 1474.6.3. A sociological approach to environmental awareness 1574.7. Profiles of selected residential actors 1584.7.1. Economical 1584.7.2. Eco-sensitive 1594.7.3. Technophiles 1594.7.4. Indifferent – moderate opportunists 1594.7.5. Disengaged 1594.7.6. Discussions 1594.8. Conclusion 1614.9. Acknowledgments 1624.10. References 162Chapter 5. Energy Supervision of a Local Residential Network with Actor Involvement 1695.1. Introduction 1695.2. Energy supervision methodology 1705.3. Modeling a residential case study 1715.3.1. Electricity network under consideration 1715.3.2. Modeling consumption 1725.3.3. Discussion of model limitations 1745.4. Day ahead supervision (before D-1) 1745.4.1. Discussion of predictive supervision 1745.4.2. Implementing the D-1 supervisor 1805.4.3. Scope statement 1815.4.4. Modeling actor profiles 1855.4.5. Supervisor structure 1905.4.6. Global optimization and game theory 1925.4.7. Local optimization using dynamic programming 1955.5. Real-time supervision 1985.5.1. Discussion of real-time supervision 1985.5.2. Implementation of supervision in real time 2025.5.3. Continuity with D-1 supervisor 2025.5.4. Fuzzy logic supervisor 2035.5.5. Indicators 2135.6. Two-week prospective simulations of the global supervisor 2135.6.1. Scenarios 2135.6.2. Results and discussion 2155.7. Conclusion 2215.8. Acknowledgments 2235.9. References 223Chapter 6. Self-Consumption within a Local Renewable Energy Community 2276.1. Introduction 2276.2. Local renewable energy communities 2306.3. Modeling a tertiary-sector case study 2316.3.1. Historic block at the Université Catholique de Lille 2316.3.2. Modeling the electrical network 2336.4. Distributed energy optimization 2346.4.1. Introduction 2346.4.2. Energy exchanges within communities 2356.4.3. Distributed optimization of energy exchanges with game theory 2396.4.4. Simulation results 2516.5. Managing energy exchanges using blockchain technology 2586.5.1. Introduction 2586.5.2. The principle of blockchain 2596.5.3. Development of a local blockchain for managing energy exchanges in the renewable energy community 2616.5.4. Simulations and results 2696.6. Interpretations and experience feedback 2756.7. Conclusion 2756.8. Acknowledgments 2766.9. References 277Chapter 7. Sustainable and Desirable Living Thanks to Smart Buildings 2817.1. Introduction 2817.2. Smart building 2847.2.1. Definition of a smart building 2847.2.2. Services provided by a smart building 2857.3. Data processing and building management 2957.3.1. Introduction 2957.3.2. Dynamic energy optimization for buildings 2967.3.3. Indoor and outdoor air quality in a building 3067.3.4. Blockchain and buildings 3097.4. Environmental and climate impact of the building 3107.4.1. Introduction 3107.4.2. Renovating instead of building new 3117.4.3. Socio-technical management of a building 3137.4.4. Sufficiency in residential buildings 3157.5. Acknowledgments 3177.6. References 318Chapter 8. Demonstration Sites 3218.1. Introduction: full-scale implementation 3218.2. Technology Readiness Level 3228.3. Development of a smart grid demonstration site 3238.3.1. Demonstration projects 3258.4. An all-in-one demonstration site 3278.4.1. Introduction 3278.4.2. Controlling photovoltaic production 3278.4.3. Integration and control of electric vehicle charging 3308.4.4. Controlling electrical loads in buildings 3358.4.5. Electrical energy storage control 3438.4.6. Communication networks 3468.4.7. IT developments 3478.4.8. Perspectives 3488.5. The contribution of occupants of a service sector site to electricity savings 3498.5.1. Evolution of the sources of energy consumption reduction 3508.5.2. Shaving potential at tertiary sites 3528.5.3. Exploring potential for load shedding in commercial sites 3578.5.4. Concluding remarks on both case studies 3658.6. Conclusion 3658.7. Acknowledgments 3668.8. References 366Postface 369Index 375