Intelligent Energy Management Systems for Smart Grids: Algorithms, Optimization, and Control
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 January 2025 | Viewed by 2684
Special Issue Editor
Interests: esilient smart energy grid and micro-energy grid planning, control, and protection; advanced plasma generation and applications in fusion energy; advanced safety and control systems for nuclear power plants; safety engineering, fault diagnosis, and real-time simulation; risk-based energy conservation; smart green buildings; process systems engineering of the energy and nuclear facilities and oil and gas production plants
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleague,
This Special Issue will present the latest research methods, system developments, and technologies relating to intelligent energy management systems and their implementations within smart grids and community applications. Topics of interest include, but are not limited to, the following:
- Applied AI techniques for smart energy systems;
- Hybrid energy systems’ design, modelling, simulation, control, integration, planning, and management;
- Applied AI for energy policies;
- Hydrogen process technologies and infrastructure;
- Carbon capturing and storage technologies;
- Applied quantum AI and quantum energy;
- Intelligent energy management systems;
- Smart energy–water systems;
- Smart energy for clean transportation;
- Smart waste-to-energy process technologies;
- Interconnected infrastructure;
- Smart electronics.
Contributions from researchers, students, and professionals are welcomed to facilitate the discussion on state-of-the-art research and developments in these areas and to reflect potential implementations and projects in urban, remote, and waterfront communities, as well as industrial applications.
Prof. Dr. Hossam A. Gaber
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
- smart energy
- energy management system
- applied AI
- hybrid energy systems
- quantum energy
- smart grid
- hydrogen process technologies
- energy–water
- clean transportation
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Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Renewable Energy Infrastructures and Management Systems for All-electric Ship Operations
Authors: Jose Guizar, Larry E. Erickson, Jennifer Anthony, John Schlup
Affiliation: Kansas State University
Abstract: There is a need to reduce greenhouse gas emissions and air pollution associated with ships. The transition to all-electric ships is moving forward for short distances; however, there is a need for efficient battery charging and swapping to have sufficient energy for long trips. There is a need to provide a review of the literature and a global plan for development of infrastructure and a management plan to provide the needed energy for the transition to all-electric ship operations. The goal of this manuscript is to make a positive contribution toward having an infrastructure and management system for all-electric ship operations in the future.
Title: Deep Learning-Driven System Dynamics for Intelligent Energy Management in Smart Grids: Modeling, Control, and Optimization
Authors: Jose Gonzalez de Durana; Luis Rabelo; Alfonso Sarmiento; Esteban Lopez; Marwen Elkamel; Edgar Gutierrez
Affiliation: University of the Basque Country
University of Central Florida
Universidad de La Sabana
Massachusetts Institute of Technology
Abstract: The growing complexity of modern power grids, driven by the integration of renewable energy sources and the need for efficient energy management, demands innovative approaches to modeling and optimization. This special issue explores advanced techniques for intelligent energy management in smart grids, with a focus on system dynamics and deep learning. By leveraging deep learning algorithms, we aim to enhance the optimization and control of energy distribution, demand-side management, and grid stability. System dynamics provides a comprehensive framework for simulating the behavior of complex energy systems, allowing for the accurate modeling of power flows, load management, and the integration of distributed energy resources. Topics covered include system dynamics for DC and AC distribution networks, the role of deep learning in predictive analytics for grid operations, and the optimization of energy storage and distribution through real-time control systems.
