Concentrated solar power (CSP) plants using dense particle suspension as heat transfer fluid and particles as the storage medium are considered as a promising solution to provide the high temperature required for the supercritical carbon dioxide (S-CO₂) Brayton cycle. During plant operation, variations in the heat transfer fluid temperature and ambient temperature would significantly affect system performance. Determining the suitable S-CO₂ Brayton cycle configuration for this particle-based CSP plant requires accurate prediction and comprehensive comparison on the system performance both at design and off-design conditions. This study presents a common methodology to homogeneously assess the plant performance for six 10 MW S-CO₂ Brayton cycles (i.e. simple regeneration, recompression, precompression, intercooling, partial cooling and split expansion) integrated with a hot particles thermal energy storage and a dry cooling system. This methodology includes both design and off-design detailed models based on the characteristic curves of all components. The optimal design for each thermodynamic cycle has been determined under the same boundary design constrains by a genetic algorithm. Then, their off-design performances have been quantitatively compared under varying particle inlet temperature and ambient temperature, in terms of cycle efficiency, net power output and specific work. Results show that the variation in ambient temperature contributes to a greater influence on the cycle off-design performance than typical variations of the heat transfer fluid temperature. Cycles with higher complexity have larger performance deterioration when the ambient temperature increases, though they could present higher peak efficiency and specific work at design-point. In particular, the cycle with maximum efficiency or specific work presents significant changes in different ranges of ambient temperature. This means that for the selection of the best configuration, the typical off-design operation conditions should be considered as well. For integrating with high-temperature CSP plants and dry cooling systems, the simple regeneration and the recompression cycles are the most suitable S-CO₂ Brayton cycle configurations due to their fewer performance degradations at ambient temperatures above 30 °C, which is a frequent environmental condition in sunny areas of the world.

使用密集的颗粒悬浮液作为传热流体并将颗粒作为存储介质的集中式太阳能发电厂（CSP）被认为是提供超临界二氧化碳（S-CO ₂）布雷顿循环所需的高温的有前途的解决方案。在工厂运行期间，传热流体温度和环境温度的变化会严重影响系统性能。为该基于粒子的CSP工厂确定合适的S-CO ₂布雷顿循环配置需要在设计和非设计条件下进行准确的预测并全面比较系统性能。这项研究提出了一种通用方法，可以对六个10 MW S-CO ₂的电厂性能进行均质评估布雷顿循环（即简单的再生，再压缩，预压缩，中间冷却，部分冷却和分流膨胀）与热颗粒热能存储和干式冷却系统集成在一起。该方法论包括基于所有组件特征曲线的设计和非设计详细模型。已经通过遗传算法在相同的边界设计约束下确定了每个热力学循环的最佳设计。然后，在循环效率，净功率输出和比功方面，在变化的颗粒入口温度和环境温度下，对它们的非设计性能进行了定量比较。结果表明，与传热流体温度的典型变化相比，环境温度的变化对循环非设计性能的影响更大。当环境温度升高时，具有较高复杂度的循环虽然性能可能会更高，但在设计点可能会表现出更高的峰值效率和特定工作。特别是，效率最高或特定工作的循环会在不同的环境温度范围内发生重大变化。这意味着，为了选择最佳配置，还应考虑典型的非设计运行条件。与高温CSP设备和干式冷却系统集成时，简单的再生和再压缩循环是最合适的S-CO 以最高效率或特定工作进行的循环会在不同的环境温度范围内发生重大变化。这意味着，为了选择最佳配置，还应考虑典型的非设计运行条件。与高温CSP设备和干式冷却系统集成时，简单的再生和再压缩循环是最合适的S-CO 以最高效率或特定工作进行的循环会在不同的环境温度范围内发生重大变化。这意味着，为了选择最佳配置，还应考虑典型的非设计运行条件。与高温CSP设备和干式冷却系统集成时，简单的再生和再压缩循环是最合适的S-CO₂ Brayton循环配置，因为它们在30°C以上的环境温度下性能下降较少，这是世界上阳光充足的地区经常发生的环境条件。