Computer Supported Data-driven Decisions for Service Personalization: A Variable-Scale Clustering Method

Ai WANG¹, Xuedong GAO¹, Mincong TANG^2*
¹Donlinks School of Economics and Management, University of Science and Technology Beijing,
No. 30 Xueyuan Road, Beijing, 100083, China
ai.wang@uta.edu, gaoxuedong@manage.ustb.edu.cn
²The International Center for Informatics Research, Beijing Jiaotong University,
No. 3, Shangyuancun, Haidian, Beijing, 100044, China
Mincong@bjtu.edu.cn (^*Corresponding author)

Abstract: Currently, dynamical heat transfer models of the District Heating (DH) systems are needed to synthesize different types of smart building controllers. Such controllers are designed in such a way as to increase energy savings and provide highly flexible and more efficient DH systems. In this work, the complete analysis, the modelling, and the simulation of a DH thermal solar system have been investigated. A Complete mathematical modelling of the DH system components has been carried out for both the transient and steady state parts. The generated mathematical heat transfer model of the DH system has been first verified and validated through computer simulations, and it has been complemented by real collected environmental data in order to validate the derived heat transfer model. Finally, a small-scale DH system has been built and tested to validate the computer simulations, which has also been used to test a simple ON/OFF as a control strategy for the DH thermal solar system.

Keywords: District Heating, DH, Thermal solar Modelling, Heat Transfer Model, Switching Control, Transient Response.

>>FULL TEXT: PDF

CITE THIS PAPER AS:
Ai WANG, Xuedong GAO, Mincong TANG, Computer Supported Data-driven Decisions for Service Personalization: A Variable-Scale Clustering Method, Studies in Informatics and Control, ISSN 1220-1766, vol. 29(1), pp. 55-65, 2020. https://doi.org/10.24846/v29i1y202006