Modelling of energy and exergy analysis of ORC integrated systems in terms of sustainability by applying artificial neural network

The present study focuses upon the Organic Rankine Cycle integrated into Evacuated Tube Heat Pipe (ETHP), which systems are an alternative solar energy system to low-efficiency planary collectors. In this work, a detailed thermodynamic and artificial neural networks (ANN) analysis was conducted to evaluate the solar energy system. One of the key parameters of sustainable approaches focused on exergy efficiency is applying to thermal engineering. In addition to this nowadays, sustainable engineering approaches is a necessity for improving the efficiency of all of the engineering researches areas. For this reason, the Artificial Neural Network (ANN) model is used to forecast different types of energy efficiency problems in thermodynamic literature. Within the scope of this study, the exergy efficiency was evaluated on the developed Artificial Neural Network algorithm. The effect rates of parameters such as pressure, temperature, and ambient temperature affecting the exergy efficiency of ORC integrated ETHP were calculated. Finally, significant findings obtained were evaluated in terms of thermodynamics rules.