Design of distributed energy system based on artificial neural network approach

被引：0
|
作者：
Zhou, Yingya [1 ]
Zhou, Zhe [1 ]
Jiang, Dongxiang [1 ]
机构：
[1] Tsinghua Univ, Dept Thermal Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
来源：
PROCEEDINGS OF THE 2013 FOURTH INTERNATIONAL CONFERENCE ON INTELLIGENT CONTROL AND INFORMATION PROCESSING (ICICIP) | 2013年
关键词：
OPTIMIZATION; EXTRACTION; BUILDINGS; ALGORITHM;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Designing distributed energy system (DES) is a complex task due to large varieties and combinations of energy generation, conversion, and storage technologies as well as time-varying energy supplies and demands. In this article, an artificial neural network (ANN) is trained by known DES design samples. Results have shown that after training, ANN can approximate the complex DES mathematical model and yield similar new DES designs to the mathematical model, given new conditions of energy supplies and demands. The advantages of using ANN to design DES lie in the simple structure of ANN and the learning ability from practical as well as updated samples.
引用
收藏
页码：437 / 442
页数：6
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