Intelligent Hybrid Methods for Renewable Energy Power System Optimization
A Special Issue of Processes (ISSN 2227-9717) belonging to the section "Energy Systems".
Deadline for manuscript submissions: 31 May 2027 | Viewed by 16
Editors
Interests: intelligent hybrid methods; AI-assisted control; uncertainty modeling; smart grid resilience
Interests: new-type energy storage; emerging energy storage technologies; advanced energy storage; renewable energy grid integration control; grid-connected control of renewable energy
Special Issue Information
Dear Colleagues,
The rapid integration of variable renewable energy sources (VRES), such as wind and solar, poses significant operational challenges for modern power systems due to inherent volatility, high dimensionality, and multi-scale temporal dynamics. Traditional optimization frameworks often struggle with the computational complexity and non-linearities of these decarbonized grids. This Special Issue focuses on advanced intelligent hybrid methods—combining physics-informed models, mathematical programming (e.g., robust, stochastic, and dynamic programming), and data-driven intelligence (e.g., machine learning and reinforcement learning)—to address critical planning, operational, and control challenges. We invite original research and review articles exploring synergistic computational frameworks that enhance grid resilience, flexibility, line loss reduction, and asset allocation under uncertainty.
Topics include, but are not limited to, the following:
- AI-assisted optimization and control;
- Hybrid machine learning and mathematical programming;
- Data-driven uncertainty modeling and scenario generation;
- Renewable power predictions;
- Planning, operations, and control of renewable energy power systems;
- Smart grid operational resilience and flexibility.
Dr. Zhongjie Guo
Prof. Dr. Xiaotao Chen
Prof. Dr. Yang Si
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
- intelligent hybrid methods
- physics-informed learning
- data-driven optimization
- reinforcement learning
- mathematical programming
- AI-assisted control
- uncertainty modeling
- smart grid resilience
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
