Multi-objective Optimization of Hydrogen Production in Hybrid Renewable Energy Systems
EEE Congress on Evolutionary Computation (CEC) • 2019
معلومات البحث
المؤلفون
Shaimaa Seyam; Khaled H. M. Al-Hamed; Ali M. M. I. Qureshy; Ibrahim Dincer; Martin Agelin-Chaab; Shahryar Rahnamayan
الكلمات المفتاحية
Genetic Programming; NSGA-II optimization; Parallel Coordination; RadViz Visualization; Renewable energy system
المجلة العلمية
EEE Congress on Evolutionary Computation (CEC)
الناشر
Not Available
المجلد
Not Available
العدد
Not Available
الصفحات
850-857
publication.type
International
رابط البحث
Open Link
المواد المرفقة
Not Available
الملخص
The proposed multi-objective optimized hybrid re- newable energy system consists of solar panels, wind turbines, a proton exchange membrane (PEM) electrolyzer for hydrogen production, and an absorption cooling system for the summer season. This study is conducted in two locations in Egypt and Saudi Arabia as the case studies. The study presents a thermodynamic analysis to investigate the system performance. In addition, an optimization-based analysis is conducted using NSGA-II algorithm to determine optimal values of the decision variables. The hybrid renewable system can operate in a signifi- cant performance with water mass flow rate of 1.8 kg/s to produce hydrogen with a mass flow rate of 0.2 kg/s, and ammonia mass flow rate of about 0.2 kg/s to produce cooling load between 40 and 120 kW with energy and exergy efficiency of more than 65%.
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