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Scheduling and Operation of Virtual Power Plants
Technical Challenges and Electricity Markets
- 1st Edition - January 25, 2022
- Editors: Ali Zangeneh, Moein Moeini-Aghtaie
- Language: English
- Paperback ISBN:9 7 8 - 0 - 3 2 3 - 8 5 2 6 7 - 8
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 8 5 2 6 8 - 5
Scheduling and Operation of Virtual Power Plants: Technical Challenges and Electricity Markets provides a multidisciplinary perspective on recent advances in VPPs, ranging f… Read more
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Request a sales quoteScheduling and Operation of Virtual Power Plants: Technical Challenges and Electricity Markets provides a multidisciplinary perspective on recent advances in VPPs, ranging from required infrastructures and planning to operation and control. The work details the required components in a virtual power plant, including smartness of power system, instrument and information and communication technologies (ICTs), measurement units, and distributed energy sources. Contributors assess the proposed benefits of virtual power plant in solving problems of distributed energy sources in integrating the small, distributed and intermittent output of these units. In addition, they investigate the likely technical challenges regarding control and interaction with other entities.
Finally, the work considers the role of VPPs in electricity markets, showing how distributed energy resources and demand response providers can integrate their resources through virtual power plant concepts to effectively participate in electricity markets to solve the issues of small capacity and intermittency. The work is suitable for experienced engineers, researchers, managers and policymakers interested in using VPPs in future smart grids.
- Explores key enabling technologies and infrastructures for virtual power plants in future smart energy systems
- Reviews technical challenges and introduces solutions to the operation and control of VPPs, particularly focusing on control and interaction with other power system entities
- Introduces the key integrating role of VPPs in enabling DER powered participative electricity markets
Graduate students (MS and Ph.D. students). Early career researchers. Power system engineers. Distribution system operators, market operators, renewable energy owners, private entities
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- List of contributors
- Preface
- Abbreviations and acronyms
- 1: Introduction and history of virtual power plants with experimental examples
- Abstract
- 1.1. Introduction
- 1.2. Distributed generation
- 1.3. Virtual power plant (VPP)
- 1.4. Research on VPP
- 1.5. Summary
- References
- 2: VPP and hierarchical control methods
- Abstract
- 2.1. Introduction
- 2.2. Hierarchical control methods
- 2.3. Conclusion
- References
- 3: Bidding strategy in the electricity market
- Abstract
- Nomenclature
- 3.1. Introduction
- 3.2. Virtual power plant
- 3.3. Optimal bidding of VPP in electricity market
- 3.4. Hypotheses and problem objectives
- 3.5. Case study
- 3.6. Conclusion
- Appendix 3.A.
- References
- 4: Optimization model of a VPP to provide energy and reserve
- Abstract
- Nomenclature
- 4.1. Introduction
- 4.2. Optimization model of VPP to provide energy
- 4.3. Optimization model of VPP to provide reserve
- 4.4. Examples for VPP optimization model providing energy and reserve
- 4.5. Conclusion
- References
- 5: Provision of ancillary services in the electricity markets
- Abstract
- Nomenclature
- 5.1. Introduction
- 5.2. Problem modelling and formulation
- 5.3. Solution algorithm
- 5.4. Numerical results
- 5.5. Conclusions
- References
- 6: Frequency control and regulating reserves by VPPs
- Abstract
- 6.1. Introduction
- 6.2. Taxonomy
- 6.3. Examples
- 6.4. Conclusions
- References
- 7: VPP's participation in demand response aggregation market
- Abstract
- Nomenclature
- 7.1. Introduction
- 7.2. Single-level model of DSO without DR programs
- 7.3. Single-level scheduling model of DSO with DR programs
- 7.4. Bi-level scheduling model between DSO and VPP-DRA
- 7.5. Numerical studies and discussions
- 7.6. Conclusion
- References
- 8: VPP's participation in demand response exchange market
- Abstract
- Nomenclature
- 8.1. Introduction
- 8.2. VPP scheduling framework
- 8.3. VPP scheduling model
- 8.4. Uncertainties arising from VPP scheduling
- 8.5. Numerical studies and discussions
- 8.6. Conclusion
- References
- 9: Uncertainty modeling of renewable energy sources
- Abstract
- 9.1. Introduction
- 9.2. Modeling of RESs
- 9.3. Modeling of VPP
- 9.4. Classification and description of uncertainties in VPP
- 9.5. Optimization approaches of VPP with uncertainties
- 9.6. Problem formulation
- 9.7. Tools used to solve optimization problems of VPP with uncertainties
- 9.8. Case study
- 9.9. Conclusion
- References
- 10: Frameworks of considering RESs and loads uncertainties in VPP decision-making
- Abstract
- 10.1. Introduction
- 10.2. Proposals for handling uncertainty within a VPP
- 10.3. Taxonomy
- 10.4. Conclusions and path forward
- References
- 11: Risk-averse scheduling of virtual power plants considering electric vehicles and demand response
- Abstract
- Nomenclature
- 11.1. Introduction
- 11.2. Problem formulation
- 11.3. Case study
- 11.4. Conclusions
- References
- 12: Optimal operation strategy of virtual power plant considering EVs and ESSs
- Abstract
- Nomenclature
- 12.1. Introduction
- 12.2. Modeling of EVs
- 12.3. Modeling of ESSs
- 12.4. VPP operation strategy modeling in the presence of EVs and ESSs
- 12.5. Examples for VPP optimal operation strategy considering EVs and ESSs
- 12.6. Conclusion
- References
- 13: EVs vehicle-to-grid implementation through virtual power plants
- Abstract
- Nomenclature
- 13.1. Introduction
- 13.2. Vehicle-to-grid (V2G)
- 13.3. Bidirectional converters for V2G systems
- 13.4. Bidirectional AC–DC converter (BADC)
- 13.5. Bidirectional DC–DC converter (BDC)
- 13.6. Modeling the problem
- 13.7. Case study
- 13.8. Conclusion
- References
- 14: Short- and long-term forecasting
- Abstract
- 14.1. Introduction
- 14.2. Wind speed forecasting from long-term observations
- 14.3. Conclusion
- References
- 15: Forecasting of energy demand in virtual power plants
- Abstract
- Introduction
- Load behavior
- Different weather parameters
- Different methods for clustering analysis
- Different methods for STLF
- Fitness criteria
- Case study
- Conclusion
- References
- 16: Emission impacts on virtual power plant scheduling programs
- Abstract
- Nomenclature
- 16.1. Introduction
- 16.2. Problem formulation
- 16.3. Simulation and numerical results
- 16.4. Conclusions
- References
- 17: Multi-objective scheduling of a virtual power plant considering emissions
- Abstract
- Nomenclature
- 17.1. Introduction
- 17.2. Problem formulation
- 17.3. Case studies
- 17.4. Conclusion
- References
- Author index
- Subject index
- No. of pages: 450
- Language: English
- Edition: 1
- Published: January 25, 2022
- Imprint: Elsevier
- Paperback ISBN: 9780323852678
- eBook ISBN: 9780323852685
AZ
Ali Zangeneh
Ali Zanganeh is Associate Professor of Electrical Engineering at Shahid Rajaee Teacher Training University, Lavizan, Tehran. He received his Ph.D. degree in electrical engineering from Iran University of Science and Technology (IUST) in 2010. His research interests include demand side management, smart grid, resiliency, distributed generation and optimization in power systems.
Affiliations and expertise
Associate Professor of Electrical Engineering, Shahid Rajaee Teacher Training University, Lavizan, Tehran, IranMM
Moein Moeini-Aghtaie
Moein Moeini-Aghtaie is Assistant Professor of Electical Engineering at Sharif University of Technology, Tehran, Iran. He received the M.Sc. and Ph.D. degrees from the Sharif University of Technology, Tehran, Iran, in 2010 and 2014, respectively, both in electrical engineering. His current research interests include reliability and resilience studies of modern distribution systems, especially in the multi-carrier energy environment, and charging management of plug-in hybrid electric vehicles.
Affiliations and expertise
Assistant Professor of Electrical Engineering, Sharif University of Technology, Tehran, IranRead Scheduling and Operation of Virtual Power Plants on ScienceDirect