Predictive Control of Enterprise Energy Management System

DOI

10.2991/icmeit-19.2019.89How to use a DOI?

Keywords

Energy Management System; Predictive; Neural Network.

Abstract

Industries and large-scale public building are one of the main power Energy consumers in China, where they consume about 70% of all the energy in the country. Different types of industrial processing techniques, equipment, product types, ways of energy management can have different influences on energy consumption. This paper suggests using BP Neural Network to scientifically predict business energy consumption, and models and analyzes consumption amount, enable the business energy manager to predict business energy consumption trend, advise business producing, fixing, and balancing, thus guarantee a balance between energy supply and demand.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nan Li
AU  - Jinsheng Qi
PY  - 2019/04
DA  - 2019/04
TI  - Predictive Control of Enterprise Energy Management System
BT  - Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SP  - 562
EP  - 565
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.89
DO  - 10.2991/icmeit-19.2019.89
ID  - Li2019/04
ER  -