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Energies
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Operation and Planning of Distribution Systems Under High Renewable Penetration
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Operation and Planning of Distribution Systems Under High Renewable Penetration

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F2: Distributed Energy System".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1407

Special Issue Editors

Dr. Yunyang Zou

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Guest Editor
School of Electrical Engineering, Chongqing University, Chongqing 400044, China
Interests: electricity markets; renewable-energy distribution systems; multi-energy systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chao Deng

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Guest Editor
Institute of Advanced Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
Interests: distributed secondary control of microgrids and cyber-physical systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yang Li

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Guest Editor
School of Electrical Engineering, Northeast Electric Power University, Jilin City 132012, China
Interests: wind and solar dispatch; uncertainty modeling and analysis; energy storage/EV integration; optimization of integrated energy systems; integrated demand response; AI-driven power system analysis; federated learning
Special Issues, Collections and Topics in MDPI journals
Dr. Chengfu Wang

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Guest Editor
School of Electrical Engineering, Shandong University, Jinan 250100, China
Interests: distribution network; power system; renewable energy generation; integrated energy system
Special Issues, Collections and Topics in MDPI journals
Dr. Haijun Liao

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Guest Editor
School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
Interests: power IoT; cyber-physical systems; cloud-edge-end collaboration; sensing-transmission-computing-control integration
Dr. Bo Wang

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Guest Editor
School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China
Interests: power system modelling and optimization

Special Issue Information

Dear Colleagues,

Driven by global decarbonization goals, the integration of distributed energy sources (DERs) into power distribution systems has been accelerating worldwide. However, the high penetration of inherently stochastic and uncertain renewable generation poses significant challenges to distribution system operators, including difficulties in maintaining power balance, voltage and frequency regulation, and ensuring network resilience. To bridge these gaps, new operational paradigms and planning approaches tailored for renewable-rich distribution systems have emerged, such as networked microgrids, DER aggregators, transactive energy-based operation, Volt/Var control with DER inverter participation, and resilience-oriented planning frameworks.

This Special Issue seeks to advance research on enhancing the hosting capacity and accommodation of renewable energy sources in distribution systems, while ensuring their secure, efficient, and resilient operation under high renewable penetration. Topics of interest include, but are not limited to, the following:

  • Modeling of renewable generation and load demand uncertainties;
  • Operation and planning strategies under uncertainties;
  • Demand-side management and flexibility utilization;
  • Coordination of DERs, flexible loads, and energy storage for system balancing;
  • Distributed and hierarchical operation techniques for multi-agent distribution systems;
  • Transactive energy and market-based coordination mechanisms;
  • Volt/Var control and reactive power ancillary service trading with DER participation;
  • Virtual inertia provision and frequency regulation;
  • Hosting capacity assessment and enhancement methods;
  • Resilience assessment of distribution systems;
  • Resilience-oriented operation and planning strategies for distribution systems;
  • Distribution system expansion planning under high renewable penetration;
  • Post-event restoration strategies for distribution systems;
  • Network reconfiguration and topology optimization for enhancing flexibility and resilience;
  • Operation and planning of multi-energy systems and power-traffic systems.

Dr. Yunyang Zou
Prof. Dr. Chao Deng
Prof. Dr. Yang Li
Dr. Chengfu Wang
Dr. Haijun Liao
Dr. Bo Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • distribution systems
  • renewable energy integration
  • transactive energy
  • distributed operation
  • voltage and frequency regulation
  • system resilience
  • multi-energy coordination

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Published Papers (2 papers)

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Research

22 pages, 3874 KB  
Article
Cloud-Edge Collaboration-Based Data Processing Method for Distribution Terminal Unit Edge Clusters
by Ruijiang Zeng, Zhiyong Li, Sifeng Li, Jiahao Zhang and Xiaomei Chen
Energies 2026, 19(1), 269; https://doi.org/10.3390/en19010269 - 4 Jan 2026
Viewed by 504
Abstract
Distribution terminal units (DTUs) play critical roles in smart grid for supporting data acquisition, remote monitoring, and fault management. A single DTU generates continuous data streams, imposing new challenges on data processing. To tackle these issues, a cloud-edge collaboration-based data processing method is [...] Read more.
Distribution terminal units (DTUs) play critical roles in smart grid for supporting data acquisition, remote monitoring, and fault management. A single DTU generates continuous data streams, imposing new challenges on data processing. To tackle these issues, a cloud-edge collaboration-based data processing method is introduced for DTU edge clusters. First, considering the load imbalance degree of DTU data queues, a cloud-edge integrated data processing architecture is designed. It optimizes edge server selection, the offloading splitting ratio, and edge-cloud computing resource allocation in a collaboration mechanism. Second, an optimization problem is formulated to maximize the weighted difference between the total data processing volume and the load imbalance degree. Next, a cloud-edge collaboration-based data processing method is proposed. In the first stage, cloud-edge collaborative data offloading based on the load imbalance degree, and a data volume-aware deep Q-network (DQN) is developed. A penalty function based on load fluctuations and the data volume deficit is incorporated. It drives the DQN to evolve toward suppressing the fluctuation of load imbalance degree while ensuring differentiated long-term data volume constraints. In the second stage, cloud-edge computing resource allocation based on adaptive differential evolution is designed. An adaptive mutation scaling factor is introduced to overcome the gene overlapping issues of traditional heuristic approaches, enabling deeper exploration of the solution space and accelerating global optimum identification. Finally, the simulation results demonstrate that the proposed method effectively improves the data processing efficiency of DTUs while reducing the load imbalance degree. Full article
(This article belongs to the Special Issue Operation and Planning of Distribution Systems Under High Renewable Penetration)
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17 pages, 2553 KB  
Article
Optimal Energy Storage Allocation for Power Systems with High-Wind-Power Penetration Against Extreme-Weather Events
by Jie Zhang, Yuyue Zhang, Jingyi Teng, Nan Wang, Zhenhua Yuan, Donglei Sun and Runjia Sun
Energies 2026, 19(1), 146; https://doi.org/10.3390/en19010146 - 26 Dec 2025
Viewed by 510
Abstract
Frequent extreme-weather events pose severe challenges to the secure and economical operation of power systems with high renewable energy penetration. To strengthen grid resilience against such low-probability, high-impact events while maintaining good performance under normal conditions, this paper proposes an optimal energy storage [...] Read more.
Frequent extreme-weather events pose severe challenges to the secure and economical operation of power systems with high renewable energy penetration. To strengthen grid resilience against such low-probability, high-impact events while maintaining good performance under normal conditions, this paper proposes an optimal energy storage allocation method for power systems with high-wind-power penetration. We first identify two representative extreme wind power events and develop a risk assessment model that jointly quantifies load-shedding volume and transmission-line security margins. On this basis, a multi-scenario joint siting-and-sizing optimization model is formulated over typical-day and extreme-day scenarios to minimize total system cost, including annualized investment cost, operating cost, and risk cost. To solve the model efficiently, a two-stage hierarchical solution strategy is designed: the first stage determines an investment upper bound from typical-day scenarios, and the second stage optimizes storage allocation under superimposed extreme-day scenarios within this bound, thereby balancing operating economy and extreme-weather resilience. Simulation results show that the proposed method reduces loss-of-load under extreme-weather scenarios by 32.46% while increasing storage investment cost by only 0.18%, significantly enhancing system resilience and transmission-line security margins at a moderate additional cost. Full article
(This article belongs to the Special Issue Operation and Planning of Distribution Systems Under High Renewable Penetration)
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