Multi-objective optimization for a small biomass cooling and power cogeneration system using binary mixtures
作者： César Adolfo Rodriguez Sotomonte , Thiago Gotelip Correa Veloso , Christian J.R. Coronado , Marco A. Rosa do Nascimento
DOI: 10.1016/J.APPLTHERMALENG.2020.116045
关键词:
摘要: Abstract This paper aims to find the optimal design for a small-scale cogeneration system using Organic Rankine cycle (ORC) integrated with an ammonia-water absorption refrigeration cycle. The thermodynamic model included two ORC configurations (with and without internal heat exchanger) used eight Siloxanes their possible mixtures as working fluids. Additionally, effects of six parameters were investigated, these being evaporation pressure, superheating, pinch point temperature, condensation exchanger effectiveness, mass fraction in binary mixtures. A multi-objective genetic optimization algorithm (NSGA-II) was employed order evaluate Pareto solutions, maximizing electrical cooling power minimizing overall global conductance, variables that have greatest influence on technical economic performance solutions present trade-offs between three objective functions, where optimum are found within generation ranges energy efficiency 18 30%. MM, MM/MD4M, MDM/MD4M MDM/D5, stand out best options fluids, net output 700 1170 kW, capacity 80 1050 kW, product transfer coefficient conductance range 120–620 kW/K.
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