TY - JOUR
T1 - A cloud-edge cooperative scheduling model and its optimization method for regional multi-energy systems
AU - Liu, Shuo
AU - Teng, Yun
AU - Cheng, Song Qing
AU - Xu, Ning Wei
AU - Sun, Peng
AU - Zhang, Kun
AU - Chen, Zhe
N1 - Copyright © 2024 Liu, Teng, Cheng, Xu, Sun, Zhang and Chen.
PY - 2024
Y1 - 2024
N2 - In the process of multi-energy system optimal scheduling, due to the high data processing requirements of the multi-energy devices and loads and the complexity of the operating states of the multi-energy devices, the scheduling optimization of the system is to some extent more difficult. To address this problem, this paper proposes a regional multi-energy system optimal scheduling model based on the theory of cloud-edge collaboration. First, based on intelligent data sensors, a cloud-edge cooperative scheduling framework of the regional multi-energy system is constructed. Then, the physical model of operating state data of multi-energy system equipment and the allocation mechanism of system scheduling tasks are studied. With the cloud service application layer and the edge computing layer as the upper and lower optimization scheduling layers, the double-layer optimization scheduling model of the regional multi-energy system is established. The objectives of the model are optimal scheduling cost and minimum delay of scheduling data transmission. The multi-objective whale optimization algorithm is used to solve the model. Finally, a simulation model is built for verification. The simulation results show that the scheduling model established in this paper can effectively improve the scheduling data processing capability and improve the economy of regional multi-energy system scheduling.
AB - In the process of multi-energy system optimal scheduling, due to the high data processing requirements of the multi-energy devices and loads and the complexity of the operating states of the multi-energy devices, the scheduling optimization of the system is to some extent more difficult. To address this problem, this paper proposes a regional multi-energy system optimal scheduling model based on the theory of cloud-edge collaboration. First, based on intelligent data sensors, a cloud-edge cooperative scheduling framework of the regional multi-energy system is constructed. Then, the physical model of operating state data of multi-energy system equipment and the allocation mechanism of system scheduling tasks are studied. With the cloud service application layer and the edge computing layer as the upper and lower optimization scheduling layers, the double-layer optimization scheduling model of the regional multi-energy system is established. The objectives of the model are optimal scheduling cost and minimum delay of scheduling data transmission. The multi-objective whale optimization algorithm is used to solve the model. Finally, a simulation model is built for verification. The simulation results show that the scheduling model established in this paper can effectively improve the scheduling data processing capability and improve the economy of regional multi-energy system scheduling.
KW - cloud-edge collaboration
KW - edge computing
KW - optimized scheduling
KW - physical perception
KW - regional multi-energy system
UR - http://www.scopus.com/inward/record.url?scp=85189859467&partnerID=8YFLogxK
U2 - 10.3389/fenrg.2024.1372612
DO - 10.3389/fenrg.2024.1372612
M3 - Journal article
AN - SCOPUS:85189859467
SN - 2296-598X
VL - 12
JO - Frontiers in Energy Research
JF - Frontiers in Energy Research
M1 - 1372612
ER -