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储能系统技术
★ 5.0
基于反应波模型的吸附式热能储存反应器性能预测方法
Prediction method of adsorption thermal energy storage reactor performances based on reaction wave model
| 作者 | Shichao Gao · Shugang Wang · Peiyu Hu · Jihong Wang |
| 期刊 | Applied Energy |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 377 卷 |
| 技术分类 | 储能系统技术 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | The prediction method of ATES reactor performances was proposed. |
语言:
中文摘要
摘要 吸附式热能储存(ATES)是实现太阳能高效利用的最重要途径之一。目前缺乏有效的反应器性能预测方法,严重制约了ATES系统的应用。本文提出了一种基于吸附反应波模型的反应器性能预测方法。通过引入吸附速率波的波参数,推导出反应器性能与设计参数之间的表达式,分别建立了设计参数与波参数之间、波参数与反应器性能之间的数学关系。开展了以沸石-水蒸气为工质对的吸附式热能储存实验,测量了反应器进出口处的空气温度和比湿度,并由此获得了相应的吸附量、储存热能及稳定输出功率。将所提出方法对反应器性能的预测结果与实验数据进行了对比分析。结果表明,该预测方法能够准确预测反应器性能,最大偏差小于6.0%。此外,该方法在简便性和通用性方面优于现有的其他预测方法。
English Abstract
Abstract Adsorption thermal energy storage (ATES) is one of the most important ways to achieve efficient utilization of solar energy. The lack of effective prediction methods of reactor performance severely restricts the application of the ATES system . In this paper, the prediction method of reactor performance was proposed based on the adsorption reaction wave model. The expressions between the reactor performances and the design parameters were derived by using the wave parameters of the adsorption rate wave. The mathematical relationships of design parameters-wave parameters and wave parameters-reactor performances were established, respectively. The experiments on adsorption thermal energy storage were performed, in which the zeolite-water vapor was determined as the working pairs. The air temperature and specific humidity at the inlet and outlet of the reactor were measured, and corresponding adsorption amount, thermal energy and stable output power were obtained. A comparison of the predictions for the reactor performances with experiments was carried out. The results indicated that the proposed prediction method was capable of accurately predicting the reactor performances, with a maximum deviation of less than 6.0 %. Moreover, the proposed prediction method is superior to available methods in terms of simplicity and generality.
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SunView 深度解读
该吸附储热反应波预测方法对阳光电源ST系列储能系统及PowerTitan产品具有重要参考价值。通过建立设计参数-波动参数-反应器性能的数学关系,可优化储能系统热管理策略,提升电池温控精度。该方法预测偏差小于6%的高精度特性,可集成至iSolarCloud平台实现储能电站热失控预警与预测性维护。特别适用于光储一体化场景中PCS功率器件的散热优化设计,延长SiC/GaN器件寿命,提升系统能量转换效率与安全性。