Effect of compressor inlet parameters on the part-load performance of a solar-driven supercritical CO₂ cycle

To address the issue of poor efficiency of supercritical CO₂ cycles under low-load conditions (i.e. the ratio of actual load to rated load is less than 0.3), this study focuses on improving the power generation performance of a solar-powered simple regenerative supercritical CO₂ cycle at low loads by adjusting the compressor conditions. A deep neural network-based compressor performance forecast is developed to assess the part-load system performance. The disparities in system performance under inventory and upstream bypass controls are discussed, as well as the impact of changes in compressor intake conditions on the system efficiency under low-load scenarios. The compressor model exhibits a performance prediction deviation of less than 3.0% across variable intake conditions. The key findings show that when the system outputs 10% load power, its off-design efficiency decreases to 7.1% and 6.5% under inventory and bypass controls, respectively. This low-load performance enhancement can be achieved by reducing the exergy loss of the turbine and regenerator. Under inventory control, the increase in temperature and decrease in pressure at the compressor intake improve system performance at 10% load by 13.5%. Under upstream bypass control, improving low-load system performance by reducing compressor inlet pressure is limited by the compressor's choke margin, but this limitation can be mitigated by using auxiliary inventory. The optimal auxiliary inventory flow rate of 4.5 kg·s⁻¹ improves the efficiency of the upstream bypass-controlled system at 10% load by 6.9%. The findings provide a theoretical framework for enhancing the low-load performance of supercritical CO₂ cycles.