REAL-TIME MONITORING AND CONTROL SYSTEMS FOR EMISSION COMPLIANCE IN POWER PLANTS
Keywords:
Emission monitoring, Artificial intelligence, Predictive control, Environmental compliance, Climate change mitigationAbstract
This paper examines the state-of-the-art real-time monitoring and control systems for emission compliance in power plants. Advanced sensor technologies, including quantum cascade lasers and nanostructured materials, have significantly enhanced the accuracy and reliability of emission monitoring. Artificial intelligence and machine learning techniques have revolutionized control systems, enabling predictive maintenance and autonomous optimization. The integration of blockchain technology has improved data integrity and streamlined emissions trading processes. However, challenges persist in system integration, especially in older facilities, and in managing the increasing volume of data generated. Economic considerations, including high initial costs and ongoing maintenance expenses, remain significant barriers to widespread adoption. The study also highlights the evolving regulatory landscape and its impact on emission control strategies. Future trends point towards the development of more robust multi-pollutant sensors, AI-driven control systems, and greater integration with smart grid technologies. This comprehensive analysis provides valuable insights for power plant operators, policymakers, and researchers, underlining the critical role of advanced monitoring and control systems in achieving sustainable power generation and contributing to global climate change mitigation efforts.References
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