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2nd Edition of Analysis and Optimization Control of Active Distribution...
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2nd Edition of Analysis and Optimization Control of Active Distribution Networks and Smart Grids

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 3265

Editors

Dr. Jingrui Zhang

E-Mail Website
Guest Editor
Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen 361005, China
Interests: power system dispatch; energy management of microgrid/active distribution networks; swarm intelligence algorithm
Special Issues, Collections and Topics in MDPI journals
Dr. Jian Wang

E-Mail Website
Guest Editor
School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China
Interests: active distribution network; convex optimization; distributed generation
Special Issues, Collections and Topics in MDPI journals
Dr. Po Li

E-Mail Website
Guest Editor
Department of Instrumental & Electrical Engineering, Xiamen University, Xiamen 361005, China
Interests: modeling and optimization control for complex systems including unmanned aerial vehicle power systems, ro-bot power systems, and other hybrid power systems
Special Issues, Collections and Topics in MDPI journals
Dr. Tengpeng Chen

E-Mail Website
Guest Editor
Department of Instrumental & Electrical Engineering, Xiamen University, Xiamen 361005, China
Interests: energy management for microgrids; optimal PMU placement in distribution systems; distributed optimization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

A safe, efficient, and green power grid is key for reducing carbon emissions and achieving carbon neutrality. Active distribution networks are the main carriers of renewables and power load, and also constitute an important part of smart grids. However, in recent years, the increasing integration of intermittent renewables (e.g., wind power and photovoltaic) and new loads (e.g., electric vehicles) has had a huge impact on the form structure and operation characteristics of active distribution networks, including network flexible interconnection, grid connections to new distribution equipment, multiple flexible control modes, and power imbalances of source and load. These not only increase the complexity of the analysis of the active distribution network, but also make the control of the distribution network more difficult. To address these issues, new methods are needed to analyze the morphological evolution, flexibility, stability, and security of active distribution networks, and to realize their safe and stable operation through advanced control technology.

This Special Issue on ‘Analysis and Optimization Control of Active Distribution Networks and Smart Grids’ calls for state-of-the-art research works on this promising research area. This Special Issue will gather high-quality research articles that provide original contributions regarding the analysis and optimization control of active distribution networks and smart grids. Topics of interest include, but are not limited to, the following:

  • Forecasting of renewable generations and active loads in active distribution and smart grids;
  • Modeling and optimizing techniques in the optimal operation of active distribution networks and smart grids;
  • Morphological evolution of active distribution networks and smart grids;
  • Hosting capacity assessment for renewables in active distribution networks and smart grids;
  • Flexibility and resilience quantification for active distribution networks and smart grids;
  • Security risk analysis and defense of cyber-physical systems in active distribution networks and smart grids;
  • Stability analysis and control of active distribution networks and smart grids;
  • Power quality analysis and control of active distribution networks and smart grids;
  • Volt/var control and energy management for active distribution networks and smart grids under uncertainties;
  • Advanced learning-based modeling and optimization control of active distribution networks and smart grids with high penetration of renewables;
  • Power electronic converters control and optimization in hybrid propulsion microgrids.

Dr. Jingrui Zhang
Dr. Jian Wang
Dr. Po Li
Dr. Tengpeng Chen
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes 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 2400 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

  • active distribution network
  • smart grid
  • renewables
  • analysis and control
  • uncertainty
  • forecasting

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Published Papers (4 papers)

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Research

17 pages, 6870 KB  
Article
A Novel Hybrid Approach for Non-Stationary Electricity Price Forecasting
by Yinwei Li, Ningxuan Li, Hui Qi, Fei Wang, Yiwen Luo and Xuchu Jiang
Processes 2026, 14(9), 1372; https://doi.org/10.3390/pr14091372 - 24 Apr 2026
Viewed by 288
Abstract
With the implementation of market-oriented electricity trading in an increasing number of countries, accurate electricity price forecasting can not only help participants in the electricity market to make more reasonable decisions but also enable regulators to have a more reliable regulatory basis. Therefore, [...] Read more.
With the implementation of market-oriented electricity trading in an increasing number of countries, accurate electricity price forecasting can not only help participants in the electricity market to make more reasonable decisions but also enable regulators to have a more reliable regulatory basis. Therefore, it is necessary to propose an appropriate electricity price forecasting method. In view of the insufficiency of the traditional models in dealing with nonlinear and non-stationary data, to improve the detection ability of the model for hidden information in data and considering the high randomness of electricity price data, this paper proposes an electricity price forecasting method based on singular spectrum analysis (SSA) to decompose the original sequence and combines it with an extreme learning machine (ELM) optimized by the grey wolf optimizer (GWO). First, SSA is used to decompose the original sequence, and then the ELM is used to predict each subsequence and add them, in which the number of neurons in the hidden layer of each ELM is jointly optimized by the GWO. To verify the effectiveness of the SSA–GWO–ELM model, a total of 2106 days of electricity price data in Victoria, Australia, were selected for modeling. The results show that the prediction accuracy of the model proposed in this paper is significantly higher than that of the other comparison models, and the R2 score is as high as 0.989, which is 0.017 higher than that of the suboptimal SSA–ELM. It can also maintain strong robustness and high prediction accuracy for heterogeneous data on power demand. SSA has the potential for real-time prediction, which can provide reliable data support for electricity market participants and supervisors. Full article
(This article belongs to the Special Issue 2nd Edition of Analysis and Optimization Control of Active Distribution Networks and Smart Grids)
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39 pages, 6157 KB  
Article
A Hybrid Machine Learning and NGO Algorithm Approach for Fault Classification and Localization in Electrical Distribution Lines
by Khaled Guerraiche, Amine Bouadjmi Abbou, Éric Chatelet, Latifa Dekhici, Abdelkader Zeblah and Mohammed Adel Djari
Processes 2026, 14(6), 944; https://doi.org/10.3390/pr14060944 - 16 Mar 2026
Viewed by 538
Abstract
Today’s distribution networks are becoming increasingly complex, necessitating highly accurate and robust fault diagnosis methods. Traditional methods based on impedance or traveling waves often lack flexibility and precision in these dynamic environments. This study proposes a hybrid approach based on the synergy between [...] Read more.
Today’s distribution networks are becoming increasingly complex, necessitating highly accurate and robust fault diagnosis methods. Traditional methods based on impedance or traveling waves often lack flexibility and precision in these dynamic environments. This study proposes a hybrid approach based on the synergy between machine learning (ML) techniques and a recent metaheuristic, the Northern Goshawk Optimizer (NGO). Fault location is performed using a cubic spline interpolation model. Classification is handled by a decision tree, while fault resistance—a key parameter that significantly influences diagnostic performance—is optimized using the NGO algorithm. The effectiveness of the proposed method is evaluated through a series of experiments conducted on the IEEE 34-bus test network. These experiments encompass various fault scenarios (single line-to-ground, line-to-line, double line-to-ground, and three-phase faults) as well as voltage and load variation conditions. Fault resistance values considered in the study are 0, 10, 50 and 100 ohms. The results highlight the robustness and efficiency of the hybrid approach, achieving an accuracy rate of up to 99.999% in fault location. This level of performance enables reliable identification of both the fault location and the affected line. Full article
(This article belongs to the Special Issue 2nd Edition of Analysis and Optimization Control of Active Distribution Networks and Smart Grids)
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28 pages, 6452 KB  
Article
On Voltage Regulation Technology for Long-Distance Power Supply in Underground Coal Mines Based on On-Load Voltage Regulation
by Wenjun Fu, Ying Xu, Tianji Lv and Liang Zhang
Processes 2025, 13(12), 3808; https://doi.org/10.3390/pr13123808 - 25 Nov 2025
Viewed by 940
Abstract
With the rapid growth in coal demands driven by economic development, the applications scenarios of long-distance, high-power mining operations in underground coal mines has gradually been expanded. Taking voltage regulation technology for long-distance power supply in underground coal mines as the research object, [...] Read more.
With the rapid growth in coal demands driven by economic development, the applications scenarios of long-distance, high-power mining operations in underground coal mines has gradually been expanded. Taking voltage regulation technology for long-distance power supply in underground coal mines as the research object, this paper analyzed the mechanisms behind voltage fluctuation hazards and the status quo of existing voltage regulation technologies in coal mines and put forward a voltage regulation technology for long-distance power supply in tunneling faces of coal mines based on on-load voltage regulation. On this basis, a voltage regulation device for long-distance power supply in underground coal mines was designed and applied to the long-distance power supply system of Wanli Coal Mine’s tunneling faces. All indicators met the design requirements, validating the effectiveness of the device and the applicability of the research outcomes, and providing an effective solution for addressing voltage fluctuations in the long-distance power supply of underground coal mines. Full article
(This article belongs to the Special Issue 2nd Edition of Analysis and Optimization Control of Active Distribution Networks and Smart Grids)
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16 pages, 1122 KB  
Article
Optimal Power Flow of Unbalanced Distribution Networks Using a Novel Shrinking Net Algorithm
by Xun Xu, Liangli Xiong, Menghan Xiao, Haoming Liu and Jian Wang
Processes 2025, 13(10), 3226; https://doi.org/10.3390/pr13103226 - 10 Oct 2025
Viewed by 1056
Abstract
The increasing penetration of distributed energy resources (DERs) in unbalanced distribution networks presents significant challenges for optimal operation, particularly concerning power loss minimization and voltage regulation. This paper proposes a comprehensive Optimal Power Flow (OPF) model that coordinates various assets, including on-load tap [...] Read more.
The increasing penetration of distributed energy resources (DERs) in unbalanced distribution networks presents significant challenges for optimal operation, particularly concerning power loss minimization and voltage regulation. This paper proposes a comprehensive Optimal Power Flow (OPF) model that coordinates various assets, including on-load tap changers (OLTCs), reactive power compensators, and controllable electric vehicles (EVs). To solve this complex and non-convex optimization problem, we developed the Shrinking Net Algorithm (SNA), a novel metaheuristic with mathematically proven convergence. The proposed framework was validated using the standard IEEE 123-bus test system. The results demonstrate significant operational improvements: total active power loss was reduced by 32.1%, from 96.103 kW to 65.208 kW. Furthermore, all node voltage violations were eliminated, with the minimum system voltage improving from 0.937 p.u. to a compliant 0.973 p.u. The findings confirm that the proposed SNA is an effective and robust tool for this application, highlighting the substantial economic and technical benefits of coordinated asset control for modern distribution system operators. Full article
(This article belongs to the Special Issue 2nd Edition of Analysis and Optimization Control of Active Distribution Networks and Smart Grids)
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