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Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement
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Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement

A Special Issue of Processes (ISSN 2227-9717) belonging to the section "Energy Systems".

Deadline for manuscript submissions: 15 July 2027 | Viewed by 8477

Editors

Dr. Rui Wang

E-Mail Website
Guest Editor
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Interests: energy routing devices; coordinated control of new energy; power system stability analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Wentao Jiang

E-Mail Website
Guest Editor
School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
Interests: control of power electronics; DC microgrid; energy storage system

Special Issue Information

Dear Colleagues,

Energy storage as a technology capable of providing timely and safe power–energy output can effectively support the stable operation of novel power systems under normal conditions and enhance resilience under extreme scenarios. However, different types of energy storage systems affect system response speed and cost; different connection points alter system flow distribution, influencing network losses and voltage levels; and different energy storage control methods struggle to cope with the uncertainty of renewable energy output, which generates vast scenarios. How to rationally utilize energy storage technology to enhance grid dynamics is a pressing issue that needs to be addressed.

This Special Issue on "Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement" aims to introduce the latest planning, control, and dispatch technologies of energy storage systems to enhance grid dynamic performance. Topics include, but are not limited to, methods and/or application in the following areas:

  • New energy storage technologies, equipment, and applications;
  • Energy storage technologies and their applications in power grids and renewable energy stations;
  • Technologies for energy storage participation in voltage and frequency regulation of power grids;
  • Integrated source–grid–load–storage modeling and simulation technologies;
  • Integrated source–grid–load–storage planning, design, and operation technologies;
  • Integrated source–grid–load–storage coordinated control technologies.

Dr. Rui Wang
Dr. Wentao Jiang
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

  • energy storage system
  • energy storage optimization and control
  • energy storage dispatch technologies
  • integrated source–grid–load–storage coordinated control
  • grid dynamic enhancement

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Published Papers (7 papers)

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Research

27 pages, 13050 KB  
Article
A Double-PLL-Based Impedance Reshaping Strategy for DFIG System Under Grid Frequency Deviation
by Zhijie Zeng, Xiaoqing Lin, Dawei Chen, Bogu Huang and Haiqiao Zhao
Processes 2026, 14(18), 2965; https://doi.org/10.3390/pr14182965 (registering DOI) - 17 Sep 2026
Viewed by 110
Abstract
The stable operation of doubly fed induction generator (DFIG) systems under weak-grid and off-nominal-frequency conditions is important for reliable wind-power integration. However, the phase-locked loop (PLL) dynamics can degrade DFIG impedance and damping, while conventional single-PLL reshaping may suffer from compensation drift under [...] Read more.
The stable operation of doubly fed induction generator (DFIG) systems under weak-grid and off-nominal-frequency conditions is important for reliable wind-power integration. However, the phase-locked loop (PLL) dynamics can degrade DFIG impedance and damping, while conventional single-PLL reshaping may suffer from compensation drift under grid-frequency deviations and often relies on a high-pass filter. Therefore, this paper proposes an integrated Double-PLL-Based impedance-reshaping strategy for DFIG systems. Firstly, a complete DFIG admittance model incorporating the rotor-side converter, grid-side converter, DC link, and PLL dynamics is established to identify the critical coupling channel responsible for the adverse impedance characteristics. Secondly, a supplementary rotor-current compensation path is constructed to directly reshape the adverse impedance characteristics and improve system damping. Thirdly, the relative phase angle between the main and auxiliary PLLs is used to generate a frequency-adaptive compensation signal, thereby avoiding continuous compensation drift under persistent frequency deviations and reducing reliance on a dedicated high-pass filter. In this complete strategy, the compensation path directly performs impedance reshaping, while the Double-PLL-Based implementation provides frequency adaptation. Finally, generalized Nyquist analysis and MATLAB/Simulink simulations demonstrate improved impedance matching and oscillation suppression under the considered weak-grid and continuous-frequency-deviation conditions, while hardware-in-the-loop (HIL) experiments corroborate the robustness under PLL-parameter variations. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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26 pages, 992 KB  
Article
AI-Based Customized Simulation Setup, Process Control, and Result Processing Technology for Distribution Networks
by Cheng Long, Hua Zhang, Xueneng Su, Yiwen Gao, Qian Xie and Kun Zheng
Processes 2026, 14(14), 2333; https://doi.org/10.3390/pr14142333 - 17 Jul 2026
Viewed by 452
Abstract
To address the two fundamental contradictions in distribution network digital simulation systems: “diversified simulation requirements versus standardized configuration” and “massive simulation outputs versus sparse decision-making information”, this paper builds upon existing work on Common Information Model (CIM)-based automatic simulation model generation and dynamic [...] Read more.
To address the two fundamental contradictions in distribution network digital simulation systems: “diversified simulation requirements versus standardized configuration” and “massive simulation outputs versus sparse decision-making information”, this paper builds upon existing work on Common Information Model (CIM)-based automatic simulation model generation and dynamic voltage regulation simulation and further constructs a user-oriented intelligent simulation service layer. This layer is collaboratively composed of an Orchestration_Agent (simulation orchestration agent) and an Analysis_Agent (result analysis agent), tasked with three responsibilities: based on multi-level simulation granularity (L0–L3) and a simulation template library, leveraging a large language model (LLM) to achieve natural language requirements parsing and automatic workflow orchestration; based on a simulation knowledge graph, implementing parameter recommendation, verification, and anomaly-adaptive recovery for process control; and based on a hybrid architecture of rule templates, statistical analysis, and causal graph models, achieving automatic result analysis, root cause reasoning, and structured report generation, with case feedback driving knowledge base iteration. Validation was conducted on data from a real 10 kV feeder with 91 distribution transformer areas over 30 consecutive days (2880 time cross-sections): comprehensive requirements-parsing accuracy of 96.3%, automatic parameter configuration coverage rate of 94.7%, anomaly identification recall/precision of 94.0%/96.9%, root cause reasoning accuracy of 92.1%, and the median end-to-end time per simulation shortened from approximately 36 min under the manual mode to 4.7 min. The results demonstrate that the proposed service layer provides a viable engineering technology pathway for the evolution of distribution network simulation from tool-oriented to service-oriented. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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29 pages, 3803 KB  
Article
Exploiting the Flexibility and Frequency Support Capability of Grid-Forming Energy Storage: A Bi-Level Robust Planning Model Considering Uncertainties
by Yijia Yuan, Zheng Fan, Xirui Jiang, Yanan Wu and Chengbin Chi
Processes 2026, 14(1), 90; https://doi.org/10.3390/pr14010090 - 26 Dec 2025
Cited by 3 | Viewed by 902
Abstract
With the continuously rising penetration rate of variable renewable energy (VRE), issues related to power balance and frequency stability in power systems have become increasingly prominent. Battery energy storage systems (BESS) with grid-forming capabilities are regarded as an effective solution for providing rapid [...] Read more.
With the continuously rising penetration rate of variable renewable energy (VRE), issues related to power balance and frequency stability in power systems have become increasingly prominent. Battery energy storage systems (BESS) with grid-forming capabilities are regarded as an effective solution for providing rapid frequency support. However, the stochastic fluctuations of VRE output also lead to time-varying system inertia, which undoubtedly increases the complexity of energy storage planning. To address these problems, this study constructs a bi-level robust planning model for grid-forming energy storage considering frequency security constraints. First, a frequency response model for grid-forming BESS is established. By accurately describing the delay characteristics of different resources in frequency response, dynamic frequency security constraints (FSC) that can be embedded into the planning model are constructed. Subsequently, the study proposes an evaluation method for the spatial distribution of power system inertia, providing a basis for the optimal siting of BESS in the grid. On this basis, a bi-level robust planning model, considering VRE uncertainty, is constructed, which embeds an operational simulation model and incorporates FSC. To achieve an effective solution of the model, FSC is transformed into a second-order cone form, and a nested column-and-constraint generation (C&CG) algorithm is employed for solving. Simulation results on the modified NPCC-140 bus system verify the effectiveness of the proposed model. While reducing the total cost by 15.9%, this method effectively ensures the dynamic frequency security of the power system, improves the spatial distribution of inertia and significantly enhances the system’s ability to accommodate VRE. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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25 pages, 13051 KB  
Article
Intelligent Frequency Control for Hybrid Multi-Source Power Systems: A Stepwise Expert-Teaching PPO Approach
by Jianhong Jiang, Shishu Zhang, Jie Wang, Wenting Shen, Changkui Xue, Qiang Ye, Zhaoyang Lv, Minxing Xu and Shihong Miao
Processes 2025, 13(11), 3396; https://doi.org/10.3390/pr13113396 - 23 Oct 2025
Cited by 4 | Viewed by 1050
Abstract
This paper proposes a stepwise expert-teaching reinforcement learning framework for intelligent frequency control in hydro–thermal–wind–solar–compressed air energy storage (CAES) integrated systems under high renewable energy penetration. The proposed method addresses the frequency stability challenge in low-inertia, high-volatility power systems, particularly in Southwest China, [...] Read more.
This paper proposes a stepwise expert-teaching reinforcement learning framework for intelligent frequency control in hydro–thermal–wind–solar–compressed air energy storage (CAES) integrated systems under high renewable energy penetration. The proposed method addresses the frequency stability challenge in low-inertia, high-volatility power systems, particularly in Southwest China, where large-scale renewable-energy-based energy bases are rapidly emerging. A load frequency control (LFC) model is constructed to serve as the training and validation environment, reflecting the dynamic characteristics of the hybrid system. The stepwise expert-teaching PPO (SETP) framework introduces a stepwise training mechanism in which expert knowledge is embedded to guide the policy learning process and training parameters are dynamically adjusted based on observed performance. Comparative simulations under multiple disturbance scenarios are conducted on benchmark systems. Results show that the proposed method outperforms standard proximal policy optimization (PPO) and traditional PI control in both transient response and coordination performance. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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15 pages, 5596 KB  
Article
Constant Power Charging Control Method for Isolated Vehicle-to-Vehicle Energy Transfer Converter
by Litong Zheng, Haoran Zhang, Xiuyu Zhang and Hongwei Li
Processes 2025, 13(7), 1999; https://doi.org/10.3390/pr13071999 - 24 Jun 2025
Cited by 1 | Viewed by 1574
Abstract
With the proliferation of electric vehicles (EVs), vehicle-to-vehicle (V2V) energy transfer has emerged as a critical technology for dynamic energy complementarity. This technology addresses “range anxiety”, thereby supporting carbon neutrality goals through the enhanced utilization of renewable-powered EVs. In order to achieve fast, [...] Read more.
With the proliferation of electric vehicles (EVs), vehicle-to-vehicle (V2V) energy transfer has emerged as a critical technology for dynamic energy complementarity. This technology addresses “range anxiety”, thereby supporting carbon neutrality goals through the enhanced utilization of renewable-powered EVs. In order to achieve fast, safe V2V charging and improve device portability, it is necessary to optimize the charging mode and simplify the device. Therefore, this paper proposes a hierarchical control strategy for constant power (CP) charging in a V2V device with a dual-active-bridge (DAB) converter topology. First, different from traditional constant voltage (CV) and constant current (CC) charging, a unified nonlinear DAB model integrating CV/CP/CC charging modes is proposed. Furthermore, sensorless current estimation based on finite-time disturbance observers further reduced the size of the device. Finally, a hierarchical control architecture was constructed by combining backstepping control theory, which ensures global stability of multi-stage charging processes through the dynamic adjustment of phase-shift ratios. The effectiveness of the proposed methodology was validated through simulation and hardware-in-the-loop experimental results. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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28 pages, 6345 KB  
Article
Multimodal Switching Control Strategy for Wide Voltage Range Operation of Three-Phase Dual Active Bridge Converters
by Chenhao Zhao, Chuang Huang, Shaoxu Jiang and Rui Wang
Processes 2025, 13(6), 1921; https://doi.org/10.3390/pr13061921 - 17 Jun 2025
Cited by 2 | Viewed by 1288
Abstract
In recent years, to achieve “dual carbon” goals, increasing the penetration of renewable energy has become a critical approach in China’s power sector. Power electronic converters play a key role in integrating renewable energy into the power system. Among them, the Dual Active [...] Read more.
In recent years, to achieve “dual carbon” goals, increasing the penetration of renewable energy has become a critical approach in China’s power sector. Power electronic converters play a key role in integrating renewable energy into the power system. Among them, the Dual Active Bridge (DAB) DC-DC converter has gained widespread attention due to its merits, such as galvanic isolation, bidirectional power transfer, and soft switching. It has been extensively applied in microgrids, distributed generation, and electric vehicles. However, with the large-scale integration of stochastic renewable sources and uncertain loads into the grid, DAB converters are required to operate over a wider voltage regulation range and under more complex operating conditions. Conventional control strategies often fail to meet these demands due to their limited soft-switching range, restricted optimization capability, and slow dynamic response. To address these issues, this paper proposes a multi-mode switching optimized control strategy for the three-port DAB (3p-DAB) converter. The proposed method aims to broaden the soft-switching range and optimize the operation space, enabling high-power transfer capability while reducing switching and conduction losses. First, to address the issue of the narrow soft-switching range at medium and low power levels, a single-cycle interleaved phase-shift control mode is proposed. Under this control, the three-phase Dual Active Bridge can achieve zero-voltage switching and optimize the minimum current stress, thereby improving the operating efficiency of the converter. Then, in the face of the actual demand for wide voltage regulation of the converter, a standardized global unified minimum current stress optimization scheme based on the virtual phase-shift ratio is proposed. This scheme establishes a unified control structure and a standardized control table, reducing the complexity of the control structure design and the gain expression. Finally, both simulation and experimental results validate the effectiveness and superiority of the proposed multi-mode optimized control strategy. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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27 pages, 2165 KB  
Article
Load Frequency Control via Multi-Agent Reinforcement Learning and Consistency Model for Diverse Demand-Side Flexible Resources
by Guangzheng Yu, Xiangshuai Li, Tiantian Chen and Jing Liu
Processes 2025, 13(6), 1752; https://doi.org/10.3390/pr13061752 - 2 Jun 2025
Cited by 3 | Viewed by 2174
Abstract
With the high-proportion integration of renewable energy into the power grid, the fast-response capabilities of demand-side flexible resources (DSFRs), such as electric vehicles (EVs) and thermostatic loads, have become critical for frequency stability. However, the diverse dynamic characteristics of heterogeneous resources lead to [...] Read more.
With the high-proportion integration of renewable energy into the power grid, the fast-response capabilities of demand-side flexible resources (DSFRs), such as electric vehicles (EVs) and thermostatic loads, have become critical for frequency stability. However, the diverse dynamic characteristics of heterogeneous resources lead to high modeling complexity. Traditional reinforcement learning methods, which rely on neural networks to approximate value functions, often suffer from training instability and lack the effective quantification of resource regulation costs. To address these challenges, this paper proposes a multi-agent reinforcement learning frequency control method based on a Consistency Model (CM). This model incorporates power, energy, and first-order inertia characteristics to uniformly characterize the response delays and dynamic behaviors of EVs and air conditioners (ACs), providing a reduced-order analytical foundation for large-scale coordinated control. On this basis, a policy gradient controller is designed. By using projected gradient descent, it ensures that control actions satisfy physical boundaries. A reward function including state deviation penalties and regulation costs is constructed, dynamically adjusting penalty factors according to resource states to achieve priority configuration for frequency regulation. Simulations on the IEEE 39-node system demonstrate that the proposed method significantly outperforms traditional approaches in terms of frequency deviation, algorithm training efficiency, and frequency regulation economy. Full article
(This article belongs to the Special Issue Energy Storage Planning, Control, and Dispatch for Grid Dynamic Enhancement)
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