Multi objective optimization and artificial neural network of a novel multi generation system using geothermal heat source and cold energy recovery of liquefied natural gas - Yophie Dikaimana

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Abstract

Renewable energy such as geothermal is very effective in reducing the effects of greenhouse gas emissions. Therefore geothermal-based multi-generation system can be used to produce commodities for cooling, power, hydrogen and water desalination system combined with liquefied natural gas as a cold energy recovery. To assess the performance of the system of the multigeneration system used, energy analysis, exergy, exergoeconomic and exergoenvironmental are needed. Also used is single and multi-objective optimization, done by Engineering Equation Solver (EES) and MATLAB softwares.

The results to be achieved or the hypothesis of the multi-objective optimization and artificial neural network multi-generation system, are: energy analysis, exergy, exergoeconomic (in the form of cost in each unit) and exergoenvironmental. Constraints used are geothermal temperatures, steam fraction and MER. The higher thermal efficiency can be achieved by increasing the vapor generator pressure and evaporator temperature or decreasing mass extraction ratio, separator pressure 2, turbine inlet pressure 2, geothermal inlet temperature, vapor generator terminal temperature difference and ammonia based concentration.


Mahaakbar96

25 months ago
Score 0++
untuk ees apakah persamaan yang sudah jadinya, dapat darimana ya bang ?

Yophie.dikaimana

25 months ago
Score 0++
persamaannya saya dapat dari paper Towhid et.al. 2018

Ahmadzikri.engineer

25 months ago
Score 0++
variabel-variabel apa saja yang digunakan pada single maupun multi-objective optimization pada project ini?

Yophie.dikaimana

25 months ago
Score 0++
variabelnya seperti Tgeothermal, mgeo, Pvg, Y(concentration)
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