Luo Yongqiang, Yan Tian, Zhang Nan
School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
School of Architecture and Art, Central South University, Changsha, Hunan, 410083, China.
Energy (Oxf). 2020 Oct 1;208:118413. doi: 10.1016/j.energy.2020.118413. Epub 2020 Jul 26.
Thermoelectric radiant panel system (TERP), requires no hydronic pipes, pumps and chillers and the size is compact in solid form. In this study, the main results include a new system model of TERP and some new findings on the system dynamic characteristics. The new model integrates finite difference method and state-space matrix, which is an integration of great simulation accuracy, high speed, and easy implementation. The thermal response time (TRT) and its asynchronism are confirmed and a new concept of AM (Asynchronism Magnitude) is defined to measure the degree of TRT asynchronism. Some new observations are obtained: (1) Under a certain environment, AM becomes a constant even when different step changes of current are imposed; (2) The TRT asynchronism disappeared at the second stage when environmental condition is step changed. Three new definitions of TRT are proposed and compared. Finally, in order to realize the fast and accurate prediction of TRT for the use of system on-line control or fast evaluation under dynamic state, an artificial neural network-based model is proved to be effective. The dynamic analysis can offer a new paradigm to the evaluation, control and optimization of radiant cooling and other dynamic systems.
热电辐射板系统（TERP）无需循环水管、水泵和冷水机组，且固态形式尺寸紧凑。本研究的主要成果包括TERP的一种新系统模型以及关于该系统动态特性的一些新发现。新模型整合了有限差分法和状态空间矩阵，具有模拟精度高、速度快且易于实现的特点。热响应时间（TRT）及其异步性得到了证实，并定义了一个新的AM（异步幅度）概念来衡量TRT异步程度。获得了一些新的观察结果：（1）在一定环境下，即使施加不同的电流阶跃变化，AM也会变为常数；（2）当环境条件发生阶跃变化时，TRT异步性在第二阶段消失。提出并比较了TRT的三个新定义。最后，为了实现对TRT的快速准确预测以用于系统在线控制或动态状态下的快速评估，基于人工神经网络的模型被证明是有效的。动态分析可为辐射制冷及其他动态系统的评估、控制和优化提供一种新的范例。
