Advances in the Modeling, Optimization and Control of Renewable Energy Systems
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 1243
Special Issue Editors
Interests: renewable energy systems modeling and control; solar energy; wind energy; marine energy
Interests: modeling and control of wave energy converters; grid integration for wave energy; energy management systems for wave energy; wave energy assessment
Special Issue Information
Dear Colleagues,
As the world is swiftly shifting towards a more diversified energy paradigm, renewable energy systems are becoming prevalent both technologically and economically. Accurate modeling of such complex, nonlinear, and often heterogenous systems offers a cost-effective method to better understand systems’ behaviors, predict their performance, and optimize operation and component selection well before the real-world implementation of such systems. Moreover, accurate and reliable models will help in designing effective control strategies that maximize energy capture, minimize conversion losses, and ensure system stability and coordination, eventually enhancing the economic feasibility of the system. This Special Issue, entitled ‘Advances in the Modeling, Optimization and Control of Renewable Energy Systems’, aims to demonstrate the most recent developments in the field of modeling and controlling renewable energy systems, which encompasses analytical physics-based, data-driven, and artificial intelligence-based methodologies. Furthermore, in this Special Issue, we aspire to provide a platform for disseminating cutting-edge research on the modeling and control of renewable energy systems not only restricted to electric energy generation, but also other alternative forms of renewable energy (e.g., chemical, thermal, mechanical, etc.) and conversion from one form to another (e.g., P2X and X2P). We cordially invite scientists, researchers, and engineers to contribute to this Special Issue, whether through theoretical study, computer simulations, or experimental implementation.
Topics of interest include, but not limited to, the following:
- Solar energy (PV and thermal);
- Wind energy;
- Marine energy (tidal, wave, SGE, and OTEC);
- Thermal energy;
- Bioenergy (biomass, biofuels, etc.);
- Energy storage (electrochemical, mechanical, chemical, thermal, etc.);
- Hybrid renewable energy systems.
Dr. Mohammed Jama
Dr. Addy Wahyudie
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 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. Processes is an international peer-reviewed open access monthly 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
- renewable energy
- modeling and simulation
- control systems
- energy systems
- energy
- artificial intelligence
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