TY - JOUR
T1 - A case study of operation optimization on a renewable energy building by E-CPS method
T2 - 10th International Conference on Applied Energy, ICAE 2018
AU - Zhong, Shengyuan
AU - Deng, Shuai
AU - Zhao, Jun
AU - Wang, Yongzhen
AU - Su, Pengwei
N1 - Publisher Copyright:
© 2019 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of ICAE2018 - The 10th International Conference on Applied Energy.
PY - 2019
Y1 - 2019
N2 - The energy system's operation strategy has a significant influence on the system efficiency. The determination of the optimal operation strategy requires the effective application of a substantial amount of data accumulated from the operation or even forecasting process. However, data processing, which is not obtained based on the physical mechanism, may fail to explain, under certain boundary conditions. Therefore, using E-CPS to combine data mining and physical model to build a more efficient and accurate model or even a real-time model is vital and has received more attention in practical applications. This paper proposes a general process for constructing E-CPS and applies it to the simulation of building energy systems. The E-CPS results in a 70% reduction in the renewable energy waste rate of the building's energy system and a 57% reduction in the purchase of electricity. Finally, it is concluded that the use of intelligent algorithm-based data mining combined with physical models to build E-CPS is practical and effective.
AB - The energy system's operation strategy has a significant influence on the system efficiency. The determination of the optimal operation strategy requires the effective application of a substantial amount of data accumulated from the operation or even forecasting process. However, data processing, which is not obtained based on the physical mechanism, may fail to explain, under certain boundary conditions. Therefore, using E-CPS to combine data mining and physical model to build a more efficient and accurate model or even a real-time model is vital and has received more attention in practical applications. This paper proposes a general process for constructing E-CPS and applies it to the simulation of building energy systems. The E-CPS results in a 70% reduction in the renewable energy waste rate of the building's energy system and a 57% reduction in the purchase of electricity. Finally, it is concluded that the use of intelligent algorithm-based data mining combined with physical models to build E-CPS is practical and effective.
KW - Building energy system
KW - Cyber physical system
KW - Data mining
KW - Energy cyber physical system
KW - Renewable energy
UR - http://www.scopus.com/inward/record.url?scp=85063909954&partnerID=8YFLogxK
U2 - 10.1016/j.egypro.2019.01.496
DO - 10.1016/j.egypro.2019.01.496
M3 - Conference article
AN - SCOPUS:85063909954
SN - 1876-6102
VL - 158
SP - 6145
EP - 6151
JO - Energy Procedia
JF - Energy Procedia
Y2 - 22 August 2018 through 25 August 2018
ER -