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Integration of Energy Storage Technologies into Smart Grids and Modern Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: 30 January 2026 | Viewed by 1826

Special Issue Editor


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Guest Editor
Department of Electrical Engineering, University of Doha for Science and Technology, Doha, Qatar
Interests: power and energy systems; renewable and sustainable energy; applications of artificial intelligence in power and energy systems; energy policy and economics

Special Issue Information

Dear Colleagues,

The increasing demand for sustainable and resilient power and energy systems is accelerating the transformation of power infrastructure. Central to this evolution is the integration of energy storage technologies into smart grids and modern power distribution systems. These advancements not only facilitate the reliable incorporation of intermittent renewable energy sources but also enable enhanced grid stability, load balancing, and energy management.

As the energy sector transitions away from traditional, centralized power generation models, energy storage systems (ESSs) have emerged as essential enablers of a flexible, decentralized, and intelligent power grid. From battery storage and pumped hydro to advanced thermal and mechanical solutions, these technologies offer the capacity to store excess energy during periods of low demand and release it in the face of peak loads—ensuring grid reliability and efficiency.

Moreover, the integration of ESSs plays a critical role in supporting the rise of prosumers, electric vehicles, demand response programs, and microgrids. However, realizing the full potential of these systems presents a host of technical, regulatory, and economic challenges. Key concerns include optimizing storage deployment, enhancing real-time control algorithms, designing cost-effective business models, and developing supportive regulatory frameworks.

This Special Issue seeks original research, review articles, and practical case studies that delve into the multifaceted applications of energy storage in smart grids and power distribution networks. Contributions are encouraged on topics such as system modelling and simulation, storage control strategies, grid integration approaches, economic and policy analysis, and the role of storage in enhancing grid resilience and sustainability. 

Dr. Ahmed Awad
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 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. 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

  • energy storage systems
  • smart grids
  • sustainable energy
  • grid stability and resilience

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Published Papers (1 paper)

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Review

19 pages, 520 KB  
Review
Physics-Informed Neural Networks in Grid-Connected Inverters: A Review
by Ekram Al Mahdouri, Said Al-Abri, Hassan Yousef, Ibrahim Al-Naimi and Hussein Obeid
Energies 2025, 18(20), 5441; https://doi.org/10.3390/en18205441 - 15 Oct 2025
Viewed by 1632
Abstract
Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for modeling and controlling complex energy systems by embedding physical laws into deep learning architectures. This review paper highlights the application of PINNs in grid-connected inverter systems (GCISs), categorizing them by key tasks: [...] Read more.
Physics-Informed Neural Networks (PINNs) have emerged as a powerful tool for modeling and controlling complex energy systems by embedding physical laws into deep learning architectures. This review paper highlights the application of PINNs in grid-connected inverter systems (GCISs), categorizing them by key tasks: parameter estimation, state estimation, control strategies, fault diagnosis and detection, and system identification. Particular focus is given to the use of PINNs in enabling accurate parameter estimation for aging and degradation monitoring. Studies show that PINN-based approaches can outperform purely data-driven models and traditional methods in both computational efficiency and accuracy. However, challenges remain, mainly related to high training costs and limited uncertainty quantification. To address these, emerging strategies such as advanced PINN frameworks are explored. The paper also explores emerging solutions and outlines future research directions to support the integration of PINNs into practical inverter design and operation. Full article
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