Abstract
Electricity usage has increased in today's life. Also, it is considered the most critical parameter. Hence, several power plants have been utilized to generate electricity based on specific constraints, like solar assist systems, fuel-based systems, etc. Some system has caused a wide range of resource wastage. Considering these merits and demerits, combined cycle power plant (CCPP) has been implanted for electricity production. However, the poor heat absorbance and emission rates have reduced the power generation percentage. So, the present article has developed novel wolf-based gradient boost vapor absorption system (WGVAS) for the CCPP. Consequently, the designed WGVAS-CCPP system is the optimal condition by optimizing the power usage, energy, and heat absorbance rate. Thus, by optimizing the CCPP parameters, the emission range of CO2 and NOx was reduced. To describe the need of the optimal function in the present CCPP system, the performance is validated under dual phases that are before applying the wolf fitness and after applying the wolf fitness function. Hence, the highest energy efficiency has been reoccurred by reducing the emission range. Hence, the present optimal model efficiently reduces the emission constraints in the CCPP system.
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Naik, M.M.M., Murthy, V.S.S. & Durga Prasad, B. An intelligent energy-efficient vapor absorption refrigeration system for inlet air cooling of CCPPS. J Braz. Soc. Mech. Sci. Eng. 44, 489 (2022). https://doi.org/10.1007/s40430-022-03796-1
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DOI: https://doi.org/10.1007/s40430-022-03796-1