Characteristic Study Of Molten Carbonate Fuel Cell And Absorption Refrigerator Hybrid System

The Molten carbonate fuel cell(MCFC)is widely used in the combined heat and power field and hybrid power generation field because of the considerable residual heat produced by electrochemical reaction.The absorption refrigeration(AR)is widely used in the field of waste heat recovery,which can alleviate environmental pollution and energy shortage.This paper takes energy saving and consumption reduction as its starting point.First,a molten carbonate fuel cell and absorption refrigeration hybrid system(MCFC/AR)running in a stable state is established.The irreversibility of the electrochemistry and the thermodynamics in the system is considered,and then the equivalent output power,the efficiency and the ecological coefficient of performance(ECOP)of the hybrid system as well as the expression of the entropy production rate are derived.Here,a mathematical model is established and the numerical simulation method is used to analyze the performance of the hybrid system so as to determine the optimization interval of the working parameters of the hybrid system.Second,the hybrid system is optimized and analyzed based on the multi-objective genetic algorithm(NSGA-?).Then four optimization objectives(the output power,the efficiency,the ECOP and the entropy production rate)as well as four decision variables(the operating current density,the operating temperature and the operating pressure of the MCFC,the internal irreversibility parameter of the AR)are determined with four situations created(each situation contains three optimization objectives).Then four groups of Pareto optimal solution sets and population distribution graphs of the four decision variables are obtained.Third,three effective decision-making methods(TOPSIS,LINMAP,FUZZY Bellman-Zadeh)are used to determine the relative optimum solution of each situation,so that the advantages and disadvantages of the four situations can be compared.Finally,the advantages of multi-objective optimization over single objective optimization are analyzed.The contents of this paper are as follows:In the first chapter,the development history and research progress of the molten carbonate fuel cell and the multi-objective optimization genetic algorithm are introduced as well as the research contents and major work of this paper.In the second chapter,a mathematical model of the MCFC is established.Under the premise of considering the irreversible loss of the cell itself,the numerical simulation and performance analysis of the MCFC are carried out so as to obtain the optimization interval of the operating parameters of the running MCFC.Finally,the effects of operating temperature and operating pressure on the performance of the MCFC are analyzed.In the third chapter,a MCFC/AR hybrid system model is established.The irreversibility of the electrochemistry and the thermodynamics in the system is considered,and the expressions for important parameters,such as the power,the efficiency and the ECOP parameters of the hybrid system,are derived.By numerical simulation the improvement situation of the hybrid system compared to the MCFC running alone is analyzed,and the optimal working intervals of the current density,the power density and the efficiency are obtained.After that,the ecological optimization of the system is carried out so as to obtain the ecological optimization interval of the working parameters.Finally,the influences of the operating temperature and the operating pressure of the MCFC,the internal irreversibility parameter of the AR on the performance of the hybrid system are analyzed.In the fourth chapter,the NSGA-? algorithm is applied to the multi-objective optimization of the hybrid system.This paper takes the power,the efficiency,the entropy production rate density and the ECOP of the hybrid system as optimization objectives,and the current density,the operating temperature,the operating pressure of the MCFC and the internal irreversibility parameter of the AR are selected as decision variables.In order to reduce the strong conflicts between the objectives when optimizing the four objective functions at the same time,four situations are proposed,each of which contains three optimization objectives.Then the population distribution graphs of the Pareto frontier and decision variables under each situation are obtained by numerical simulation.After obtaining the relative optimum solution,the corresponding operating conditions and the deviation index under different situations by using the decision-making methods,the advantages and disadvantages of different situations in guiding the system optimization design are analyzed.Finally,the single objective optimization results are compared with that of the TOPSIS decision-making method under situation 4.The fifth chapter summarizes the main contents,the main conclusions and the innovation of this paper.Finally,some in-depth future research ideas and prospects are put forward in view of the shortcomings of the research.