Designing Autonomous Carbon Reduction Mechanisms: A Data-Driven Approach in Renewable Energy Systems

Authors

  • Khorshed Alam Masters in Industrial Engineering, Industrial and Systems Engineering, College of Engineering, Lamar University, Beaumont, TX, 77710, USA
  • M S Hossen Masters in Industrial Engineering, Industrial and Systems Engineering, College of Engineering, Lamar University, Beaumont, TX, 77710, USA
  • Md Al Imran Masters in Electrical Engineering, Phillip M. Drayer Department of Electrical Engineering, College of Engineering, Lamar University, Beaumont, TX, 77710, USA
  • Upal Mahmud Project Manager, Engineering & Site Services, Imperious Engineering, Mohakhali, Dhaka, 1216, Bangladesh
  • Abdullah Al Fathah Area Sales Manager, Sales, Ingersoll Rand Industrial Company B.V., UTC Tower, Panthapath, Dhaka, 1215, Bangladesh
  • Md Ali Mostakim Technical Account Manager, Cement Dept., Maple Leaf International. Banani, Dhaka, 1213, Bangladesh

Keywords:

Renewable Energy, Carbon Emission Efficiency, Machine Learning, Data Analysis, Simulation Models

Abstract

The study examines the effects of renewable energy deployment on carbon emission efficiency and aims at establishing the efficient integration thresholds level. The study employs statistical artificial intelligence simulation models based on the comprehensive energy production and consumption data set from different geographical locations. The results also show that China's carbon emission efficiency varies by region, with coastal regions being more efficient than the northwest areas. The research revealed the importance of policy-specific and sector-focused support schemes and investment in renewable energy technologies. Besides, it focuses on the role of the public in promoting and supporting the new culture regarding sustainable energy usage. Therefore, the study is useful for policymakers and stakeholders who want to increase carbon emission efficiency and meet the national carbon neutrality targets.

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Published

20-11-2023

How to Cite

Alam, K., Hossen, M. S., Imran, M. A., Mahmud, U., Fathah, A. A., & Mostakim, M. A. (2023). Designing Autonomous Carbon Reduction Mechanisms: A Data-Driven Approach in Renewable Energy Systems. Well Testing Journal, 32(2), 103–129. Retrieved from https://welltestingjournal.com/index.php/WT/article/view/117

Issue

Vol. 32 No. 2 (2023)

Section

Research Articles

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