Intelligent Modeling and Optimization of Energy Systems and Industrial Processes

Dear Colleagues,

In recent years, energy systems and industrial processes have undergone significant transformation driven by increasing demands for energy efficiency, environmental sustainability, operational reliability, and economic competitiveness. This development is closely associated with rapid advances in computational methods, the growing availability of large-scale data sources, the evolution of sensing and monitoring technologies, and the widespread adoption of digitalization, Industry 4.0 concepts, and artificial intelligence.

Modern energy and industrial systems generate vast amounts of data that enable the development of more accurate process models, more effective operational monitoring, and the implementation of advanced optimization and control strategies. In this context, particular attention has been devoted to hybrid modeling approaches that combine first-principles knowledge with machine learning techniques, digital twins, advanced predictive methods, intelligent diagnostic systems, and algorithms that support autonomous real-time decision-making.

The aim of this Special Issue is to present the latest scientific advances, methodological developments, and practical applications in the fields of intelligent modeling, monitoring, optimization, and control of energy systems and industrial processes. Particular emphasis will be placed on interdisciplinary contributions that bridge theoretical foundations and real-world industrial applications. We welcome submissions addressing physics-based, data-driven, and hybrid modeling approaches; advanced optimization techniques; adaptive and predictive control systems; digital twins; fault diagnosis and detection; and artificial intelligence and machine learning applications in energy and industrial domains.

Topics of particular interest also include solutions to reduce process energy consumption, minimize greenhouse gas emissions, improve the utilization of renewable energy resources, integrate energy markets with industrial demand, and enhance system resilience to faults, uncertainties, and extreme operating conditions. Equally important are issues related to data quality, data preprocessing, model validation, and the objective assessment of proposed solutions through appropriate performance metrics and evaluation methodologies.

We invite original research articles, review papers, technical studies, and industrial case studies that make novel scientific contributions and demonstrate practical benefits in energy efficiency, sustainability, safety, and economic feasibility. We believe that the contributions published in this Special Issue will support the continued advancement of intelligent technologies and accelerate the transition toward more efficient, cleaner, and more resilient energy and industrial systems.

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

• Intelligent modeling of energy systems and industrial processes;
• Data-driven and hybrid modeling approaches;
• Machine learning and artificial intelligence applications;
• Digital twins and virtual process representations;
• Process monitoring and condition monitoring systems;
• Advanced process control and optimization;
• Model predictive control and adaptive control systems;
• Soft sensors and indirect measurement techniques;
• Fault detection, diagnosis, and predictive maintenance;
• Industrial process simulation and optimization;
• Energy management and energy efficiency improvement;
• Optimization of industrial energy consumption;
• Renewable energy systems and their integration;
• Smart grids and intelligent energy networks;
• Multi-objective and robust optimization methods;
• Uncertainty quantification and decision support systems;
• Industrial Internet of Things (IIoT) applications;
• Big data analytics and industrial informatics;
• Sustainable and low-carbon industrial technologies;
• Decarbonization strategies for industrial processes;
• Integration of energy markets and industrial consumers;
• Cyber-physical systems in energy and industry;
• Resource efficiency and circular economy approaches;
• Case studies and industrial applications of intelligent systems.

Prof. Dr. Marek Laciak
Dr. Patrik Flegner
Dr. Ján Kačur
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.