Artificial Intelligence and Model Predictive Control for Renewable Energy
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Energy Systems".
Deadline for manuscript submissions: closed (31 January 2024) | Viewed by 9864
Special Issue Editors
Interests: multiphase flow; population balance modelling; machine Learning; Digital Twin; particle dynamics; high performance computing
Special Issues, Collections and Topics in MDPI journals
Interests: artificial intelligence; smart energy; chemical kinetics; model predictive control
Interests: numerical simulation of deep water geo-environment; geotechnical modeling in offshore geotechnical engineering; physics-informed neural network method in energy engineering
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Over the last several decades, the countries worldwide have devoted enormous efforts to developing renewable energies in line with the targets of the Paris Agreement and Sustainable Development Goals. Renewable energy is produced using natural resources that are abundant and able to be constantly renewed, including the sun, wind, water and trees. It can offer substantial cost savings compared with grid-supplied energy and enables businesses to reduce emissions, enhance sustainability credentials and reduce exposure to future price volatility. Unfortunately, the renewable industry suffers a poor yield and high cost. There is a lack of highly efficient production and conversion devices for the renewable fuels. The reaction mechanisms for the renewable fuels are far from being fully understood, to which model and simulation could contribute significantly. Among various modelling techniques, Artificial Intelligence (AI) is the most promising one. AI on everyone's lips right now. It is the fastest growing branch of the high-tech industry and has gained relevance in a wide variety of sectors including material synthesis, medical science, auto pilot as well as energy system design. It has a great potential for the future design of the energy system. Typical areas of application are renewable fuel mechanism construction, highly efficient system design, smart grid or the sector coupling of electricity, heat and transport. Prerequisites for an increased use of AI in the energy system are the digitalization of the energy sector and a correspondingly large set of data that is evaluable. AI helps make the energy industry more efficient and secure by analyzing and evaluating the data volumes.
This special issue will focus on publishing original research works about AI for Renewable Energy. We target specifically the development of novel AI algorithms and their applications in renewable energy industries, incluidng new energy system, energy materials, energy conversion devices and energy chemistry. It also welcomes the review papers covering the state-of-the-art developments of AI technologies for renewable energy system modelling and optimization.
Topics of interest for this Special Issue include but are not limited to:
- AI for renewable fuel synthesis
- Data-driven modelling of renewable energy device
- Advanced optimization technique for energy system
- Model predictive control of energy system
- Hybrid AI and physical model for renewable energy related problems
- Internet of things and digital twining technologies for renewable energy systems
- Data science in renewable energy
- Environmental impact assessment based on big data technique
Dr. Shaohua Wu
Dr. Han Xu
Dr. Xiang Sun
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
- artificial intelligence
- optimization
- model predictive control
- fuel synthesis
- data-driven modelling technique
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