Steady-state operation dataset of an experimental Wet Cooling Tower pilot plant located at Plataforma Solar de Almería

Repository that contains experimental data obtained from a Wet Cooling Tower (WCT) plant located at Plataforma Solar de Almería. For the article "Wet cooling tower performance prediction in CSP plants: A comparison between artificial neural networks and Poppe’s model", three experimental campaigns were used, quoting from the article: A total of 132 steady-state experimental points have been obtained thanks to the thorough experimentation conducted. These data cover a large variety of ambient conditions (different seasons, days and nights) and thermal loads (from 27 kW to 207 kW). See README.md for a more detailed description and instructions on how to use the data. License CC BY 4.0. Attribution 4.0 International If the data is used as part of a scientific publication, please cite the source publication: Serrano, Juan Miguel, Pedro Navarro, Javier Ruiz, Patricia Palenzuela, Manuel Lucas, and Lidia Roca. “Wet Cooling Tower Performance Prediction in CSP Plants: A Comparison between Artificial Neural Networks and Poppe’s Model.” Energy 303 (September 15, 2024): 131844. https://doi.org/10.1016/j.energy.2024.131844.本仓库收录了取自阿尔梅里亚太阳能试验平台（Plataforma Solar de Almería）的湿式冷却塔（Wet Cooling Tower, WCT）试验装置所获取的实验数据。 为支撑论文《光热电站（Concentrated Solar Power, CSP）湿式冷却塔性能预测：人工神经网络与Poppe模型的对比研究》的研究工作，本次数据集采用了三项实验测试批次的数据，相关引用信息如下： 本次实验通过周密详尽的测试流程，共获取132组稳态实验数据点。这些数据覆盖了多样的环境工况（涵盖不同季节、昼夜时段）与热负荷工况（热负荷范围为27 kW至207 kW）。 如需了解数据集的详细说明与使用方法，请查看README.md文件。 本数据集采用CC BY 4.0（知识共享署名4.0国际许可协议）进行授权。 若将本数据集用于科学出版物中，请引用如下文献： 胡安·米格尔·塞拉诺、佩德罗·纳瓦罗、哈维尔·鲁伊斯、帕特里夏·帕伦苏埃拉、曼努埃尔·卢卡斯、莉迪亚·罗卡. 《光热电站湿式冷却塔性能预测：人工神经网络与Poppe模型的对比研究》[J]. Energy, 2024, 303: 131844. DOI: 10.1016/j.energy.2024.131844.