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

Over the past few years, there has been a growing focus on energy sustainability among scholars, policymakers, and practitioners. In the realm of practical competition, companies must also uphold flexibility in meeting customer demands. The prevailing theory has predominantly regarded flexibility and sustainability as distinct matters, disregarding their interconnection. Data science encompasses a combination of data inference, algorithm development, and technology to address analytically complex problems. Integrating sustainability is an indispensable asset for any manufacturing enterprise. It empowers a business to establish a unique identity in the market and engage in competitive operations with the utmost efficiency and effectiveness. Operations research and Data science methods have facilitated the utilization and implementation of energy sustainability in different industries worldwide, providing valuable guidance to Decision Makers (DMs).

1. Demonstrate the efficacy of employing OR and data science methodologies to achieve sustainable energy goals.

2. Present strategies for conveying the significance of implementing sustainable energy in global discourse.

3. Showcase how OR and data science techniques are utilized to implement sustainable energy practices within diverse industries.

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

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