Application of Operations Research and Data Science in Sustainable Energy and its Global Relevance

In recent years, the field of sustainable energy has garnered significant attention from scholars, policymakers, and industry practitioners. This focus is driven by the urgent need to address global energy challenges and the increasing demand for sustainable practices. A critical issue in this domain is the perceived separation between flexibility in meeting customer demands and sustainability goals. Traditionally, these aspects have been treated as distinct, with limited exploration of their interconnection. Recent studies have highlighted the potential of data science, which combines data inference, algorithm development, and technology, to tackle complex analytical problems in this area. Operations research (OR) and data science have emerged as powerful tools in promoting energy sustainability across various industries, offering strategic insights and guidance to decision-makers. However, there remains a gap in fully understanding and leveraging the synergy between flexibility and sustainability, necessitating further investigation into their integration.

This research topic aims to explore the application of operations research and data science in achieving sustainable energy goals and enhancing their global relevance. The primary objectives include demonstrating the effectiveness of OR and data science methodologies in promoting sustainable energy, presenting strategies to emphasize the importance of sustainable energy in global discussions, and showcasing the practical implementation of these techniques across diverse industries. By addressing these objectives, the research seeks to bridge the gap between flexibility and sustainability, providing a comprehensive understanding of their interconnectedness.

To gather further insights in the integration of operations research and data science with sustainable energy practices, we welcome articles addressing, but not limited to, the following themes:

• The role of data science in enhancing energy efficiency and sustainability
• Case studies on the successful implementation of OR techniques in sustainable energy projects
• Strategies for integrating flexibility and sustainability in energy systems
• The impact of sustainable energy practices on global economic and environmental policies
• Innovative algorithmic approaches to optimize energy resource management
• Challenges and opportunities in the adoption of sustainable energy technologies across industries.

Keywords: Renewable Energy, Data science, Multi-Criteria Decision Analysis, Fuzzy numbers, Carbon Emissions Reduction, Optimization

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.