The CO_(2)power cycle(CPC)system is an efficient and environmentally friendly method for waste heat recovery(WHR).However,the traditional design and optimization process of a CPC system is very complex and timeconsumi...The CO_(2)power cycle(CPC)system is an efficient and environmentally friendly method for waste heat recovery(WHR).However,the traditional design and optimization process of a CPC system is very complex and timeconsuming.This paper proposes a novel goal-oriented design method based on machine-learning methods for quickly designing an optimized CPC system with given performance indicators.And taking the design of the CO_(2)transcritical power cycle(CTPC)system for internal combustion engines(ICEs)as an example.Firstly,the net output power and the total cost of the system prediction models are trained by simulated data.Then the multiobjective optimization of the system is carried out by using the genetic algorithm coupled with the prediction models,and the optimization results are used to train a classification model.Finally,the given target indicators are input into the classification model for goal-oriented designing and getting the optimal configuration.The results of the goal-oriented design validation show that the goal-oriented design method can design the CTPC system well.And,once the classification model is trained,the CTPC system’s future goal-oriented design process only needs to be calculated once,significantly reducing design time.In conclusion,the goal-oriented design method based on machine-learning proposed is a novel and promising method.This is a technology that combines computer science and energy science and can provide users with a quick and reliable CPC system design method.展开更多
Hybrid solar-based integrated systems represent a viable solution for countries with abundant solar radiation,as they provide energy needs in an environmentally friendly way,offering a sustainable and economically adv...Hybrid solar-based integrated systems represent a viable solution for countries with abundant solar radiation,as they provide energy needs in an environmentally friendly way,offering a sustainable and economically advantageous energy solution that utilizes a free source of energy.Therefore,this research offers a thermodynamic evaluation of a novel integrated system driven by solar energy that aims to produce power,heating and freshwater.The integrated system consists of a parabolic trough collector that uses CO_(2) as its working fluid and implements the supercritical carbon dioxide cycle to generate power and heating.The integrated system also in-cludes an adsorption desalination system with heat recovery between the condenser and evaporator,which employs a cutting-edge material called an aluminium fumarate metal–organic framework to produce fresh water.For the modelling of a novel system,an en-gineering equation solver,which is considered a reliable tool for thermodynamic investigations,is employed.The effectiveness of an integrated system is evaluated using a mathematical model and different varying parameters are examined to ascertain their influence on thermal and exergy efficiency,specific daily water production and gained output ratio.The results revealed that the parabolic trough collector achieved a thermal efficiency of 67.2%and an exergy efficiency of 41.2%under certain conditions.Additionally,the thermal efficiencies for electrical and heating were obtained 24.68%and 9.85%,respectively.Finally,the specific daily water production was calculated,showing promising results and an increase from 7.1 to 12.5 m3/ton/day,while the gain output ratio increased from 0.395 to 0.62 when the temperature of hot water increased from 65°C to 85°C,under the selected conditions.展开更多
The objective of this paper is to understand the benefits that one can achieve for large-scale supercritical CO_(2)(S-CO_(2))coal-fired power plants.The aspects of energy environment and economy of 1000 MW S-CO_(2)coa...The objective of this paper is to understand the benefits that one can achieve for large-scale supercritical CO_(2)(S-CO_(2))coal-fired power plants.The aspects of energy environment and economy of 1000 MW S-CO_(2)coal-fired power generation system and 1000 MW ultra-supercritical(USC)water-steam Rankine cycle coal-fired power generation system are analyzed and compared at the similar main vapor parameters,by adopting the neural network genetic algorithm and life cycle assessment(LCA)methodology.Multi-objective optimization of the 1000 MW S-CO_(2)coal-fired power generation system is further carried out.The power generation efficiency,environmental impact load,and investment recovery period are adopted as the objective functions.The main vapor parameters of temperature and pressure are set as the decision variables.The results are concluded as follows.First,the total energy consumption of the S-CO_(2)coal-fired power generation system is 10.48 MJ/k Wh and the energy payback ratio is 34.37%.The performance is superior to the USC coal-fired power generation system.Second,the resource depletion index of the S-CO_(2)coal-fired power generation system is 4.38μPRchina,90,which is lower than that of the USC coal-fired power generation system,and the resource consumption is less.Third,the environmental impact load of the S-CO_(2)coal-fired power generation system is 0.742 m PEchina,90,which is less than that of the USC coal-fired power generation system,0.783 m PEchina,90.Among all environmental impact types,human toxicity potential HTP and global warming potential GWP account for the most environmental impact.Finally,the investment cost of the S-CO_(2)coal-fired power generation system is generally less than that of the USC coal-fired power generation system because the cost of the S-CO_(2)turbine is only half of the cost of the steam turbine.The optimal turbine inlet temperature T_(5)becomes smaller,and the optimal turbine inlet pressure is unchanged at 622.082°C/30 MPa.展开更多
The objective of this paper is to provide the optimal choice of single-reheating or double-reheating when considering residual flue gas heat in S-CO_2 coal fired power system. The cascade utilization of flue gas energ...The objective of this paper is to provide the optimal choice of single-reheating or double-reheating when considering residual flue gas heat in S-CO_2 coal fired power system. The cascade utilization of flue gas energy includes three temperature levels, with high and low temperature ranges of flue gas heat extracted by S-CO_2 cycle and air preheater, respectively. Two methods are proposed to absorb residual flue gas heat Qre in middle temperature range. Both methods shall decrease CO_2 temperature entering the boiler T4 and increase secondary air temperature Tsec air, whose maximum value is deduced based on energy conservation in air preheater. The system is analyzed incorporating thermodynamics, boiler pressure drop and energy distribution. It is shown that at a given main vapor temperature T5, the main vapor pressure P5 can be adjusted to a value so that Qre is completely eliminated, which is called the main vapor pressure adjustment method. For this method, single-reheating is only available for higher main vapor temperatures. The power generation efficiency for single-reheating is obviously higher than double-reheating. If residual flue gas heat does exist, a flue gas heater FGC is integrated with S-CO_2 cycle, which is called the FGC method. Both single-reheating and double-reheating share similar power generation efficiency, but single-reheating creates less residual flue gas heat. We conclude that single-reheating is preferable, and the pressure adjustment method achieves obviously higher power generation efficiency than the FGC method.展开更多
基金supported by the National Key R&D Program of China(2022YFE0100100).
文摘The CO_(2)power cycle(CPC)system is an efficient and environmentally friendly method for waste heat recovery(WHR).However,the traditional design and optimization process of a CPC system is very complex and timeconsuming.This paper proposes a novel goal-oriented design method based on machine-learning methods for quickly designing an optimized CPC system with given performance indicators.And taking the design of the CO_(2)transcritical power cycle(CTPC)system for internal combustion engines(ICEs)as an example.Firstly,the net output power and the total cost of the system prediction models are trained by simulated data.Then the multiobjective optimization of the system is carried out by using the genetic algorithm coupled with the prediction models,and the optimization results are used to train a classification model.Finally,the given target indicators are input into the classification model for goal-oriented designing and getting the optimal configuration.The results of the goal-oriented design validation show that the goal-oriented design method can design the CTPC system well.And,once the classification model is trained,the CTPC system’s future goal-oriented design process only needs to be calculated once,significantly reducing design time.In conclusion,the goal-oriented design method based on machine-learning proposed is a novel and promising method.This is a technology that combines computer science and energy science and can provide users with a quick and reliable CPC system design method.
文摘Hybrid solar-based integrated systems represent a viable solution for countries with abundant solar radiation,as they provide energy needs in an environmentally friendly way,offering a sustainable and economically advantageous energy solution that utilizes a free source of energy.Therefore,this research offers a thermodynamic evaluation of a novel integrated system driven by solar energy that aims to produce power,heating and freshwater.The integrated system consists of a parabolic trough collector that uses CO_(2) as its working fluid and implements the supercritical carbon dioxide cycle to generate power and heating.The integrated system also in-cludes an adsorption desalination system with heat recovery between the condenser and evaporator,which employs a cutting-edge material called an aluminium fumarate metal–organic framework to produce fresh water.For the modelling of a novel system,an en-gineering equation solver,which is considered a reliable tool for thermodynamic investigations,is employed.The effectiveness of an integrated system is evaluated using a mathematical model and different varying parameters are examined to ascertain their influence on thermal and exergy efficiency,specific daily water production and gained output ratio.The results revealed that the parabolic trough collector achieved a thermal efficiency of 67.2%and an exergy efficiency of 41.2%under certain conditions.Additionally,the thermal efficiencies for electrical and heating were obtained 24.68%and 9.85%,respectively.Finally,the specific daily water production was calculated,showing promising results and an increase from 7.1 to 12.5 m3/ton/day,while the gain output ratio increased from 0.395 to 0.62 when the temperature of hot water increased from 65°C to 85°C,under the selected conditions.
基金supported by the National Key R&D Program of China(2017YFB0601801)the National Natural Science Foundation of China(No.51806165)。
文摘The objective of this paper is to understand the benefits that one can achieve for large-scale supercritical CO_(2)(S-CO_(2))coal-fired power plants.The aspects of energy environment and economy of 1000 MW S-CO_(2)coal-fired power generation system and 1000 MW ultra-supercritical(USC)water-steam Rankine cycle coal-fired power generation system are analyzed and compared at the similar main vapor parameters,by adopting the neural network genetic algorithm and life cycle assessment(LCA)methodology.Multi-objective optimization of the 1000 MW S-CO_(2)coal-fired power generation system is further carried out.The power generation efficiency,environmental impact load,and investment recovery period are adopted as the objective functions.The main vapor parameters of temperature and pressure are set as the decision variables.The results are concluded as follows.First,the total energy consumption of the S-CO_(2)coal-fired power generation system is 10.48 MJ/k Wh and the energy payback ratio is 34.37%.The performance is superior to the USC coal-fired power generation system.Second,the resource depletion index of the S-CO_(2)coal-fired power generation system is 4.38μPRchina,90,which is lower than that of the USC coal-fired power generation system,and the resource consumption is less.Third,the environmental impact load of the S-CO_(2)coal-fired power generation system is 0.742 m PEchina,90,which is less than that of the USC coal-fired power generation system,0.783 m PEchina,90.Among all environmental impact types,human toxicity potential HTP and global warming potential GWP account for the most environmental impact.Finally,the investment cost of the S-CO_(2)coal-fired power generation system is generally less than that of the USC coal-fired power generation system because the cost of the S-CO_(2)turbine is only half of the cost of the steam turbine.The optimal turbine inlet temperature T_(5)becomes smaller,and the optimal turbine inlet pressure is unchanged at 622.082°C/30 MPa.
基金supported by the National Key R&D Program of China (2017YFB0601801)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (51821004)the Fundamental Research Funds for the Central Universities (2018ZD02 and 2018QN042)
文摘The objective of this paper is to provide the optimal choice of single-reheating or double-reheating when considering residual flue gas heat in S-CO_2 coal fired power system. The cascade utilization of flue gas energy includes three temperature levels, with high and low temperature ranges of flue gas heat extracted by S-CO_2 cycle and air preheater, respectively. Two methods are proposed to absorb residual flue gas heat Qre in middle temperature range. Both methods shall decrease CO_2 temperature entering the boiler T4 and increase secondary air temperature Tsec air, whose maximum value is deduced based on energy conservation in air preheater. The system is analyzed incorporating thermodynamics, boiler pressure drop and energy distribution. It is shown that at a given main vapor temperature T5, the main vapor pressure P5 can be adjusted to a value so that Qre is completely eliminated, which is called the main vapor pressure adjustment method. For this method, single-reheating is only available for higher main vapor temperatures. The power generation efficiency for single-reheating is obviously higher than double-reheating. If residual flue gas heat does exist, a flue gas heater FGC is integrated with S-CO_2 cycle, which is called the FGC method. Both single-reheating and double-reheating share similar power generation efficiency, but single-reheating creates less residual flue gas heat. We conclude that single-reheating is preferable, and the pressure adjustment method achieves obviously higher power generation efficiency than the FGC method.
