Estimation of energy savings for building retrofits using neural networks

被引：19

作者：

Krarti, M ^{[1
]}

Kreider, JF

Cohen, D

Curtiss, P

机构：

[1] Univ Colorado, Joint Ctr Energy Management, Boulder, CO 80309 USA

[2] Architectural Energy Corp, Boulder, CO 80301 USA

来源：

JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME | 1998年 / 120卷 / 03期

关键词：

D O I：

10.1115/1.2888071

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：

This paper overviews some applications of neural networks (NNs) to estimate energy and demand savings from retrofits of commercial buildings. First, a brief background information on NNs is provided. Then three specific case studies are described to illustrate how and when NNs can be used successfully to determine energy savings due to the implementation of various energy conservation measures in existing commercial buildings.

引用

页码：211 / 216

页数：6