AI Summary & Key Takeaways
AI InsightThe results showed that, the total exergy efficiency of the system was 35.25% while its value increased with the ABC optimization in the maximum possible exergy efficiency of 38.45%.
📌 3 Key Takeaways
Abstract
For engineering applications related to techniques that optimize power plants or thermal systems, optimization techniques are very important. Power plants with wasted geothermal resources and inefficient organic Rankine cycle ORC attract the attention of researchers, engineers and decision-makers. In this study, the pressure and mass flow rates on turbine lines are optimized to maximize exergy efficiency in a binary ORC geothermal power plant GPP . With this aim, initially data collected from a real operating GPP are used to simulate the system. Then an artificial bee colony ABC algorithm is developed for this model. The results showed that, the total exergy efficiency of the system was 35.25% while its value increased with the ABC optimization in the maximum possible exergy efficiency of 38.45%. Optimizing the turbine lines in the system ensured improvement rate of 4-6% for the turbines. As a result, the thermodynamic performance of the system is estimated at the same moment and with reasonable accuracy, it can be ensured that the physical process used for improvements is better understood.