Performance assessment of a solar powered hydrogen production system and its ANFIS model

Abstract

Apart from many limitations, the usage of hydrogen in different day-to-day applications have been increasing drastically in recent years. However, numerous techniques available to produce hydrogen, electrolysis of water is one of the simplest and cost-effective hydrogen production techniques. In this method, water is split into hydrogen and oxygen by using external electric current. In this research, a novel hydrogen production system incorporated with Photovoltaic -Thermal (PVT) solar collector is developed. The influence of different parameters like solar collector tilt angle, thermal collector design and type of heat transfer fluid on the performance of PVT system and hydrogen production system are also discussed. Finally, thermal efficiency, electrical efficiency, and hydrogen production rate have been predicted by using the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique. Based on this study results, it can be inferred that the solar collector tilt angle plays a significant role to improve the performance of the electrical and thermal performance of PVT solar system and Hydrogen yield rate. On the other side, the spiral-shaped thermal collector with water exhibited better end result than the other hydrogen production systems. The predicted results ANFIS techniques represent an excellent agreement with the experimental results. In consequence, it is suggested that the developed ANFIS model can be adopted for further studies to predict the performance of the hydrogen production system.

Development of Various Photovoltaic‐Driven Water Electrolysis Technologies for Green Solar Hydrogen Generation

“…The heat transfer was improved by circulating the electrolyte through a heat exchange chamber inserted between the PV module and the EC, before feeding the EC. This prototype has a simpler balance of plant than others [9,10] because it eliminates both the need for a separate fluid circulation circuit for heat transfer and power conditioning electronics. Unlike the previous prototype for which the EC could not be separately tested, the output of the prototype could be tested with and without thermal integration.…”

“…For example, the PV modules can be cooled by a heat transfer fluid that heats the EC, leading to enhanced StH efficiency. [9,10] In another case, the excess heat generated by the PV modules, exposed to concentrated sunlight, is transferred to the EC by direct thermal contact, leading to extremely high StH efficiencies >15-20% but at the cost of more complex engineering and the need for high-temperature-resistant materials. [11][12][13][14] To prevent long start-up times in the morning while the EC is still heating up, or reduced output during low-solar irradiance intervals, such systems would need a heat reservoir.…”

ANFIS and ANN models to predict heliostat tracking errors

“…Regardless of prior knowledge about the physical phenomenon and the nature of the relationships between the input/output variables, ANN and ANFIS networks can be used to interpret the behavior of complex nonlinear problems and, therefore, predict their future response. These two methods of prediction have been used in several fields [ [13] , [14] , [15] , [16] , [17] , [18] ]. To determine the most suitable technique for predicting data, ANN and ANFIS performances have been compared in many instances [ 19 , 20 ].…”

Techno-economic assessment of green hydrogen production using different configurations of wind turbines and PV panels

“…A ten percent increase in Hydrogen generation and a 0.1% increase in capital investment costs were found when solar power output increased [8]. The PVT Hydrogen production system can produce up to14.15 ml/min with electric efficiency [9]. In addition, wind speed, WT hub height, and WT-rated power considerably impact system performance when used in Hydrogen synthesis utilizing wind power.…”