TY - JOUR
T1 - Managing data center cluster as non-wire alternative
T2 - A case in balancing market
AU - Cao, Yujie
AU - Cao, Fang
AU - Wang, Yajing
AU - Wang, Jianxiao
AU - Wu, Lei
AU - Ding, Zhaohao
N1 - Publisher Copyright:
© 2024
PY - 2024/4/15
Y1 - 2024/4/15
N2 - As the demand for Internet services continues to rise, large-scale Internet companies have expanded their data center infrastructure across multiple global regions. The inherent spatial-temporal flexibility in scheduling workloads allows data center clusters to dynamically adjust their power consumption without overloading the transmission network. In this work, we introduce a novel approach for treating a geo-distributed data center cluster as a non-wire alternative resource and explore its potential role in the energy balancing market. Our methodology manages a geographically distributed data center cluster as a balance-responsible entity by employing optimal workload scheduling that considers its inherent spatial-temporal flexibility and market arbitrage opportunities. To achieve this, we develop a two-layer stochastic receding horizon control optimization algorithm to formulate a strategic bidding strategy for the data center cluster. To validate the effectiveness of our proposed approach, we conduct numerical experiments using real-world data center production traces and data from the Nordic balancing market, demonstrating its practical applicability and performance.
AB - As the demand for Internet services continues to rise, large-scale Internet companies have expanded their data center infrastructure across multiple global regions. The inherent spatial-temporal flexibility in scheduling workloads allows data center clusters to dynamically adjust their power consumption without overloading the transmission network. In this work, we introduce a novel approach for treating a geo-distributed data center cluster as a non-wire alternative resource and explore its potential role in the energy balancing market. Our methodology manages a geographically distributed data center cluster as a balance-responsible entity by employing optimal workload scheduling that considers its inherent spatial-temporal flexibility and market arbitrage opportunities. To achieve this, we develop a two-layer stochastic receding horizon control optimization algorithm to formulate a strategic bidding strategy for the data center cluster. To validate the effectiveness of our proposed approach, we conduct numerical experiments using real-world data center production traces and data from the Nordic balancing market, demonstrating its practical applicability and performance.
KW - Balancing mechanism
KW - Data center
KW - Demand response
KW - Energy management
KW - Power market
UR - http://www.scopus.com/inward/record.url?scp=85183965151&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85183965151&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2024.122769
DO - 10.1016/j.apenergy.2024.122769
M3 - Article
AN - SCOPUS:85183965151
SN - 0306-2619
VL - 360
JO - Applied Energy
JF - Applied Energy
M1 - 122769
ER -