TY - GEN
T1 - Day-ahead Time-sharing Optimal Scheduling for Community Integrated Energy System Based on Multi-energy Time-series Analysis
AU - Li, Peng
AU - Wang, Jiahao
AU - Zhang, Chunyan
AU - Wang, Nan
AU - Dou, Zhenlan
AU - Zhou, Xichao
AU - Wen, Miao
AU - Wang, Gang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Community integrated energy system (CIES) can give full play to the comprehensive advantages of multiple heterogeneous energy, and provide reliable and economical energy supply for users in the community by coordinating various energy equipment. However, in existing research, the scheduling plan of CIES is not arranged according to characteristics of equipment itself. Based on this consideration, this paper proposes a day-ahead optimal scheduling method for CIES based on multi-energy time-series analysis. First, unified scheduling model of CIES is established. Then, the complexity of the multi-energy time-series in CIES is analyzed based on fuzzy entropy, and the scheduling period is further divided according to the response speed of various energy equipment. Next, a day-ahead time-sharing optimal scheduling method for CIES is proposed. Finally, a case study is used to demonstrate the scheduling model, and simulation results show that the proposed method allows for efficient use of various equipment at a relatively small additional cost.
AB - Community integrated energy system (CIES) can give full play to the comprehensive advantages of multiple heterogeneous energy, and provide reliable and economical energy supply for users in the community by coordinating various energy equipment. However, in existing research, the scheduling plan of CIES is not arranged according to characteristics of equipment itself. Based on this consideration, this paper proposes a day-ahead optimal scheduling method for CIES based on multi-energy time-series analysis. First, unified scheduling model of CIES is established. Then, the complexity of the multi-energy time-series in CIES is analyzed based on fuzzy entropy, and the scheduling period is further divided according to the response speed of various energy equipment. Next, a day-ahead time-sharing optimal scheduling method for CIES is proposed. Finally, a case study is used to demonstrate the scheduling model, and simulation results show that the proposed method allows for efficient use of various equipment at a relatively small additional cost.
KW - community integrated energy system
KW - day-ahead optimal scheduling
KW - division of scheduling periods
KW - fuzzy entropy
KW - responsiveness
UR - https://www.scopus.com/pages/publications/85143403617
U2 - 10.1109/ICPSAsia55496.2022.9949883
DO - 10.1109/ICPSAsia55496.2022.9949883
M3 - Conference contribution
AN - SCOPUS:85143403617
T3 - I and CPS Asia 2022 - 2022 IEEE IAS Industrial and Commercial Power System Asia
SP - 738
EP - 743
BT - I and CPS Asia 2022 - 2022 IEEE IAS Industrial and Commercial Power System Asia
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE IAS Industrial and Commercial Power System Asia, I and CPS Asia 2022
Y2 - 8 July 2022 through 11 July 2022
ER -