Scholarlink

This research shall first examine the possibility of incorporating solar and wind energy into the power generation system at the Koradi Thermal Power Station in India and secondly general an AI-based model for continual emission monitoring and forecasting. Its objective is to discuss the role of renewable energy hybrid systems concerning to minimize carbon emissions in thermal power plant. Solar and wind power play an instrumental role in minimizing the usage of fossil energy, and integrating them with AI will further develop the best method of managing emission. The first prerequisite of the study will be to assess the technical and economic viability of hybrid solar-wind system integration into the presently installed power system of Koradi. It will then proceed to create an AI-based model—based on the massive data set—to estimate emissions in real time for faster, more accurate decisions of where to focus to maximize emission control outcomes. The use of advanced analytical techniques in these areas holds promise for benchmarking the inefficiencies, modeling future trends in emissions, and proactivity, enhancing operational effectiveness, and minimizing harm to the environment. The study also puts a figure on the possible reduction in carbon emissions when these technologies are implemented. Through a comparison of current emission levels to simulation results derived from the hybrid system and incorporating AI, this work shall ascertain the impact of these technologies in reducing emissions to sustainable levels. Last of all, the research also provides recommendations for a replicable workflow that can be applied to other thermal power stations in India. The intended advantage of this approach is to establish a way of planning how the reduction in the carbon impact on thermal electricity generation can be done on the national level to encourage cleaner electricity transformation in all thermal power stations. The framework will lay recommendations on how renewables will interconnect to AI-based emission control systems to serve multiple power plants, and across regions. The study aligns well with India’s environmental commitments and provides scalable solutions.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Integrating Renewable Energy Sources and AI for Emission Reduction: A Feasibility Study of Solar and Wind Energy in Koradi Thermal Power Station, Nagpur

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Shailesh Gahane,
  • Pankajkumar Anawade,
  • Prateek Verma,
  • Payal Khode,
  • Deepak Sharma

摘要

This research shall first examine the possibility of incorporating solar and wind energy into the power generation system at the Koradi Thermal Power Station in India and secondly general an AI-based model for continual emission monitoring and forecasting. Its objective is to discuss the role of renewable energy hybrid systems concerning to minimize carbon emissions in thermal power plant. Solar and wind power play an instrumental role in minimizing the usage of fossil energy, and integrating them with AI will further develop the best method of managing emission. The first prerequisite of the study will be to assess the technical and economic viability of hybrid solar-wind system integration into the presently installed power system of Koradi. It will then proceed to create an AI-based model—based on the massive data set—to estimate emissions in real time for faster, more accurate decisions of where to focus to maximize emission control outcomes. The use of advanced analytical techniques in these areas holds promise for benchmarking the inefficiencies, modeling future trends in emissions, and proactivity, enhancing operational effectiveness, and minimizing harm to the environment. The study also puts a figure on the possible reduction in carbon emissions when these technologies are implemented. Through a comparison of current emission levels to simulation results derived from the hybrid system and incorporating AI, this work shall ascertain the impact of these technologies in reducing emissions to sustainable levels. Last of all, the research also provides recommendations for a replicable workflow that can be applied to other thermal power stations in India. The intended advantage of this approach is to establish a way of planning how the reduction in the carbon impact on thermal electricity generation can be done on the national level to encourage cleaner electricity transformation in all thermal power stations. The framework will lay recommendations on how renewables will interconnect to AI-based emission control systems to serve multiple power plants, and across regions. The study aligns well with India’s environmental commitments and provides scalable solutions.