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Smart Energy Storage and Management

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "D: Energy Storage and Application".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 2243

Special Issue Editors


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Guest Editor
School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
Interests: energy storage optimal configuration and control technology; power grids; battery management systems; data mining; distributed power generation; power apparatus; power distribution reliability
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
School of Electric Power Engineering, Nanjing Institute of Technology, Nanjing 211167, China
Interests: lithium compounds; secondary cells; frequency control; power engineering computing; power grids; battery management systems
Special Issues, Collections and Topics in MDPI journals
College of Electrical Engineering, Sichuan University, Chengdu 610065, China
Interests: power system stability and control; renewable power generation; grid-connected energy storage system control; flexible DC power transmission
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the critical area of energy storage and management, emphasizing innovative approaches and technologies that enhance the efficiency, reliability, and sustainability of energy systems. As the global transition towards renewable energy sources accelerates, effective energy storage and management solutions become increasingly vital for stabilizing power grids and ensuring a consistent energy supply.

In addition, this Special Issue will explore advanced methodologies in the design and management of energy storage systems, highlighting how optimized design can significantly improve the performance and longevity of these systems. A key area of interest is the battery modeling and online identification of parameters, which is crucial for the estimation of battery state of X (SOX) and predicting the lifespan of batteries. This involves sophisticated techniques that combine physical models with data-driven approaches to provide accurate and reliable assessments.

Another focus is on the integration of data-driven and mechanistic models in battery diagnostics and prognostics, leveraging big data analytics to predict potential failures and optimize maintenance schedules. This approach is particularly relevant in enhancing the safety and reliability of battery systems, which are central to modern energy storage solutions.

Furthermore, this Special Issue will cover innovative testing methodologies and performance evaluation techniques for battery systems. These methods are essential for understanding the operational characteristics of batteries under various conditions and for developing standards that ensure the quality and safety of energy storage technologies.

By gathering cutting-edge research and practical insights, this Special Issue aims to contribute to the development of more efficient, reliable, and sustainable energy storage systems. We invite submissions that address these challenges through novel technologies, methodologies, and applications, helping to advance the field of energy storage and management.

Prof. Dr. Haitao Liu
Dr. Jichang Peng
Dr. Jinhao Meng
Dr. Qiao Peng
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. 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

  • lithium compounds
  • secondary cells
  • frequency control
  • power engineering computing
  • power grids
  • battery management systems

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Published Papers (3 papers)

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Research

22 pages, 1447 KiB  
Article
Optimization of a Nuclear–CSP Hybrid Energy System Through Multi-Objective Evolutionary Algorithms
by Chenxiao Ji, Xueying Nie, Shichao Chen, Maosong Cheng and Zhimin Dai
Energies 2025, 18(9), 2189; https://doi.org/10.3390/en18092189 - 25 Apr 2025
Viewed by 286
Abstract
Combining energy storage with base-load power sources offers an effective way to cover the fluctuation of renewable energy. This study proposes a nuclear–solar hybrid energy system (NSHES), which integrates a small modular thorium molten salt reactor (smTMSR), concentrating solar power (CSP), and thermal [...] Read more.
Combining energy storage with base-load power sources offers an effective way to cover the fluctuation of renewable energy. This study proposes a nuclear–solar hybrid energy system (NSHES), which integrates a small modular thorium molten salt reactor (smTMSR), concentrating solar power (CSP), and thermal energy storage (TES). Two operation modes are designed and analyzed: constant nuclear power (mode 1) and adjusted nuclear power (mode 2). The nondominated sorting genetic algorithm II (NSGA-II) is applied to minimize both the deficiency of power supply probability (DPSP) and the levelized cost of energy (LCOE). The decision variables used are the solar multiple (SM) of CSP and the theoretical storage duration (TSD) of TES. The criteria importance through inter-criteria correlation (CRITIC) method and the technique for order preference by similarity to ideal solution (TOPSIS) are utilized to derive the optimal compromise solution. The electricity curtailment probability (ECP) is calculated, and the results show that mode 2 has a lower ECP compared with mode 1. Furthermore, the configuration with an installed capacity of nuclear and CSP (100:100) has the lowest LCOE and ECP when the DPSP is satisfied with certain conditions. Optimizing the NSHES offers an effective approach to mitigating the mismatch between energy supply and demand. Full article
(This article belongs to the Special Issue Smart Energy Storage and Management)
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15 pages, 9684 KiB  
Article
Analysis and Verification of Equivalent Circuit Model of Soft-Pack Lithium Batteries
by Fei Li, Zhaojie Li, Yanlei Zhang, Guoning Xu, Xuwei Wang and Haoyi Zhang
Energies 2025, 18(3), 510; https://doi.org/10.3390/en18030510 - 23 Jan 2025
Cited by 1 | Viewed by 641
Abstract
High-energy-density lithium batteries play a crucial role in the lightweight design of stratospheric airship systems. This paper conducts an in-depth experimental study of the equivalent circuit model of soft-pack batteries, with a focus on how parameter identification methods affect model accuracy. To this [...] Read more.
High-energy-density lithium batteries play a crucial role in the lightweight design of stratospheric airship systems. This paper conducts an in-depth experimental study of the equivalent circuit model of soft-pack batteries, with a focus on how parameter identification methods affect model accuracy. To this end, first-order RC, second-order RC, and third-order RC equivalent circuit models were constructed, and model parameters under different temperature and current conditions were obtained through constant-current intermittent discharge experiments. During the parameter identification process, special consideration was given to the impact of sampling time on voltage measurements and the interdependent constraints among models. Additionally, the effects of current, temperature, and SOC (state of charge) variations on ohmic resistance and polarization resistance–capacitor parameters were analyzed. The experimental results show that the root mean square error (RMSE) of battery terminal voltage calculated using parameter identification methods that account for these factors is significantly lower than when these factors are not considered. By comparing the voltage calculation accuracy and operational efficiency of the three models, the second-order RC model was determined to be the preferred choice due to its simple structure, high computational efficiency, and superior accuracy. Full article
(This article belongs to the Special Issue Smart Energy Storage and Management)
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16 pages, 2761 KiB  
Article
Design of Energy Management Strategy for Integrated Energy System Including Multi-Component Electric–Thermal–Hydrogen Energy Storage
by Bo Peng, Yunguo Li, Hengyang Liu, Ping Kang, Yang Bai, Jianyong Zhao and Heng Nian
Energies 2024, 17(23), 6184; https://doi.org/10.3390/en17236184 - 8 Dec 2024
Cited by 4 | Viewed by 940
Abstract
To address the challenges of multi-energy coupling decision-making caused by the complex interactions and significant conflicts of interest among multiple entities in integrated energy systems, an energy management strategy for integrated energy systems with electricity, heat, and hydrogen multi-energy storage is proposed. First, [...] Read more.
To address the challenges of multi-energy coupling decision-making caused by the complex interactions and significant conflicts of interest among multiple entities in integrated energy systems, an energy management strategy for integrated energy systems with electricity, heat, and hydrogen multi-energy storage is proposed. First, based on the coupling relationship of electricity, heat, and hydrogen multi-energy flows, the architecture of the integrated energy system is designed, and the mathematical model of the main components of the system is established. Second, evaluation indexes in three dimensions, including energy storage device life, load satisfaction rate, and new energy utilization rate, are designed to fully characterize the economy, stability, and environmental protection of the system during operation. Then, an improved radar chart model considering multi-evaluation index comprehensive optimization is established, and an adaptability function is constructed based on the sector area and perimeter. Combined with the operation requirements of the electric–thermal–hydrogen integrated energy system, constraint conditions are determined. Finally, the effectiveness and adaptability of the strategy are verified by examples. The proposed strategy can obtain the optimal decision instructions under different operation objectives by changing the weight of evaluation indexes, while avoiding the huge decision space and secondary optimization problems caused by multiple non-inferior solutions in conventional optimization, and has multi-scenario adaptability. Full article
(This article belongs to the Special Issue Smart Energy Storage and Management)
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