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Energies
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Energy Storage Technologies and Applications for Smart Grids
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Energy Storage Technologies and Applications for Smart Grids

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 1738

Special Issue Editor

Dr. Jingyuan Yin

E-Mail Website
Guest Editor
1. Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China
2. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
Interests: flexible HVDC transmission technology; distributed power generation and energy storage technology; DC power grid key equipment technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Energy storage technology is vital in the creation of novel power systems that utilize a high proportion of new energy as the main body. It can effectively enhance the acceptance capacity of new forms of energy such as wind and photovoltaic power. Numerous countries have successively introduced strong policies that greatly promote the rapid development of energy storage technology. Energy storage technology is conducive to promoting the development of technology for the generation of new energy, while also providing functions such as peak shaving, frequency regulation, backup power supply, and black start; this technology can also promote the consumption of renewable energy, thereby enhancing the safety and flexibility of power grid operation. The application of energy storage is extensive, and it can be utilized in the comprehensive integration of power generation, transmission, and distribution, thus playing multiple roles. Exploring the application of energy storage in power systems and smart microgrids can help further leverage the advantages of energy storage and promote the efficient, safe, and stable operation of smart grids.

The scope of this Special Issue includes the following topics:

  1. Energy storage technology and applications;
  2. Research on energy storage power stations on the power supply side, grid side, and user side;
  3. Research on optical storage charging stations;
  4. Research on mobile energy storage applications;
  5. The application of energy storage in smart microgrids;
  6. Research on the standard system of energy storage technology;
  7. Analysis and research on diversified energy storage business models;
  8. Research on energy storage policy environment and mechanism;
  9. Other energy-storage-related research.

Dr. Jingyuan Yin
Guest Editor

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

  • flexible HVDC transmission technology
  • distributed power generation
  • energy storage technology
  • DC power grid key equipment technology

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Published Papers (2 papers)

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Research

24 pages, 7462 KiB  
Article
Multi-Time-Scale Layered Energy Management Strategy for Integrated Production, Storage, and Supply Hydrogen Refueling Stations Based on Flexible Hydrogen Load Characteristics of Ports
by Zhuoyu Jiang, Rujie Liu, Weiwei Guan, Lei Xiong, Changli Shi and Jingyuan Yin
Energies 2025, 18(7), 1583; https://doi.org/10.3390/en18071583 - 22 Mar 2025
Viewed by 284
Abstract
Aiming at resolving the problem of stable and efficient operation of integrated green hydrogen production, storage, and supply hydrogen refueling stations at different time scales, this paper proposes a multi-time-scale hierarchical energy management strategy for integrated green hydrogen production, storage, and supply hydrogen [...] Read more.
Aiming at resolving the problem of stable and efficient operation of integrated green hydrogen production, storage, and supply hydrogen refueling stations at different time scales, this paper proposes a multi-time-scale hierarchical energy management strategy for integrated green hydrogen production, storage, and supply hydrogen refueling station (HFS). The proposed energy management strategy is divided into two layers. The upper layer uses the hourly time scale to optimize the operating power of HFS equipment with the goal of minimizing the typical daily operating cost, and proposes a parameter adaptive particle swarm optimization (PSA-PSO) solution algorithm that introduces Gaussian disturbance and adaptively adjusts the learning factor, inertia weight, and disturbance step size of the algorithm. Compared with traditional optimization algorithms, it can effectively improve the ability to search for the optimal solution. The lower layer uses the minute-level time scale to suppress the randomness of renewable energy power generation and hydrogen load consumption in the operation of HFS. A solution algorithm based on stochastic model predictive control (SMPC) is proposed. The Latin hypercube sampling (LHS) and simultaneous backward reduction methods are used to generate and reduce scenarios to obtain a set of high-probability random variable scenarios and bring them into the MPC to suppress the disturbance of random variables on the system operation. Finally, real operation data of a HFS in southern China are used for example analysis. The results show that the proposed energy management strategy has a good control effect in different typical scenarios. Full article
(This article belongs to the Special Issue Energy Storage Technologies and Applications for Smart Grids)
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16 pages, 12178 KiB  
Article
SOC Equalization Control Method Considering SOH in DC–DC Converter Cascaded Energy Storage Systems
by Shixian Bai, Xiangqian Tong, Xin Ma and Jie Zhou
Energies 2024, 17(24), 6385; https://doi.org/10.3390/en17246385 - 19 Dec 2024
Cited by 1 | Viewed by 820
Abstract
In large-scale industrial and commercial energy storage systems, as well as ground power station energy storage systems, the trend is to adopt large-capacity battery cells to reduce system construction costs. It is essential to screen the consistency of battery cells during the initial [...] Read more.
In large-scale industrial and commercial energy storage systems, as well as ground power station energy storage systems, the trend is to adopt large-capacity battery cells to reduce system construction costs. It is essential to screen the consistency of battery cells during the initial design phase. In conventional energy storage systems, battery clusters utilize multiple batteries connected in series, which can lead to differential attenuation over time and inconsistent state of charge (SOC) among the batteries. The “barrel effect” diminishes the effective capacity of the energy storage system. To mitigate this issue, a DC–DC converter cascaded energy storage system has been developed, incorporating precise charge and discharge management for each battery module within a cluster. By implementing SOC equalization control at the module level, it mitigates the barrel effect and enables full utilization of each battery module’s charging and discharging capabilities, thereby enhancing the overall charge–discharge capacity of the energy storage system. However, when considering only the SOC equalizing factor, its effectiveness may be limited by constraints such as DC–DC converter power limitations and device voltage stress levels. Therefore, a novel SOC equalization control method that considers both SOH and SOC variations across battery modules is proposed here. Through a droop control methodology combined with closed-loop control implementation on eight DC–DC converter cascaded energy storage systems, we validate the improved effectiveness achieved by incorporating SOH-aware SOC equalization control. The energy storage system has the capability to enhance both charging and discharging capacities, achieving a remarkable increase of 1.85% every 10 min, thereby yielding significant economic advantages. Full article
(This article belongs to the Special Issue Energy Storage Technologies and Applications for Smart Grids)
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