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The ever-growing concerns about global warming and the rapid depletion of fossil fuels have triggered a rising interest in the research for cleaner, more efficient, and cost-effective energy generation. Organic Rankine cycle systems have immense potential to become a strong alternative to conventional methods of energy generation. However, such systems' efficiency is limited by the performance of the incorporated gas expanders or prime movers. Conventional gas expanders often utilize ports or cam-operated valves. Ported expanders offer limited efficiency and controllability and produce high emissions, causing a large amount of heated and compressed gas to be wasted. Cam-operated valves, in contrast, increase expansion performance compared to ported expanders; however, they have no variability and adaptability to changes in system parameters such as gas pressure, temperature, dryness fraction, and load variation, to name a few. On a positive note, this issue can be addressed by adopting a variable timing and fast-operating, control valve with an accurate and adaptive control mechanism at the expander inlet. A properly designed and controlled valve can greatly improve the system performance of gas expanders and pave the way for an efficient low-cost alternative energy generation. This manuscript provides a comparative review of recent progress on the design, modeling, optimization, and control aspects of valves for gas expanders. A clear pathway on the scope of further development is also drawn based on the present state of the art. [ABSTRACT FROM AUTHOR]

In this work, an artificial neural network (ANN)-based model is proposed to describe the input–output relationships in a Limaçon-To-Circular (L2C) gas expander with an inlet valve. The L2C gas expander is a type of energy converter that has great potential to be used in organic Rankine cycle (ORC)-based small-scale power plants. The proposed model predicts the different performance indices of a limaçon gas expander for different input pressures, rotor velocities, and valve cutoff angles. A network model is constructed and optimized for different model parameters to achieve the best prediction performance compared to the classic mathematical model of the system. An overall normalized mean square error of 0.0014, coefficient of determination ( R 2 ) of 0.98, and mean average error of 0.0114 are reported. This implies that the surrogate model can effectively mimic the actual model with high precision. The model performance is also compared to a linear interpolation (LI) method. It is found that the proposed ANN model predictions are about 96.53% accurate for a given error threshold, compared to about 91.46% accuracy of the LI method. Thus the proposed model can effectively predict different output parameters of a limaçon gas expander such as energy, filling factor, isentropic efficiency, and mass flow for different operating conditions. Of note, the model is only trained by a set of input and target values; thus, the performance of the model is not affected by the internal complex mathematical models of the overall valved-expander system. This neural network-based approach is highly suitable for optimization, as the alternative iterative analysis of the complex analytical model is time-consuming and requires higher computational resources. A similar modeling approach with some modifications could also be utilized to design controllers for these types of systems that are difficult to model mathematically. [ABSTRACT FROM AUTHOR]

Renewable energy-based compact energy-generation systems based on the organic Rankine cycle (ORC) can be employed to meet the ever-growing thirst for affordable and clean energy. The overall performance and effectiveness of ORC systems are constrained by the low efficiency of the gas expander, specifically the positive displacement expander, which is responsible for energy conversion from the working fluid. This low-efficiency scenario can be significantly improved by employing a control valve to regulate and restrict the flow of the working fluid into the expander. A control valve can effectively curve the loss of costly compressed and energized working fluids by allowing them to expand in the expander chamber before discharging through the outlet port. They can thus be used to regulate the amount of energy yield and output power. In this work, two direct drive rotary valves (DDRVs) operated by a stepper motor (SM-DDRV) and rotary solenoid (RS-DDRV) are suggested, and the behavior of the valves is examined. The effect of friction and temperature on the valve response is also studied. Additionally, the effect of inlet control valves on the overall system performance of the limaçon expander is assessed. Thermodynamic properties such as the isentropic efficiency and filling factor are also computed. The effect of leakage due to valve response delay is analyzed at different inlet pressures. The performance indices are compared to the expander performance without any inlet valve. The SM-DDRV setup results in a 14.86% increase in isentropic efficiency and a 220% increase in the filling factor, whereas the RS-DDRV performs moderately with a 2.58% increase in isentropic efficiency and an 80% increase in the filling factor compared to a ported expander. The SM-DDRV provides better performance indices compared to the RS-DDRV and without valve setups. However, the performance of the limaçon expander with the SM-DDRV is sensitive to the inlet pressure and degrades at higher pressure. Overall, the valves proposed in this work present key insights into improving the performance characteristics of gas expanders of ORC systems. [ABSTRACT FROM AUTHOR]