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Processes
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Optimal Design, Control and Simulation of Energy Management Systems
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Optimal Design, Control and Simulation of Energy Management Systems

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

Deadline for manuscript submissions: 30 March 2026 | Viewed by 3346

Special Issue Editors

Dr. Chutong Wang

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Guest Editor
Department of Electrical Engineering, North China Electric Power University, Baoding 071003, China
Interests: energy storage; ectricity market; integrated energy system
Prof. Dr. Junhui Li

E-Mail Website
Guest Editor
School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Interests: power quality; interruption; voltage source converter; power control
Prof. Dr. Wuqin Tang

E-Mail Website
Guest Editor
College of Electrical Engineering, Guizhou University, Guiyang 550025, China
Interests: intelligent operation and maintenance; smart energy systems; learning based optimization and control
Dr. Yubin Wang

E-Mail Website
Guest Editor
School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
Interests: energy management systems; energy-transportation coupling; energy system resilience

Special Issue Information

Dear Colleagues,

Energy management systems (EMSs) have become critical in modern power grids and industrial applications due to the increasing complexity of energy production, distribution, and consumption. As the world shifts toward sustainable energy solutions, the optimal design, control, and simulation of EMSs are paramount to ensuring efficiency, stability, and flexibility in managing diverse energy resources.

This Special Issue entitled “Optimal Design, Control and Simulation of Energy Management Systems” seeks to showcase cutting-edge research focused on the development and improvement of EMSs. The aim is to bring together the latest advances in the design, control algorithms, and simulation techniques that optimize energy use across various sectors, such as power grids, renewable energy integration, smart buildings, and industrial processes. Topics of interest include, but are not limited to, the following:

  • Optimal design and architecture of energy management systems;
  • Advanced control strategies for real-time EMSs (e.g., model predictive control, adaptive control, multi-agent systems);
  • Simulation techniques for EMS performance analysis under different operating conditions;
  • Integration of renewable energy sources (e.g., wind, solar) into EMSs;
  • Demand response and load forecasting for efficient energy utilization;
  • Battery storage and energy storage system optimization in EMSs;
  • Distributed energy resource (DER) management and coordination;
  • Cybersecurity and fault tolerance in EMSs;
  • Case studies and applications of EMSs in power grids, industrial plants, and smart homes.

Dr. Chutong Wang
Prof. Dr. Junhui Li
Prof. Dr. Wuqin Tang
Dr. Yubin 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. 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

  • energy management systems
  • advanced control strategies
  • integration of renewable energy sources
  • distributed energy resources
  • energy storage systems
  • simulation techniques
  • demand response and load forecasting

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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

29 pages, 2731 KB  
Article
Study on the Improvement in Nuclear Generation Flexibility Under a Unified Electricity Market with a High Share of Renewables
by Ge Qin, Dongyuan Li, Kexin Hu, Qianying Gao, Jiaoshen Xu, Hui Ren and Jinling Lu
Processes 2026, 14(1), 7; https://doi.org/10.3390/pr14010007 - 19 Dec 2025
Viewed by 140
Abstract
China’s nuclear power plants traditionally operate to meet baseload needs, with minimal involvement in peak load regulation. However, as the share of renewable energy generation rapidly increases, the volatility of the power system and the demand for peak load regulation have significantly risen, [...] Read more.
China’s nuclear power plants traditionally operate to meet baseload needs, with minimal involvement in peak load regulation. However, as the share of renewable energy generation rapidly increases, the volatility of the power system and the demand for peak load regulation have significantly risen, necessitating greater nuclear power flexibility to meet the new power system’s requirements. Our study forecasts the energy structure and load demand for the Province of Liaoning in Northeastern China in 2035. Under this vision, it analyzes the flexibility challenges faced by nuclear generation units. A joint clearing model for spot electricity and ancillary services, along with an energy storage revenue model, was established. Based on this, this study analyzed the clearing results for various typical scenarios in the Province of Liaoning in 2035. The simulation results demonstrate that nuclear units will participate in peak shaving by the target year. This study demonstrates the feasibility of solid-state thermal storage in improving both flexibility and economic efficiency of nuclear generation. Based on these findings, policy recommendations are proposed, including improving regulation compensation mechanisms and promoting multi-energy coupling, providing crucial theoretical and practical support for the role transformation of nuclear generation entities in the new power system. This study establishes a full lifecycle economic assessment model for combined heat and power revenue versus thermal storage investment costs, considering integrated nuclear power–solid thermal energy storage heating systems as the primary technical pathway. Taking a configuration plan with a 715 MW heating capacity and a 6000 MWh thermal storage capacity as an example under Liaoning Province’s 2035 long-term scenario, the simulation results indicate that introducing solid thermal energy storage can significantly improve the revenue structure of nuclear units while meeting deep peak shaving demands, reducing the project’s static payback period to under 11 years. Full article
(This article belongs to the Special Issue Optimal Design, Control and Simulation of Energy Management Systems)
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17 pages, 2821 KB  
Article
A Collaborative Planning Method for Distributed Energy Storage Based on Differentiated Demands
by Zhiwei Li, Xijun Ren, Li Zhang, Tiancheng Shi, Yufeng Liu, Jiayao Wang, Huizhou Liu, Xueao Qiu and Zixuan Wang
Processes 2025, 13(11), 3680; https://doi.org/10.3390/pr13113680 - 14 Nov 2025
Viewed by 418
Abstract
With the continuous increase in the proportion of wind and solar power, the strong randomness and volatility of distributed new energy output have brought great challenges to the planning, regulation, and operation of the new distribution system. Distributed energy storage, with its characteristics [...] Read more.
With the continuous increase in the proportion of wind and solar power, the strong randomness and volatility of distributed new energy output have brought great challenges to the planning, regulation, and operation of the new distribution system. Distributed energy storage, with its characteristics such as scattered location distribution, flexible installation, small capacity, and diverse forms and application scenarios, is increasingly becoming an important resource and technical means to enhance the consumption capacity of new energy and ensure the safe and reliable operation of the power system. This paper proposes a collaborative planning method for distributed energy storage based on differentiated demands. First, the typical application scenarios of distributed energy storage are analyzed; secondly, the source–load matching degree and modularity are proposed as cluster division indicators. Voltage fluctuation, load fluctuation, and the net income of distributed energy storage are combined into multiple optimization objectives. Based on differentiated demands, a two-layer optimal configuration model of distributed energy storage is proposed and solved by using the improved particle swarm optimization algorithm. Finally, the feasibility and effectiveness of the proposed method were verified through a modified IEEE33 node simulation example. Full article
(This article belongs to the Special Issue Optimal Design, Control and Simulation of Energy Management Systems)
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21 pages, 1367 KB  
Article
Bi-Level Planning of Energy Storage and Relocatable Static Var Compensators in Distribution Networks with Seasonal Transformer Area Load
by He Jiang, Risheng Qin, Zhijie Gao, Guofang Sun, Sida Peng and Hui Ren
Processes 2025, 13(6), 1739; https://doi.org/10.3390/pr13061739 - 1 Jun 2025
Viewed by 715
Abstract
The integration of large-scale distributed photovoltaics (DGPVs) and the generation of distributed photovoltaics (PVs) and loads with distinct characteristics in different transformer areas causes voltage problems in distribution networks, significantly compromising operational reliability and economy. To address this challenge, this study proposes the [...] Read more.
The integration of large-scale distributed photovoltaics (DGPVs) and the generation of distributed photovoltaics (PVs) and loads with distinct characteristics in different transformer areas causes voltage problems in distribution networks, significantly compromising operational reliability and economy. To address this challenge, this study proposes the installation of a relocatable static var compensator (RSVC) to enhance the voltage regulation capability in addition to conventional voltage regulation methods. An RSVC can be deployed at critical nodes of distribution lines to provide continuous adjustable reactive power. RSVCs’ relocation capability in response to seasonal shifts in reactive power demand makes them an effective solution for spatiotemporal load disparities across transformer areas. A bi-level planning framework is established by first generating multiple typical scenarios based on load categories and their seasonal characteristics. The lower level achieves optimal operation in multiple scenarios through the coordination of active–reactive power regulation devices. The upper level employs a particle swarm optimization algorithm to determine the optimal siting and sizing of energy storage and the RSVC, iteratively invoking the lower-level model to minimize the total investment and operational costs. Validation was conducted on a modified IEEE 33-node test system. The results demonstrate that the proposed method effectively mitigates voltage violations caused by DGPVs and spatiotemporal load disparities while significantly enhancing the economic efficiency of distribution networks. Full article
(This article belongs to the Special Issue Optimal Design, Control and Simulation of Energy Management Systems)
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15 pages, 2640 KB  
Article
Inverse Characteristic Locus Method for Power System Low-Frequency Oscillation Control and Optimal Design
by Peng Shi, Yongcan Wang, Xi Wang, Chengwei Fan, Jiayu Bai, Baorui Chen, Hao Xu, Deqiang Gan and Chutong Wang
Processes 2025, 13(3), 920; https://doi.org/10.3390/pr13030920 - 20 Mar 2025
Viewed by 592
Abstract
Recent results indicate that the characteristic locus method provides a convenient approach for analyzing power system low-frequency stability. In this study, an enhanced version of the method, referred to as the inverse characteristic locus method, is introduced. By inverting the similarity matrix of [...] Read more.
Recent results indicate that the characteristic locus method provides a convenient approach for analyzing power system low-frequency stability. In this study, an enhanced version of the method, referred to as the inverse characteristic locus method, is introduced. By inverting the similarity matrix of the loop transfer function matrix of the system, a more reliable and accurate stability metric is obtained. The proposed method is applied to assess the impact of changes in wind turbine generator (WTG) dynamics and system operating conditions on stability. Simulation results demonstrate that variations in system operating conditions exert a greater influence on stability compared to changes in WTG dynamics. Full article
(This article belongs to the Special Issue Optimal Design, Control and Simulation of Energy Management Systems)
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