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Global Optimization of Energy Processes

This special issue belongs to the section “F4: Critical Energy Infrastructure“.

Special Issue Information

Dear Colleagues,

Energy processes are pivotal to global sustainable development, facing the dual challenge of enhancing efficiency while reducing environmental impact. Global optimization transcends the limits of local search, offering a powerful paradigm for maximizing energy savings and emission reductions across complex, integrated systems.

This Special Issue, titled “Global Optimization of Energy Processes”, aims to showcase the latest research and innovative applications in this critical field. We invite contributions that address both theoretical advances and practical implementations, with a particular interest in global optimization integrated with discrete, coupling, and parallel principles. These approaches encompass the decomposition of complex systems, the management of intercomponent couplings, and the deployment of parallel computation to achieve superior, system-wide solutions.

Topics of interest include, but are not limited to, the following:

  • Novel global optimization algorithms (deterministic, heuristic, and hybrid) tailored for large-scale energy systems.
  • Optimization under uncertainty for robust design and operation of renewable-integrated grids and multi-energy networks.
  • Data-driven and AI-enhanced global optimization, integrating machine learning, digital twins, and mechanistic models.
  • Process integration, synthesis, and scheduling for energy-intensive industries (e.g., chemical, petrochemical, metallurgical).
  • Sustainable process design for energy-saving separation, CO2 capture/conversion, and life-cycle assessment.
  • Supply chain optimization for energy and resource systems, supporting circular economy transitions.
  • Multi-scale applications, from unit operation and plant-wide optimization to regional energy supply chain and integrated energy system management.

We encourage submissions that demonstrate tangible industrial impact, evidenced by case studies in traditional fossil-based systems, renewable energy hubs, and multi-energy complementary systems. The Special Issue seeks to bridge academia and industry, providing a platform to disseminate cutting-edge strategies that contribute to greener, smarter, and more resilient global energy infrastructure.

Prof. Dr. Xin Xiao
Prof. Dr. Jie Li
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-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

  • global optimization algorithms
  • optimization under uncertainty
  • data-driven optimization
  • process integration and synthesis
  • energy scheduling
  • energy supply chain
  • integrated energy system
  • energy conservation and management
  • industrial artificial intelligence
  • sustainable process design
  • CO2 capture and conversion

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Energies - ISSN 1996-1073