Special Issues

Digital and Intelligent Planning and Operation Technologies for Flexible Distribution Network

Submission Deadline: 28 February 2026 View: 372 Submit to Special Issue

Guest Editors

Prof. Haoran Ji

Email: jihaoran@tju.edu.cn

Affiliation: School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China

Homepage:

Research Interests: energy management of distribution networks, intelligent control with renewable energy integration

图片5.png


Dr. Jinli Zhao

Email: jlzhao@tju.edu.cn

Affiliation: School of Electrical and Information Engineering, Tianjin University, Tianjin, 300072, China

Homepage:

Research Interests: integrated energy system operation and analysis, active distribution network operation analysis and optimization control

图片6.png


Prof. Hany M. Hasanien

Email: hanymhasanien@gmail.com

Affiliation: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo, 11566, Egypt

Homepage:

Research Interests: renewable energy systems, power systems dynamics and control, smart grid

图片7.png


Summary

With the large-scale access of renewable energy and flexible loads, the limited hosting capacity of the distribution system is becoming the key issue that restricting the construction and development of power systems. The flexible distribution network (FDN) is regarded as the core that supports the flexible combination of the source, network, load and storage. The innovation of the planning and operating technology of FDN is crucial to improve the hosting capacity and operating level of the system. The construction of FDN has the potential to apply big data, digital twin, artificial intelligence, edge computing, and other new-type technologies to achieve high-quality planning and operation of distribution networks. This topic will focus on advanced digital and intelligent technologies for planning and operation of FDN, in order to enhance the flexibility, controllability and hosing capacity of distribution networks.


This special issue (SI) will mainly focus on digital and intelligence technologies for FDNs. The aim is to gather and present the latest digital technology and intelligent algorithm for the planning and operation of distribution networks. This special issue will provide a platform for researchers and practical engineers to share their latest discoveries and best practices in these fields.


Topics of interest include, but are not limited to:
- The evolution path and driving elements of flexible distribution networks
- Digital and intelligent planning methods considering the coordination of source, grid, load, storage and flexible interconnection in FDNs
- Planning and operation technologies for multi-voltage level distribution networks
- Data-driven state perception and prediction technologies for distribution systems
- Distribution system operation control technologies based on artificial intelligence
- Modeling and intelligent control strategies of flexible interconnection devices
- Engineering practices and typical demonstration application cases of flexible distribution systems


Keywords

flexible distribution networks, digital technologies, edge intelligence, data-driven control, flexible interconnection devices

Published Papers


  • Open Access

    ARTICLE

    A Multi-Stage Expansion Planning Method for Rural Distribution Networks with Flexible Interconnection

    Yueyang Ji, Yaohui Peng, Haoran Ji, Xinran Na, Yuxuan Chen, Wei Li, Shengbin Chen
    Energy Engineering, DOI:10.32604/ee.2025.074599
    (This article belongs to the Special Issue: Digital and Intelligent Planning and Operation Technologies for Flexible Distribution Network)
    Abstract With the increasing penetration of distributed generations and continuous growth of loads, traditional rural distribution networks face severe challenges in both hosting capacity and reliability. Addressing these issues requires planning approaches that strike a balance between economic efficiency in infrastructure development and resilience in operation. Considering the dynamic growth of distributed generations and rural loads over the planning horizon, this paper presents a multi-stage expansion planning approach that coordinates flexible interconnection devices (FIDs) with substation and line construction to improve both economic performance and system reliability. The proposed method account for the time-varying growth of… More >

  • Open Access

    ARTICLE

    Curriculum-Learning-Guided Multi-Agent Deep Reinforcement Learning for N-1 Static Security Prevention and Control

    Ximing Zhang, Zhuohuan Li, Xuexia Quan, Kai Cheng, Yang Yu
    Energy Engineering, DOI:10.32604/ee.2025.073912
    (This article belongs to the Special Issue: Digital and Intelligent Planning and Operation Technologies for Flexible Distribution Network)
    Abstract The “N-1” criterion represents a fundamental principle for assessing the reliability of power systems in static security analysis. Existing studies mainly rely on centralized single-agent reinforcement learning frameworks, where centralized control is difficult to cope with regional autonomy and communication delays. In high-dimensional state–action spaces, these approaches often suffer from low efficiency and unstable policies, limiting their applicability to large-scale grids. To address these issues, this paper proposes a Multi-Agent Deep Reinforcement Learning (MADRL) method enhanced with Curriculum Learning (CL) and Prioritized Experience Replay (PER). The proposed framework adopts a Centralized Training with Decentralized Execution… More >

Share Link