Distributed Energy Resources in Local Integrated Energy Systems: Optimal Operation and Planning reviews research and policy developments surrounding the optimal operation and planning of DER in the context of local integrated energy systems in the presence of multiple energy carriers, vectors and multi-objective requirements. This assessment is carried out by analyzing impacts and benefits at local levels, and in distribution networks and larger systems. These frameworks represent valid tools to provide support in the decision-making process for DER operation and planning. Uncertainties of RES generation and loads in optimal DER scheduling are addressed, along with energy trading and blockchain technologies.
Interactions among various energy carriers in local energy systems are investigated in scalable and flexible optimization models for adaptation to a number of real contexts thanks to the wide variety of generation, conversion and storage technologies considered, the exploitation of demand side flexibility, emerging technologies, and through the general mathematical formulations established.
1. 5.1: Introduction - p. 128 2. 5.2: A distributed approach for the day-ahead scheduling of the LEC - p. 129 3. 5.3: Implementation and numerical tests - p. 138 4. 5.4: Distribution network planning model considering nonnetwork solutions and neighborhood energy trading - p. 148 5. 5.5: Application of the planning model to case studies and analysis of the results - p. 160 6. 5.6: Conclusions - p. 170 7. Acknowledgment - p. 171 8. References - p. 171 9. Chapter 6 Fostering DER integration in the electricity markets - p. 175 10. Chapter 7 Challenges and directions for Blockchain technology applied to Demand Response and Vehicle-to-Grid scenarios - p. 207 11. Chapter 8 Optimal management of energy storage systems integrated in nanogrids for virtual “nonsumer” community - p. 231 12. Chapter 9 Demand response role for enhancing the flexibility of local energy systems - p. 279 13. Abbreviations - p. 279 14. Nomenclature - p. 279 15. 9.1: Introduction - p. 282 16. 9.2: Demand response programs for local energy systems - p. 286 17. 9.3: Flexibility assessment of local energy systems in the presence of energy storage systems and DR programs - p. 292 18. 9.4: Energy management framework for DER integrated distribution networks - p. 292 19. 9.5: Simulation results - p. 304 20. 9.6: Conclusion remarks - p. 310 21. Acknowledgment - p. 311 22. References - p. 311 23. Chapter 10 The integration of electric vehicles in smart distribution grids with other distributed resources - p. 315 24. Chapter 11 Assessing renewables uncertainties in the short-term (day-ahead) scheduling of DER - p. 347 25. Chapter 12 Load forecasting in the short-term scheduling of DERs - p. 389 26. Chapter 13 Conclusions and key findings of optimal operation and planning of distributed energy resources in the context of local integrated energy systems - p. 419 27. Index - p. 427
Distributed Energy Resources in Local Integrated Energy Systems: Optimal Operation and Planning reviews research and policy developments surrounding the optimal operation and planning of DER in the context of local integrated energy systems in the presence of multiple energy carriers, vectors and multi-objective requirements. This assessment is carried out by analyzing impacts and benefits at local levels, and in distribution networks and larger systems. These frameworks represent valid tools to provide support in the decision-making process for DER operation and planning. Uncertainties of RES generation and loads in optimal DER scheduling are addressed, along with energy trading and blockchain technologies.
Interactions among various energy carriers in local energy systems are investigated in scalable and flexible optimization models for adaptation to a number of real contexts thanks to the wide variety of generation, conversion and storage technologies considered, the exploitation of demand side flexibility, emerging technologies, and through the general mathematical formulations established.
1. 5.1: Introduction - p. 128 2. 5.2: A distributed approach for the day-ahead scheduling of the LEC - p. 129 3. 5.3: Implementation and numerical tests - p. 138 4. 5.4: Distribution network planning model considering nonnetwork solutions and neighborhood energy trading - p. 148 5. 5.5: Application of the planning model to case studies and analysis of the results - p. 160 6. 5.6: Conclusions - p. 170 7. Acknowledgment - p. 171 8. References - p. 171 9. Chapter 6 Fostering DER integration in the electricity markets - p. 175 10. Chapter 7 Challenges and directions for Blockchain technology applied to Demand Response and Vehicle-to-Grid scenarios - p. 207 11. Chapter 8 Optimal management of energy storage systems integrated in nanogrids for virtual “nonsumer” community - p. 231 12. Chapter 9 Demand response role for enhancing the flexibility of local energy systems - p. 279 13. Abbreviations - p. 279 14. Nomenclature - p. 279 15. 9.1: Introduction - p. 282 16. 9.2: Demand response programs for local energy systems - p. 286 17. 9.3: Flexibility assessment of local energy systems in the presence of energy storage systems and DR programs - p. 292 18. 9.4: Energy management framework for DER integrated distribution networks - p. 292 19. 9.5: Simulation results - p. 304 20. 9.6: Conclusion remarks - p. 310 21. Acknowledgment - p. 311 22. References - p. 311 23. Chapter 10 The integration of electric vehicles in smart distribution grids with other distributed resources - p. 315 24. Chapter 11 Assessing renewables uncertainties in the short-term (day-ahead) scheduling of DER - p. 347 25. Chapter 12 Load forecasting in the short-term scheduling of DERs - p. 389 26. Chapter 13 Conclusions and key findings of optimal operation and planning of distributed energy resources in the context of local integrated energy systems - p. 419 27. Index - p. 427
