Application of Artificial Neural Networks in the Urban Building Energy Modelling of Polish Residential Building Stock

被引：9

作者：

Zygmunt, Marcin ^{[1
]}

Gawin, Dariusz ^{[1
]}

机构：

[1] Tech Univ Lodz, Dept Bldg Mat Phys & Sustainable Design, PL-93590 Lodz, Poland

来源：

ENERGIES | 2021年 / 14卷 / 24期

关键词：

urban building energy modeling; Artificial Neural Network; energy clusters; Energy Flexible Building Clusters; energy efficiency; environmental impact; CONSUMPTION; SIMULATION; SECTOR; PERFORMANCE; SAVINGS; CITY; METHODOLOGY; VALIDATION; GENERATION; DEMAND;

D O I：

10.3390/en14248285

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

The development of energy-efficient buildings and sustainable energy supply systems is an obligatory undertaking towards a more sustainable future. To protect the natural environment, the modernization of urban infrastructure is indisputably important, possible to achieve considering numerous buildings as a group, i.e., Building Energy Cluster (BEC). The urban planning process evaluates multiple complex criteria to select the most profitable scenario in terms of energy consumption, environmental protection, or financial profitability. Thus, Urban Building Energy Modelling (UBEM) is presently a popular approach applied for studies towards the development of sustainable cities. Today's UBEM tools use various calculation methods and approaches, as well as include different assumptions and limitations. While there are several popular and valuable software for UBEM, there is still no such tool for analyses of the Polish residential stock. In this work an overview on the home-developed tool called TEAC, focusing on its' mathematical model and use of Artificial Neural Networks (ANN). An exemplary application of the TEAC software is also presented.

引用

页数：15

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