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. 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. 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. 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. Qiuwei Wu received the PhD degree in Electrical Engineering from Nanyang Technological University, Singapore, in 2009. He is a professor with the School of Electronics, Electrical Engineering, and Computer Science (EEECS), Queen’s University Belfast, the UK. His research interests are distributed optimal operation and control of low carbon power and energy systems, including distributed optimal control of wind power, optimal operation of active distribution networks, and optimal operation and planning of integrated energy systems.

• 1. Introduction to Active Distribution Networks2. Distribution locational marginal pricing for congestion management in distribution networks3. Distribution Locational Marginal Pricing for Optimal Electric Vehicle Charging through Chance Constrained Mixed-Integer Programming4. Robust Dynamic Tariff Method for Day-Ahead Congestion Management of Distribution Networks5. Comprehensive Congestion Management for Distribution Networks based on Dynamic Tariff, Reconfiguration and Re-profiling Product6. ADMM-based Market Clearing and Optimal Flexibility Bidding of Distribution-level Flexibility Market for Day-Ahead Congestion Management of Distribution Networks7. Two-Tier Demand Response with Flexible Demand Swap and Transactive Control for Real-Time Congestion Management in Distribution Networks8. Distributed Coordinated Voltage Control for Distribution Networks with DG and OLTC based on MPC and Gradient Projection9. Double-Time-Scale Distributed Voltage Control for Unbalanced Distribution Networks Based on MPC and ADMM10. Distributed Self-healing Scheme for Unbalanced Electrical Distribution Systems Based on Alternating Direction Method of Multipliers11. Distributed Risk-Limiting Load Restoration in Unbalanced Distribution Systems with Networked Microgrids12. Hierarchical Service Restoration Scheme for Active Distribution Networks based on ADMM