Process Integration and Optimization for Efficient and Low-Carbon Energy Systems

The increasing integration of renewable energy technologies, energy storage solutions, sustainable materials, and industrial decarbonization pathways creates new challenges for system design, operation, monitoring, and assessment. At the same time, developments in advanced modeling, simulation, optimization, machine learning, digital tools, and life-cycle assessment provide new opportunities to evaluate and improve the technical, economic, and environmental performance of complex systems. Within this context, process and energy systems engineering plays a central role in developing decision-support methods that can address uncertainty, efficiency, reliability, circularity, and emissions reduction across multiple scales and applications.Process integration and optimization provide a framework for coordinating energy, material, and process flows across interconnected technologies and operating stages. Advanced optimization methods can help identify efficient system configurations and manage trade-offs among energy use, emissions, cost, reliability, and resource use. This Research Topic focuses on these methods and their application to efficient and low-carbon process and energy systems.Goal:This Research Topic addresses the need for integrated modeling, optimization, and sustainability assessment methods for the design of efficient, reliable, and low-carbon process and energy systems. While significant progress has been made in renewable energy technologies, energy storage, industrial decarbonization, and circular resource use, many approaches remain fragmented, separately considering technical performance, economic feasibility, environmental impacts, and operational uncertainty. This limits evidence-based decision-making across the full life cycle of technologies and processes.To tackle this challenge, this Research Topic will promote submissions that integrate data-driven modeling, physics-informed machine learning, multi-objective optimization, life-cycle assessment, and decision-support frameworks. These approaches will facilitate researchers and practitioners to better balance trade-offs between energy efficiency, emissions reduction, cost, reliability, circularity, and resource use. The overall aim is to enable more informed, transparent, and sustainable decision-making for process and energy systems.Scope and information for AuthorsThis Research Topic welcomes methodological and applied contributions on process integration and advanced optimization for efficient and low-carbon process and energy systems. Contributions may address renewable energy integration, energy storage, industrial processes, and decarbonization pathways, supported where relevant by data-driven modeling, uncertainty analysis, life-cycle assessment, or techno-economic analysis.Topics of interest include, but are not limited to:• Process integration and superstructure optimization for renewable energy systems, energy storage, industrial processes, and energy conversion technologies• Multi-objective, multi-scale, and uncertainty-aware optimization under technical, economic, environmental, and operational constraints• Integrated design and operation of flexible, resilient, and low-carbon process and energy systems• Data-driven, physics-informed, and hybrid modeling approaches for process integration and system optimization• Life-cycle and techno-economic assessment methods supporting technology selection, process design, and system optimization• Digital tools and decision-support frameworks for improving energy efficiency, resource utilization, and emissions reductionWe welcome Original Research, Review, Mini Review, Technology and Code, and Brief Research Report articles that provide methodological advances, applied case studies, decision-support frameworks, or critical syntheses relevant to efficient and low-carbon process and energy systems. Topic editors: Chrysa Politi, Francesco Crespi Source: https://www.frontiersin.org/research-topics/84045/process-integration-and-optimization-for-efficient-and-low-carbon-energy-systems