| publication name | Multi-objective Optimization of Hydrogen Production in Hybrid Renewable Energy Systems |
|---|---|
| Authors | Shaimaa Seyam; Khaled H. M. Al-Hamed; Ali M. M. I. Qureshy; Ibrahim Dincer; Martin Agelin-Chaab; Shahryar Rahnamayan |
| year | 2019 |
| keywords | Genetic Programming; NSGA-II optimization; Parallel Coordination; RadViz Visualization; Renewable energy system |
| journal | EEE Congress on Evolutionary Computation (CEC) |
| volume | Not Available |
| issue | Not Available |
| pages | 850-857 |
| publisher | Not Available |
| Local/International | International |
| Paper Link | https://ieeexplore.ieee.org/abstract/document/8790299 |
| Full paper | download |
| Supplementary materials | Not Available |
Abstract
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%.