Special Issue "Technologies and Policies for Decarbonization of Energy Sector"

Dear Colleagues,

Decarbonization in modern energy systems is a critical to reducing global greenhouse gas emissions and thus mitigating climate change.  Therefore, governments around the world have implemented substantial decarbonization actions and have announced targets and plans that aim to achieve carbon neutrality.  Digital technologies such as big data, machine learning, blockchain and the Internet of Things are currently receiving extensive attention because they contribute to the decarbonization process.  The information system provides a model for these innovative technologies to work together, and further enhances the efficiency of the energy supply in order to optimize economic viability and environmental impact.  This Special Issue aims to provide a platform on which to discuss the latest advances in this area and exchange ideas regarding the implementatin of technologies and policies that may aid in the decarbonization of the energy sector.

The Special Issue welcomes submissions that attend to topics that include, but are not limited to, the following:

• applications of data-driven methods in the technical, economic, and environmental modeling of the decarbonization of the energy sector;
• development of computational and data-driven methods for applying them in the decarbonization of the energy sector;
• performance comparison of various optimization or data-driven approaches in the modeling of the decarbonization of the energy sector;
• recently developed optimization approaches that are based on computational methods and artificial intelligence, and are applicable in the decarbonization of the energy sector;
• artificial intelligence-assisted or data-driven diagnostics for the decarbonization of the energy sector;
• utilization of artificial intelligence for predicting the performance and output of the decarbonization of the energy sector;
• performance analysis for renewable energies;
• renewable energy, wind, solar, fuel cells, and distributed generation within the decarbonization of the energy sector;
• artificial intelligence for the optimization of the industrial process;
• optimization of industrial applications and energy systems;
• modelling, simulation, and data management;
• filtering algorithms and their application in the decarbonization of the energy sector.

Dr. Ming-Chung Chang
Dr. Xiang Chen
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. 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 2200 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.

• decarbonization
• optimization approaches
• DEA
• machine learning
• data-driven methods
• renewable energy policy
• state estimation