Technologies for utilizing waste heat for power generation have attracted significant attention in recent years due to their potential to enhance energy efficiency and reduce greenhouse gas emissions.This research foc...Technologies for utilizing waste heat for power generation have attracted significant attention in recent years due to their potential to enhance energy efficiency and reduce greenhouse gas emissions.This research focuses on the comparative and optimization analysis of three supercritical carbon dioxide(sCO_(2))Rankine cycles(simple,cascade,and split)for gas turbine waste heat recuperation.The study begins with parametric analysis,investigating the significant effects of key variables,including turbine inlet temperature,condenser inlet temperature,and pinch point temperature,on the thermal performance of advanced sCO_(2) power cycles.To identify the most efficient cycle configuration,a multi-objective optimization approach is employed.This approach combines a Genetic Algorithm with machine learning regression models(Random Forest,XGBoost,Artificial Neural Network,Ridge Regression,and K-Nearest Neighbors)to predict cycle performance using a dataset extracted from cycle simulations.The decision-making process for determining the optimal cycle configuration is facilitated by the TOPSIS(technique for order of preference by similarity to the ideal solution)method.The study's major findings reveal that the split cycle outperforms the simple and cascade configurations in terms of power generation across various operating conditions.The optimized split cycle not only demonstrates superior power output but also exhibits enhanced net power output,heat recovery,system and exergy efficiency of 7.99 MW,76.17%,26.86%and 57.96%,respectively,making it a promising choice for waste heat recovery applications.This research has the potential to contribute to the advancement and widespread adoption of waste heat recovery in energy technologies boosting system efficiency and economic feasibility.It provides a new perspective for future research,contributing to the improvement of energy generation infrastructure.展开更多
In this paper,a novel polygeneration system involving plasma gasifier,pyrolysis reactor,gas turbine(GT),supercritical CO_(2)(S-CO_(2))cycle,and organic Rankine cycle(ORC)has been developed.In the proposed scheme,the s...In this paper,a novel polygeneration system involving plasma gasifier,pyrolysis reactor,gas turbine(GT),supercritical CO_(2)(S-CO_(2))cycle,and organic Rankine cycle(ORC)has been developed.In the proposed scheme,the syngas is obtained by the gasification and the pyrolysis is first burned and drives the gas turbine for power generation,and then the resulting hot exhaust gas is applied to heat the working fluid for the supercritical CO_(2)cycle and the working fluid for the bottom organic Rankine cycle.In addition to the electrical output,the pyrolysis subsystem also produces pyrolysis oil and char.Accordingly,energy recovery is achieved while treating waste in a non-hazardous manner.The performance of the new scheme was examined by numerous methods,containing energy analysis,exergy analysis,and economic analysis.It is found that the net total energy output of the polygeneration system could attain 19.89 MW with a net total energy efficiency of 52.77%,and the total exergy efficiency of 50.14%.Besides,the dynamic payback period for the restoration of the proposed project is only 3.31 years,and the relative net present value of 77552640 USD can be achieved during its 20-year lifetime.展开更多
文摘Technologies for utilizing waste heat for power generation have attracted significant attention in recent years due to their potential to enhance energy efficiency and reduce greenhouse gas emissions.This research focuses on the comparative and optimization analysis of three supercritical carbon dioxide(sCO_(2))Rankine cycles(simple,cascade,and split)for gas turbine waste heat recuperation.The study begins with parametric analysis,investigating the significant effects of key variables,including turbine inlet temperature,condenser inlet temperature,and pinch point temperature,on the thermal performance of advanced sCO_(2) power cycles.To identify the most efficient cycle configuration,a multi-objective optimization approach is employed.This approach combines a Genetic Algorithm with machine learning regression models(Random Forest,XGBoost,Artificial Neural Network,Ridge Regression,and K-Nearest Neighbors)to predict cycle performance using a dataset extracted from cycle simulations.The decision-making process for determining the optimal cycle configuration is facilitated by the TOPSIS(technique for order of preference by similarity to the ideal solution)method.The study's major findings reveal that the split cycle outperforms the simple and cascade configurations in terms of power generation across various operating conditions.The optimized split cycle not only demonstrates superior power output but also exhibits enhanced net power output,heat recovery,system and exergy efficiency of 7.99 MW,76.17%,26.86%and 57.96%,respectively,making it a promising choice for waste heat recovery applications.This research has the potential to contribute to the advancement and widespread adoption of waste heat recovery in energy technologies boosting system efficiency and economic feasibility.It provides a new perspective for future research,contributing to the improvement of energy generation infrastructure.
基金supported by the National Natural Science Fund of China(No.52106008)Science Fund for Creative Research Groups of the National Natural Science Foundation of China(No.51821004)Science and Technology Planning Project of Guangdong Province(No.2020B1212060048).
文摘In this paper,a novel polygeneration system involving plasma gasifier,pyrolysis reactor,gas turbine(GT),supercritical CO_(2)(S-CO_(2))cycle,and organic Rankine cycle(ORC)has been developed.In the proposed scheme,the syngas is obtained by the gasification and the pyrolysis is first burned and drives the gas turbine for power generation,and then the resulting hot exhaust gas is applied to heat the working fluid for the supercritical CO_(2)cycle and the working fluid for the bottom organic Rankine cycle.In addition to the electrical output,the pyrolysis subsystem also produces pyrolysis oil and char.Accordingly,energy recovery is achieved while treating waste in a non-hazardous manner.The performance of the new scheme was examined by numerous methods,containing energy analysis,exergy analysis,and economic analysis.It is found that the net total energy output of the polygeneration system could attain 19.89 MW with a net total energy efficiency of 52.77%,and the total exergy efficiency of 50.14%.Besides,the dynamic payback period for the restoration of the proposed project is only 3.31 years,and the relative net present value of 77552640 USD can be achieved during its 20-year lifetime.
