Process Simulation And Multi-objective Optimization Of Ocean Thermal Energy Conversion Cycle

Ocean thermal energy conversion(OTEC),as a clean and new energy technology,is an excellent solution to energy and power supply along the coastline with its extraordinary reserves and great potentials.Based on the actually measured data on ocean environment,this paper will build the organic Rankine cycle(ORC)model of OTEC for process simulation and sensitivity analysis.With the multi-objective optimization and decision-making method,it realizes thermal-economical optimization of the OTEC power generation model and makes comparative analysis on performance of different working fluids.Firstly,it summarizes the domestic and overseas OTEC research development,briefly introduces the common power generation configuration,and brings up the start point of research which combines multi-objective optimization and selection of working fluids for OTEC model.Secondly,it elaborates the thermodynamics process of ORC of OTEC and suggests applicable working fluids.Thus,it builds the OTEC power generation model,and illustrates the modelling method for each element of the system and the economical analysis model.After this,relevant data and documents are referenced to validate the built model.Thirdly,it applies support vector regression for fitting analysis for actually measured ocean temperature and depth data in selected sea areas,and conducts process simulation and sensitivity analysis on the model by six working fluids,including key performance parameters such as net output power,thermal efficiency,LCOE and exergetic efficiency.Finally,it describes details on the multi-objective particle swarm optimization(MOPSO)as well as principles and computing processes of three decision-making methods applied here,and introduces the classic method in NSGA-2 algorithm to improve performance of the traditional MOPOS algorithm.Furthermore,it uses LCOE and exergetic efficiency,as dual objective functions to represent the thermal economy of the OTEC system,and based on the improved MOPOS algorithm which realizes Pareto optimization,it produces six Pareto frontiers respectively corresponding to six selected working fluids.Finally,it concludes the global optimal solutions for six working fluids with different decision-making methods,and focuses on the thermal economy between working fluids and makes comparative analysis based on the non-dominated sorting method.