Jaroslaw Mark Krzywanski ^1* Dr. Muhammad Farooq ^2* Yunfei Gao ³ Karol Sztekler ⁴ Anna Zylka ¹ Marcin Dyner ¹ Marcin Sosnowski ¹ Tomasz Czakiert ⁵ Mose Rossi ⁶ Marcio L. de Souza-Santos ⁷

• ¹ Jan Długosz University, Częstochowa, Poland
• ² Prince Mohammad bin Fahd University, Khobar, Saudi Arabia
• ³ East China University of Science and Technology, Shanghai, Shanghai, China
• ⁴ AGH University of Science and Technology, Kraków, Lesser Poland, Poland
• ⁵ Częstochowa University of Technology, Częstochowa, Poland
• ⁶ Marche Polytechnic University, Ancona, Marche, Italy
• ⁷ State University of Campinas, Campinas, São Paulo, Brazil

2023) makes a significant methodological contribution by presenting a comprehensive framework for uncertainty quantification in the Techno-Economic Analysis (TEA) of carbon capture technologies. Using CO2 mineralization in cement production as a detailed case study, they demonstrate the limitations of traditional local sensitivity analyses and provide structured guidance for selecting appropriate analytical methods. Their work is particularly relevant for decision-makers evaluating carbon capture technologies to achieve net-zero emissions by 2050 (Bergero et Finally, the research establishes optimal parameters for viscosity reducer concentrations and characterizes emulsion behavior under various operating conditions.In a related development focusing on renewable energy integration, Xu et al. (2024) address the optimization of hydrogen energy storage in Integrated Energy Systems (IESs) centered on water electrolysis technology. The study evaluates optimal hydrogen storage capacity using a data-driven DOuble-layer Mixed Integer Nonlinear Optimization (DOMINO) algorithm by developing a two-layer optimization model. The research explicitly targets the problem of wind and solar curtailment in new energy development, proposing hydrogen storage as an effective solution within comprehensive energy architectures. The study validates algorithm convergence through simulation analysis and determines optimal hydrogen capacity configuration, contributing to enhanced renewable integration."The discussed studies employ sophisticated computational tools and simulation methods, including MATLAB-based implementations, computational fluid dynamics, and artificial intelligence algorithms. These tools enable complex system modeling and optimization under various operational conditions. Future developments in this field will likely focus on enhanced integration of renewable energy sources, improved grid stability mechanisms, and more sophisticated uncertainty quantification methods. Integrating these technological advances points toward a future where energy systems are increasingly efficient, resilient, and environmentally sustainable. Emerging trends suggest continued development in areas such as:• Advanced control algorithms for complex grid systems;• Enhanced integration of renewable energy sources;• Improved methods for uncertainty quantification in system design;• More sophisticated approaches to resource extraction and utilization. The collected works demonstrate significant progress in addressing contemporary energy challenges through innovative engineering solutions. Integrating advanced modeling techniques, control strategies, and optimization methods provides a robust foundation for future developments in energy systems engineering. These contributions are precious as the global energy sector transitions toward more sustainable and efficient operations. This editorial offers a comprehensive overview of current research while highlighting the interconnected nature of various energy engineering disciplines. The findings and methodologies presented provide valuable insights for researchers, practitioners, and policy-makers working toward more sustainable and efficient energy systems.