TY - JOUR
T1 - Feed-forward active operation optimization for CCHP system considering thermal load forecasting
AU - Kang, Ligai
AU - Yuan, Xiaoxue
AU - Sun, Kangjie
AU - Zhang, Xu
AU - Zhao, Jun
AU - Deng, Shuai
AU - Liu, Wei
AU - Wang, Yongzhen
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/9/1
Y1 - 2022/9/1
N2 - Using simulated load obtained by energy consumption simulation software is a feasible way to optimize operation of combined cooling heating and power (CCHP) system. However, due to attenuation and delay of thermal energy on transmission, there may be a mismatch between real demand and supplied energy. To obtain more accurate assessment of supplied energy, this paper analyzes characteristics of thermal load through correlation analysis and principal component analysis. Then, the model of thermal load forecasting considering attenuation and delay on transmission is constructed and a case study with actual monitored data in an energy system is employed. Finally, a method of feed-forward active operation optimization for CCHP system is put forward. Based on forecasted thermal load on weekday and weekend in heating, transition and cooling season, dynamic matching optimization and evaluation were carried out. Results show that mean absolute percentage error are 5.43% for heating load forecasting and 6.84% for cooling load forecasting, respectively. The performances of CCHP system are better than that of separate system based on the forecasted thermal load and the maximum integrated performance index is 68.81%, obtained at weekend in cooling season.
AB - Using simulated load obtained by energy consumption simulation software is a feasible way to optimize operation of combined cooling heating and power (CCHP) system. However, due to attenuation and delay of thermal energy on transmission, there may be a mismatch between real demand and supplied energy. To obtain more accurate assessment of supplied energy, this paper analyzes characteristics of thermal load through correlation analysis and principal component analysis. Then, the model of thermal load forecasting considering attenuation and delay on transmission is constructed and a case study with actual monitored data in an energy system is employed. Finally, a method of feed-forward active operation optimization for CCHP system is put forward. Based on forecasted thermal load on weekday and weekend in heating, transition and cooling season, dynamic matching optimization and evaluation were carried out. Results show that mean absolute percentage error are 5.43% for heating load forecasting and 6.84% for cooling load forecasting, respectively. The performances of CCHP system are better than that of separate system based on the forecasted thermal load and the maximum integrated performance index is 68.81%, obtained at weekend in cooling season.
KW - CCHP system
KW - Integrated performance
KW - Load forecasting
KW - Operation optimization
UR - http://www.scopus.com/inward/record.url?scp=85131123706&partnerID=8YFLogxK
U2 - 10.1016/j.energy.2022.124234
DO - 10.1016/j.energy.2022.124234
M3 - Article
AN - SCOPUS:85131123706
SN - 0360-5442
VL - 254
JO - Energy
JF - Energy
M1 - 124234
ER -
