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- W4200593485 abstract "Energy shortage, greenhouse effect and environmental pollution are the three major crises faced by mankind. How to solve these three problems effectively has become the focus of all countries. Therefore, this paper proposes an innovative LNG cold energy utilization method that can simultaneously alleviate these three problems. This method includes an improved structure of the organic Rankine cycle, CO2 capture cycle and supercritical CO2 extraction of wastewater. In addition, automated machine learning based on data-driven approach is effectively used for modeling the wastewater extraction. Then, after verifying the accuracy of the proposed model, some parameters have great influence on the system performance. For instance, the temperature of supercritical CO2 and working fluid water affect the local exergy efficiency and their regression coefficients are −0.29%/°C and 0.13%/°C, respectively. These parameters in wastewater extraction process are studied. Finally, under the optimization of genetic algorithm, the maximum wastewater treatment can reach 62.7 t/h increasing by 14.0%, and the LNG cold energy generation can reach 110.1 kWh/tLNG with an increase of 28.9%, while the exergy efficiency of the system is 50.4% increasing by 24.1%. Thus, organic Rankine cycle power generation, carbon capture and wastewater treatment play the roles of energy saving, emission reduction and environmental protection. At the same time, the results are compared with those of other scholars to verify the superiority of the proposed scheme." @default.
- W4200593485 created "2021-12-31" @default.
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- W4200593485 date "2022-02-01" @default.
- W4200593485 modified "2023-10-15" @default.
- W4200593485 title "Evaluating and optimizing the cold energy efficiency of power generation and wastewater treatment in LNG-fired power plant based on data-driven approach" @default.
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- W4200593485 doi "https://doi.org/10.1016/j.jclepro.2021.130149" @default.
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