This research introduces a novel approach specifically designed to improve the design of Concentrated Solar Power plants utilizing the Response Surface Methodology. The objective of the suggested methodology is to enhance energy production efficiency by simultaneously minimizing the levelized cost of electricity and the land footprint associated with the power plant while comparing three different cooling techniques: air, water, and hybrid. Two software tools, System Advisor Model and Design-Expert, are employed to validate the primary model, evaluate the responses, generate the predictive models, and verify the results. The configuration of a Concentrated Solar Power plant is influenced by four main factors: the size of the solar field (solar multiple), row spacing, number of solar assemblies per loop, and size of thermal energy storage. In this study, these factors are varied within the following ranges: solar multiple from 1 to 5, row spacing from 10 to 30 m, number of solar assemblies from 4 to 10 per loop, and thermal energy storage from 5 to 15 h. The generated predictive models demonstrated very high accuracy, particularly for the annual energy production, with an error ranging between 0.2% and 1.5%. The findings showed that the hybrid cooling system is the most cost-effective cooling technique and has the highest energy output compared to the evaporative and air-cooling methods. When optimizing the required area of the hybrid cooled plant with a reduction of 47.44%, the analysis indicated a minimal decrease in energy output of 3.61% and a slight increase in the levelized cost of electricity by 0.95%. According to the results, the effect of area on the annual energy production and levelized cost of electricity is significant below the optimal area, while this effect becomes minor at higher values.

中文翻译：

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使用响应面法对聚光太阳能进行建模和优化：空气、水和混合冷却技术的比较研究


这项研究引入了一种新颖的方法，专门用于利用响应面方法改进聚光太阳能发电厂的设计。建议方法的目标是通过比较三种不同的冷却技术：空气、水和混合冷却技术，同时最大限度地降低电力成本和与发电厂相关的土地足迹，从而提高能源生产效率。使用 System Advisor Model 和 Design-Expert 这两个软件工具来验证主要模型、评估响应、生成预测模型并验证结果。聚光型太阳能发电厂的配置受四个主要因素影响：太阳能场的大小（太阳能倍数）、行距、每环太阳能组件的数量以及热能存储的大小。在本研究中，这些因素在以下范围内变化：太阳能倍数从1到5，行间距从10到30 m，每个回路的太阳能组件数量从4到10个，热能存储从5到15小时。生成的预测模型显示出非常高的准确性，特别是对于年能源产量，误差范围在 0.2% 到 1.5% 之间。研究结果表明，与蒸发冷却和空气冷却方法相比，混合冷却系统是最具成本效益的冷却技术，并且具有最高的能量输出。当优化混合冷却设备所需面积减少 47.44% 时，分析表明能源输出最小减少 3.61%，平准化电力成本略有增加 0.95%。 结果表明，低于最佳面积时，面积对年能源产量和平准化电力成本的影响显着，而在较高值时，这种影响变得较小。