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Processes
Special Issues
Modeling, Optimization, and Control of Distributed Energy Systems
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Modeling, Optimization, and Control of Distributed Energy Systems

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

Deadline for manuscript submissions: 31 October 2025 | Viewed by 2666

Special Issue Editors

Dr. Lei Sun

E-Mail Website
Guest Editor
School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
Interests: planning method of energy systems; restoration control and resilience improvement of energy systems
Dr. Xiaodong Yang

E-Mail Website
Guest Editor
State Key Laboratory of High Efficiency and High Quality Electric Energy Conversion (Hefei University of Technology), Hefei 230009, China
Interests: flexible interconnection; AC/DC distribution system operation; service restoration; demand side management; peer-to-peer energy trading
Special Issues, Collections and Topics in MDPI journals
Dr. Yue Yang

E-Mail Website
Guest Editor
School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China
Interests: power system operation; power system dispatch; stochastic optimization methods

Special Issue Information

Dear Colleagues,

The push towards constructing clean, low-carbon, secure, and efficient distributed energy systems has gained broad consensus within the energy and power industry. As diverse energy sources with varying spatiotemporal distribution characteristics integrate into these systems, traditional modeling, optimization, and control methods face significant challenges. Relying solely on mechanism-based research methods often proves inadequate for solving the complex non-convex optimization problems inherent in distributed energy systems, limiting the ability to fully explore the synergy and potential value of various energy sources. Moreover, the interactive coordination of "source-grid-load-storage" within distributed energy systems significantly increases the complexity of information interaction, making data sharing between different energy entities a critical bottleneck in the optimization process. Centralized control methods also struggle to accommodate distributed energy systems' multi-entity, multi-spatial, and temporal scale operational characteristics. Thus, there is an urgent need for advanced research in the modeling, optimization, and control technologies for distributed energy systems to address these challenges.

This Special Issue on “Modeling, Optimization, and Control of Distributed Energy Systems” showcases recent advancements in this area. Topics of interest include, but are not limited to:

  • Multi-time scale dynamic modeling and simulation of distributed energy systems;
  • Modeling methods for cyber-physical distributed energy systems;
  • Morphological evolution and planning technologies for distributed energy systems;
  • Energy management and optimal operations of distributed energy systems;
  • Restoration control methods for distributed energy systems;
  • Evaluation and improvement of resilience and flexibility in distributed energy systems;
  • Application of artificial intelligence in the modeling, optimization, and control of distributed energy systems;
  • Stable operation and control technologies for distributed energy systems;
  • Aggregation of demand-side flexible resources and market mechanism;
  • Transactive energy control of distributed energy systems.

Dr. Lei Sun
Dr. Xiaodong Yang
Dr. Yue Yang
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 100 words) can be sent to the Editorial Office for announcement on this website.

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. Processes is an international peer-reviewed open access monthly 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

  • distributed energy sources
  • modeling
  • optimization algorithms
  • control strategy
  • distributed energy systems
  • renewable energy

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

22 pages, 2987 KiB  
Article
Optimal Configuration Method of Energy Routers in Active Distribution Network Considering Demand Response
by Junqing Jia, Tianyu Wu, Jia Zhou, Wenchao Cai, Zehua Wang, Junda Lu, Chen Shao and Jiaoxin Jia
Processes 2025, 13(4), 1248; https://doi.org/10.3390/pr13041248 - 20 Apr 2025
Viewed by 156
Abstract
The energy router (ER) is a crucial component in smart distribution networks, and its optimal configuration is essential for enhancing the operational efficiency, economy, and security of the grid. However, existing research rarely considers both the location and sizing costs of the ER [...] Read more.
The energy router (ER) is a crucial component in smart distribution networks, and its optimal configuration is essential for enhancing the operational efficiency, economy, and security of the grid. However, existing research rarely considers both the location and sizing costs of the ER in conjunction with flexible load demand response. Therefore, this paper proposes an optimal configuration method for the energy router in active distribution networks, incorporating demand response. First, to balance the comprehensive operational characteristics of the active distribution network throughout the year with computational efficiency, an improved K-means clustering algorithm is employed to construct multiple representative scenarios. Then, a bi-level programming model is established for ER location and sizing, considering demand response. The upper level optimizes the location and capacity configuration of the ER to minimize the overall cost of the distribution network. The lower level focuses on multi-objective optimization, including peak shaving, valley filling, network losses, and voltage deviations, to achieve energy scheduling within the distribution network. Finally, an improved bi-level particle swarm optimization algorithm is employed to solve the model. Simulation results based on the IEEE 33-node system demonstrate that the peak shaving and valley filling optimization rate after ER integration into the active distribution network is at least 9.19%, and it is improved to 14.35% when combined with demand response. Concurrently, the integration of the ER enhances the distribution network’s ability to absorb renewable energy, reduces network losses, and improves power quality. Full article
(This article belongs to the Special Issue Modeling, Optimization, and Control of Distributed Energy Systems)
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19 pages, 5123 KiB  
Article
A Dual-Objective Approach to Load Management: Telecommunication Switch Optimization with Distributed Generation Integration
by Hossein Parsadust, Hossein Lotfi and Mohammad Ebrahim Hajiabadi
Processes 2025, 13(3), 716; https://doi.org/10.3390/pr13030716 - 1 Mar 2025
Viewed by 734
Abstract
This research addresses the challenge of load management in electricity distribution networks, focusing on the optimal placement of telecommunication load breaker switches in the presence of distributed generation units. By integrating two key objectives—preserving critical loads and minimizing energy not supplied—a strategy is [...] Read more.
This research addresses the challenge of load management in electricity distribution networks, focusing on the optimal placement of telecommunication load breaker switches in the presence of distributed generation units. By integrating two key objectives—preserving critical loads and minimizing energy not supplied—a strategy is proposed to enhance the performance of the power distribution grid during peak load conditions. The study utilizes a search algorithm designed around a dual-objective function to simultaneously prioritize high-importance loads and reduce energy not supplied by optimizing the placement of telecommunication load breaker switches while considering distributed generation. The effectiveness of the proposed model has been evaluated on a 33-bus test network as well as a feeder from the Iranian distribution network, with detailed analysis and interpretation of the results. Simulation findings reveal that as the priority of critical loads increases, the optimal placement of switches adapts accordingly, leading to significant improvements in the reliability and efficiency of the power distribution network under peak load scenarios. Full article
(This article belongs to the Special Issue Modeling, Optimization, and Control of Distributed Energy Systems)
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19 pages, 3481 KiB  
Article
Risk Assessment Method for Power Distribution Systems Based on Spatiotemporal Characteristics of the Typhoon Disaster Chain
by Bin Chen, Nuoling Sun, Hao Chen, Linyao Zhang, Jiawei Wan and Jie Su
Processes 2025, 13(3), 699; https://doi.org/10.3390/pr13030699 - 28 Feb 2025
Cited by 1 | Viewed by 440
Abstract
In recent years, power outages due to typhoon-induced rainstorms, waterlogging, and other extreme weather events have become increasingly common, and accurately assessing the risk of damage to the distribution system during a disaster is critical to enhancing the resilience of the power system. [...] Read more.
In recent years, power outages due to typhoon-induced rainstorms, waterlogging, and other extreme weather events have become increasingly common, and accurately assessing the risk of damage to the distribution system during a disaster is critical to enhancing the resilience of the power system. Therefore, a risk assessment method for power distribution systems considering the spatiotemporal characteristics of the typhoon disaster chain is proposed. The mechanism of forming the typhoon disaster chain is first analyzed and its spatiotemporal characteristics are modeled. Secondly, the failure probability of the distribution system equipment during the evolution process of the disaster chain is modeled. Then, the non-sequential Monte Carlo state sampling method combined with the distribution system risk assessment index is proposed to establish the disaster risk assessment system of the distribution system. Finally, based on the IEEE 33-bus power system, the proposed distribution system disaster risk assessment method is verified. Simulation solutions show that the proposed assessment method can effectively assess the disaster risk of the distribution system under the influence of the typhoon disaster chain. The simulation results show that at the time step of typhoon landfall, the load shedding reaches 1315.3 kW with a load shedding rate of 35.4%. The total economic loss at the time step is 2,289,200 CNY. These results demonstrate the effectiveness of the proposed method in assessing disaster risks and improving the resilience of power systems during typhoon events. Full article
(This article belongs to the Special Issue Modeling, Optimization, and Control of Distributed Energy Systems)
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16 pages, 1597 KiB  
Article
Aggregation Modeling for Integrated Energy Systems Based on Chance-Constrained Optimization
by Jianhua Zhou, Rongqiang Li, Yang Li and Linjun Shi
Processes 2024, 12(12), 2672; https://doi.org/10.3390/pr12122672 - 27 Nov 2024
Cited by 1 | Viewed by 843
Abstract
Integrated energy systems (IESs) strengthen electricity–gas–heat multi-energy coupling and reduce wind and light abandonment. For grids with superior distribution, IESs are similar to virtual energy storage systems and are able to realize efficient interaction with the grid by synergizing the operating status of [...] Read more.
Integrated energy systems (IESs) strengthen electricity–gas–heat multi-energy coupling and reduce wind and light abandonment. For grids with superior distribution, IESs are similar to virtual energy storage systems and are able to realize efficient interaction with the grid by synergizing the operating status of the internal equipment and improving the security, economy, and flexibility of the grid’s operation. However, the internal equipment coupling of an IES is complex, and determining how to evaluate its adjustable capacity range (that is, the upper and lower boundaries of its external energy demand) considering the uncertainty and volatility of wind power and photovoltaic output is a problem to be solved. To solve this problem, this paper presents a chance-constrained evaluation method for the adjustable capacity of IESs. Firstly, mathematical models and operational constraints of each device within the IES are established. Secondly, based on the mathematical model of chance-constrained planning, an adjustable capacity range assessment model considering the uncertainty of wind and photovoltaic output is established. Finally, the MATLAB/Yalmip/Gurobi solver is used for the optimization solution, and the adjustable capacity range interval of the constructed IES model is solved using an arithmetic example to analyze and verify the correctness and validity of the method and to study the influencing factors of its adjustable range. Full article
(This article belongs to the Special Issue Modeling, Optimization, and Control of Distributed Energy Systems)
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