Abstract :

The Increasing Demand For Electricity, Rapid Industrialization, And The Global Commitment To Reducing Greenhouse Gas Emissions Have Intensified The Need For Sustainable Power System Management. Traditional Power Systems Often Face Challenges Related To Carbon Emissions, Inefficient Energy Utilization, And The Integration Of Renewable Energy Resources. Artificial Intelligence (AI) Has Emerged As A Transformative Technology Capable Of Enhancing Power System Sustainability Through Intelligent Carbon Management Strategies. This Study Explores The Application Of AI-enabled Carbon Management Techniques For Optimizing Power System Sustainability. Machine Learning, Deep Learning, And Predictive Analytics Are Utilized To Monitor Carbon Emissions, Forecast Energy Demand, Optimize Renewable Energy Integration, And Improve Operational Efficiency. AI-driven Models Enable Real-time Decision-making, Facilitating Effective Energy Dispatch, Load Balancing, And Carbon Footprint Reduction. Furthermore, Intelligent Carbon Accounting And Emission Tracking Mechanisms Support Regulatory Compliance And Environmental Sustainability Goals. The Proposed Framework Demonstrates How AI Can Contribute To Cleaner Energy Production, Reduced Operational Costs, And Enhanced Grid Reliability While Supporting Decarbonization Initiatives. The Study Highlights The Potential Of AI-enabled Carbon Management As A Strategic Approach For Achieving Sustainable, Resilient, And Environmentally Responsible Power Systems In The Era Of Smart Energy Transformation.

Published:

16-12-2022

Issue:

Vol. 22 No. 12 (2022)

Page Nos:

54-60

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

How to Cite