Supercritical CO₂ (sCO₂) Brayton cycle is a promising technology for coal-fired power generation with high efficiency and compact equipment size. However, its sophisticated construct and high-temperature waste heat rejection require a systematic design to maximize its performance. Herein, we develop a combined sCO₂ Brayton cycle-organic Rankine cycle (ORC) design for coal-fired power plant. A novel glass-box model that considers the specific designs of sCO₂ boiler, recuperators, coolers, and turbomachinery is formulated to optimize the power plant. A high-accuracy artificial neural network model is also developed to estimate the system’s pressure drop to reduce model complexity. As a result, the glass-box model is reformulated into a grey-box model. The model is applied to three different combined cycles’ design problem to evaluate their performance. Result shows that the grey-box model saves more than 50% of CPU time. With the turbine inlet at 620 °C/25 MPa and the main compressor inlet at 35 °C/7.38 MPa, the proposed combined cycle reaches a thermal efficiency of 45.73%, thereby achieving a 2.75 percentage point improvement compared with the standalone design. Sensitivity analysis is also carried out to evaluate the effects of ORC working fluid, flue gas temperature at the cooling wall outlet, main compressor inlet pressure, and evaporating temperature of ORC, on the system’s performance.

超临界CO ₂ (sCO ₂ )布雷顿循环是一种具有高效率和紧凑设备尺寸的燃煤发电技术。然而，其复杂的构造和高温废热排放需要系统化的设计以最大限度地提高其性能。在此，我们为燃煤电厂开发了 sCO ₂布雷顿循环-有机朗肯循环 (ORC) 组合设计。考虑 sCO ₂特定设计的新型玻璃盒模型锅炉、换热器、冷却器和涡轮机械的配方是为了优化发电厂。还开发了高精度人工神经网络模型来估计系统的压降以降低模型复杂度。因此，玻璃盒模型被重新表述为灰盒模型。该模型被应用于三个不同的联合循环的设计问题来评估它们的性能。结果表明，灰盒模型节省了 50% 以上的 CPU 时间。在涡轮进口温度为 620 °C/25 MPa 和主压气机进口温度为 35 °C/7.38 MPa 的情况下，所提出的联合循环热效率达到 45.73%，从而与独立设计相比提高了 2.75 个百分点。还进行了敏感性分析，以评估 ORC 工质、冷却壁出口烟气温度、