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Optimal Operation of Active Distribution Networks
Congestion Management, Voltage Control and Service Restoration
- 1st Edition - August 29, 2023
- Authors: Feifan Shen, Zhaoxi Liu, Wenshu Jiao, Menglin Zhang, Qiuwei Wu
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 9 0 1 5 - 5
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 9 0 1 6 - 2
Optimal Operation of Active Distribution Networks: Congestion Management, Voltage Control and Service Restoration provides researchers and practitioners with a clear and modern un… Read more
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Request a sales quoteOptimal Operation of Active Distribution Networks: Congestion Management, Voltage Control and Service Restoration provides researchers and practitioners with a clear and modern understanding of how to optimize the economic, secure and resilient operation of active distribution networks. The book provides case studies, modern implementations and supporting flowcharts and code, along with current research in congestion management, service restoration and voltage control of active distribution networks. Chapter provide an overview of the active distribution network concept, present key approaches for the congestion management of active distribution networks, and cover approaches in uncertainty, coordination of DLMP, scheduled re-profiling, and more.
Other sections cover real-time congestion management and service restoration of active distribution networks.
- Reviews how to optimally operate active distribution networks under normal conditions and demonstrates worked solutions and contingency planning to mitigate unforeseen challenges
- Provides clear guidance on optimizing congestion management, voltage control and service restoration in DER-heavy systems
- Demonstrates how to implement distributed voltage control in systems using active distribution networks
- Provides an extensive body of methods, associated case studies, worked solutions and implementation discussions on how to embed best practices in engineering and research workflows
Early career researchers at PhD level, postdoctoral researchers, and Professors investigating the optimal operation of power systems, including congestion management, service restoration, and voltage control.
- Cover image
- Title page
- Table of Contents
- Copyright
- 1. Introduction of active distribution networks
- Abstract
- 1.1 Introduction
- 1.2 The concept of active distribution network
- 1.3 Key technologies of active distribution network
- 1.4 Conclusions
- References
- 2. Distribution locational marginal pricing for congestion management in distribution networks
- Abstract
- 2.1 Introduction
- 2.2 Optimal energy planning
- 2.3 Multiple solution issue of the aggregator optimization with linear programming formulation
- 2.4 Proof of the convergence of the DSO optimization and the aggregator optimization
- 2.5 Case studies
- 2.6 Conclusions
- References
- 3. Distribution locational marginal pricing for optimal electric vehicle charging through chance-constrained mixed-integer programming
- Abstract
- 3.1 Introduction
- 3.2 Chance-constrained charging scheduling of EV aggregators
- 3.3 DLMP design and calculation with chance-constrained EV charging model
- 3.4 Case studies of DLMP scheme with chance-constrained EV charging model
- 3.5 Summary
- References
- 4. Robust dynamic tariff method for day-ahead congestion management of active distribution networks
- Abstract
- 4.1 Introduction
- 4.2 Model formulation and uncertainty in the DT method
- 4.3 Robust DT model formulation and iterative solution method
- 4.4 Case studies
- 4.5 Conclusions
- References
- 5. Comprehensive day-ahead congestion management based on the dynamic tariff, network reconfiguration, and reprofiling product
- Abstract
- 5.1 Introduction
- 5.2 Comprehensive congestion management scheme
- 5.3 Model formulations of the comprehensive scheme
- 5.4 Case studies
- 5.5 Conclusion
- References
- 6. ADMM-based market clearing and optimal flexibility bidding of distribution-level flexibility market for day-ahead congestion management of distribution networks
- Abstract
- 6.1 Introduction
- 6.2 Distribution-level flexibility market
- 6.3 Model formulations
- 6.4 The ADMM-based market clearing strategy
- 6.5 Case studies
- 6.6 Conclusion
- References
- 7. Two-tier real-time congestion management based on flexible demand swap and transactive control
- Abstract
- 7.1 Introduction
- 7.2 Concepts of the flexible demand swap and transactive control
- 7.3 Framework of the real-time congestion management
- 7.4 Model formulations and algorithm
- 7.5 Case studies
- 7.6 Conclusion
- References
- 8. Distributed coordinated voltage control for distribution networks with DG and OLTC based on MPC and gradient projection
- Abstract
- 8.1 Introduction
- 8.2 Overview of distributed coordinated voltage control scheme
- 8.3 GP-based decentralized voltage control
- 8.4 OLTC control scheme based on MPC
- 8.5 Case study
- 8.6 Conclusion
- References
- 9. Double-timescale distributed voltage control for unbalanced distribution networks based on MPC and ADMM
- Abstract
- 9.1 Introduction
- 9.2 Brief overview
- 9.3 Problem formulation
- 9.4 B&B algorithm embedded with McCormick envelopes for MINLP problem in STC
- 9.5 ADMM-based algorithm for the distributed voltage control problem
- 9.6 Tests and results
- 9.7 Conclusion
- References
- 10. Distributed coordinated operations of transmission and distribution systems
- Abstract
- 10.1 Introduction and literature review
- 10.2 Optimal reserve activation strategy with transmission-distribution coordination
- 10.3 ADMM-based distributed algorithm for coordinated transmission-distribution operations
- 10.4 Case studies and discussions
- 10.5 Summary
- References
- 11. Distributed service restoration for active distribution networks based on alternating direction method of multipliers
- Abstract
- 11.1 Introduction
- 11.2 Optimal service restoration model for unbalanced ADNs
- 11.3 ADMM-based algorithm for the service restoration problem
- 11.4 Case studies and results
- 11.5 Conclusion
- References
- 12. Distributed risk-limiting service restoration for active distribution networks with networked microgrids
- Abstract
- 12.1 Introduction
- 12.2 Optimal risk-limiting service restoration problem
- 12.3 MILP model formulation and decomposition
- 12.4 ADMM-based solution method
- 12.5 Case studies and results
- 12.6 Conclusion
- References
- 13. Hierarchical service restoration for active distribution networks based on alternating direction method of multipliers
- Abstract
- 13.1 Introduction
- 13.2 Framework of the proposed hierarchical service restoration scheme
- 13.3 Model formulations for the optimal service restoration problem
- 13.4 ADMM-based algorithm for the service restoration model
- 13.5 Case studies
- 13.6 Conclusion
- References
- 14. DMPC-based distributed voltage control for unbalanced distribution networks with single-/three-phase DGs
- Abstract
- 14.1 Introduction
- 14.2 Overview of DMPC-based distributed voltage control scheme
- 14.3 Voltage synchronization and sensitivity calculation
- 14.4 Case study
- 14.5 Conclusion
- References
- 15. Hierarchical distributed voltage control for active distribution networks with DGCs based on GP and ADMM
- Abstract
- 15.1 Introduction
- 15.2 Overview of hierarchical distributed voltage control scheme
- 15.3 DGC control based on GP
- 15.4 DG control based on ADMM
- 15.5 Case study
- 15.6 Conclusion
- References
- 16. Transactive control for real-time electric vehicle charging management under uncertainty
- Abstract
- 16.1 Introduction
- 16.2 Energy management framework for EVs and PVs
- 16.3 Real-time EV charging operation of BEMS
- 16.4 Case studies of transactive energy-based real-time EV charging management
- 16.5 Summary
- References
- 17. A two-stage scheduling method for aggregators based on transactive control
- Abstract
- 17.1 Introduction
- 17.2 Two-stage demand management framework for aggregators
- 17.3 Optimal two-stage scheduling model of aggregators based on transactive energy
- 17.4 Case studies of two-stage scheduling for demand management of aggregators
- 17.5 Summary
- References
- Appendix A. Introduction to alternating direction method of multipliers
- A.1 Fundamental of alternating direction method of multipliers algorithm
- A.2 Voltage control scheme based on alternating direction method of multipliers
- Appendix B. Introduction to analytical target cascading
- B.1 Problem decomposition
- B.2 Solution methodology
- Index
- No. of pages: 435
- Language: English
- Edition: 1
- Published: August 29, 2023
- Imprint: Academic Press
- Paperback ISBN: 9780443190155
- eBook ISBN: 9780443190162
FS
Feifan Shen
Feifan Shen received the B.Eng. degree in Electrical Engineering and Automation from Hohai University, Nanjing, China, in 2015, and the M.Eng. degree from the Department of Electrical Engineering, Wuhan University, Wuhan, China, in 2017, and the joint Ph.D. degree from the Department of Electrical Engineering, Centre of Electric Power and Energy, Technical University of Denmark, Lyngby, Denmark, and the Interdisciplinary graduate school, Nanyang Technological University, Singapore, in 2021. He is currently an assistant professor in the school of electrical and information engineering, Hunan University. His research interests include congestion management and self-healing of distribution networks, wind farm operation and control, and the application of AI in smart grid operation.
Affiliations and expertise
Hunan University, Yuelu District, Changsha, Hunan, ChinaZL
Zhaoxi Liu
Zhaoxi Liu received his Ph.D. degree from the Technical University of Denmark in 2016. He is currently a Professor at the South China University of Technology, Guangzhou, China. He was a Research Associate at the University of Wisconsin-Milwaukee, a Postdoctoral fellow in the Technical University of Denmark and a visiting scholar at the University of California, Berkeley. He has practical industrial experience in more than ten large power industry projects as an Electrical Engineer. His research interests mainly include operations research of energy systems, power system security and resilience, and integration of distributed energy resources and renewable energy sources in power systems. He serves as an active reviewer for several journals on power and energy systems. He is also a guest editor of the journal Frontiers in Energy Research.
Affiliations and expertise
Dr. Zhaoxi Liu is a Professor at the South China University of Technology (SCUT), China.WJ
Wenshu Jiao
Wenshu Jiao received the B.S. and a M.S. degree in Electrical Engineering in 2018 and 2021 respectively from Shandong University, Jinan, China, where he is currently working toward his Ph.D. degree in Electrical Engineering. His research interests include renewable energy generation, active distribution networks, voltage control and distributed optimization algorithms with applications to power system.
Affiliations and expertise
Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education, Shandong University, Jinan, ChinaMZ
Menglin Zhang
Menglin Zhang is a professor with the School of Automation, China University of Geosciences, Wuhan. She received the B.S. degree in Electrical Engineering and Automation from Southwest Jiaotong University, Chengdu, China, in 2011, and the Ph.D. from the Department of Electrical Engineering, Wuhan University, Wuhan, China, in 2017. She was a Postdoctoral Researcher with the Department of Electrical and Electronic Engineering, Huazhong University of Science and Technology (HUST), Wuhan, China from 2017 to 2019. She was a Postdoctoral Researcher with the Center for Electric Power and Energy, Technical University of Denmark (DTU) from 2019 to 2021. Her research includes the optimal operation of renewable-based multi-energy systems under uncertainty, including the modeling of multi-energy systems considering flexibility, robust and stochastic optimization, and the solution for bulk energy systems. She is a young editor for Applied Energy and IET Renewable Power Generation.
Affiliations and expertise
Professor, Automation School, China University of Geosciences, Wuhan, ChinaQW
Qiuwei Wu
Qiuwei Wu is currently a Chair Professor at the School of Electrical and Information Engineering at Tianjin University, China. Prior to this he was a tenured Associate Professor at the Tsinghua-Berkeley Shenzhen Institute of Tsinghua University, China. His research interests are in decentralized/distributed optimal operation and control of power systems with high penetration of renewables, including distributed wind power modelling and control, decentralized/distributed congestion management, voltage control and load restoration of active distribution networks, and decentralized/distributed optimal operation of integrated energy systems. Dr. Wu is an Associate Editor of IEEE Transactions on Power Systems and IEEE Power Engineering Letters, Deputy Editor-in-Chief and Associate Editor of the International Journal of Electrical Power and Energy Systems and the Journal of Modern Power Systems and Clean Energy, and a subject editor for IET Generation, Transmission & Distribution and IET Renewable Power Generation.
Affiliations and expertise
Chair Professor, School of Electrical and Information Engineering, Tianjin University, China