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Modeling and Optimization of Power Grid

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

Deadline for manuscript submissions: 31 August 2026 | Viewed by 672

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Department of Electrical and Computer Engineering, Jeju National University, 102 Jejudaehak-ro, Jeju 63243, Republic of Korea
Interests: peer-to-peer transaction; distributed system operation; distributed renewables; virtual power plant; energy trading
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Special Issue Information

Dear Colleagues,

Reshaping the grid into digitalized and decentralized networks is essential for carbon neutrality and renewable energy integration. This structural evolution involves moving away from traditional centralized power grids toward highly interconnected systems with bidirectional energy flows. As this transformation progresses, however, the resulting complexity poses significant challenges to traditional operational paradigms in ensuring stability, reliability and economic efficiency. Furthermore, the digitalization of the grid, while providing better visibility, introduces new interdependencies between communication layers and physical infrastructure, necessitating more robust cyber–physical security measures. To address these issues, advanced modeling and optimization techniques have become more critical than ever.

This Special Issue aims to gather innovative research articles and comprehensive reviews that tackle the multifaceted problems of next-generation power grids, particularly focusing on advanced methodologies for modeling large-scale power grids, addressing DER-related uncertainties, and enhancing the operational efficiency of microgrids and smart systems. Topics to be covered in this Special Issue include, but are not limited to, the following:

  • Advanced Power System Modeling and Planning
  • Optimization of Smart Grids and Microgrids
  • Renewable Energy Integration and Uncertainty Management
  • Optimal Sizing and Scheduling of Energy Storage Systems (ESS)
  • Demand Response and Load Management
  • Grid Resilience and Reliability Analysis
  • AI and Machine Learning for Power Systems
  • Cyber–Physical Energy Systems

Dr. Young Gyu Jin
Guest Editor

Manuscript Submission Information

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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

  • power system modeling
  • grid optimization and planning
  • smart grid and microgrids
  • renewable energy integration
  • energy storage systems (ESS)
  • demand response and load management
  • grid resilience and reliability analysis
  • AI and machine learning for power systems
  • cyber–physical energy systems

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Published Papers (1 paper)

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Research

23 pages, 2548 KB  
Article
Energy Sustainability in the Usumacinta River: An Energy Management System for a Microgrid in Boca del Cerro, Tabasco
by David Abraham Uribe Sosa, Víctor Manuel Ramírez Rivera, Víctor Darío Cuervo Pinto and Diego Langarica Córdoba
Energies 2026, 19(10), 2390; https://doi.org/10.3390/en19102390 - 15 May 2026
Viewed by 431
Abstract
The growing energy demand in rural areas such as the ejido Boca del Cerro, located in Tenosique, Tabasco (Mexico), near the Usumacinta River, calls for sustainable energy solutions such as microgrids. This study proposes an energy management system combining renewable energy forecasting and [...] Read more.
The growing energy demand in rural areas such as the ejido Boca del Cerro, located in Tenosique, Tabasco (Mexico), near the Usumacinta River, calls for sustainable energy solutions such as microgrids. This study proposes an energy management system combining renewable energy forecasting and fuzzy control for a simulated small autonomous rural microgrid scenario designed to supply a fixed priority load of 5 kW and a variable flexible load ranging from 1 to 10 kW. Three LSTM architectures (vanilla, stacked, and bidirectional) are compared for predicting solar irradiance, wind speed, and river flow. The vanilla model is optimized using Hyperband to improve prediction accuracy, particularly for flow rate, which is rarely addressed in similar studies. Forecasts feed into models of photovoltaic, wind, and hydro systems within the microgrid. Energy dispatch is managed through fuzzy logic control. The fuzzy controller supports load prioritization, battery charge/discharge management, and surplus energy redirection to an absorbing load. The final vanilla LSTM achieved RMSE values of 25.741, 0.302, and 12.644 for solar irradiance, wind speed, and river flow, respectively, with NSE values above 0.949 in all cases. These results indicate high forecasting accuracy for solar irradiance and river flow, with limited improvement for wind speed. Overall, the proposed EMS enables effective energy flow management, while the integration of hydrokinetic turbines with AI-based forecasting represents a novel contribution. Full article
(This article belongs to the Special Issue Modeling and Optimization of Power Grid)
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