TY - JOUR
T1 - A multicriteria optimal operation framework for a data center microgrid considering renewable energy and waste heat recovery
T2 - Use of balanced decision making
AU - Li, Yuanzheng
AU - Huang, Jingjing
AU - Liu, Yun
AU - Wang, Hao
AU - Wang, Yongzhen
AU - Ai, Xiaomeng
N1 - Funding Information:
This work is supported in part by the National Natural Science Foundation of China under Grants 62073148 and 62233006 and in part by the Open Project of the Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology, Ministry of Education, Northeast Electric Power University under Grant MPSS2022-04.
Publisher Copyright:
© 1975-2012 IEEE.
PY - 2023/7
Y1 - 2023/7
N2 - The rapid development of data centers (DCS) leads to a huge challenge in their energy consumption and environmental impact. It is promising to establish DC microgrids (DCMGs) for solving these issues, considering utilizing renewable energy (RE) generation and waste heat recovery systems. However, the efficient energy management of a DCMG is a topic to be pursued. In this article, we propose a multicriteria optimal operation framework for the DCMG by coordinatively scheduling the energy supply and demand. In this framework, multiple criteria are comprehensively considered via a multicriteria optimization (MCO) approach. Then, we adopt an augmented E-constraint algorithm to address the corresponding MCO problem. Afterward, a balanced decision-making (BDM) method is further proposed to determine the optimal scheduling solution. Finally, a case study and results analysis verify the effectiveness of the proposed multicriteria optimal operation framework for the DCMG.
AB - The rapid development of data centers (DCS) leads to a huge challenge in their energy consumption and environmental impact. It is promising to establish DC microgrids (DCMGs) for solving these issues, considering utilizing renewable energy (RE) generation and waste heat recovery systems. However, the efficient energy management of a DCMG is a topic to be pursued. In this article, we propose a multicriteria optimal operation framework for the DCMG by coordinatively scheduling the energy supply and demand. In this framework, multiple criteria are comprehensively considered via a multicriteria optimization (MCO) approach. Then, we adopt an augmented E-constraint algorithm to address the corresponding MCO problem. Afterward, a balanced decision-making (BDM) method is further proposed to determine the optimal scheduling solution. Finally, a case study and results analysis verify the effectiveness of the proposed multicriteria optimal operation framework for the DCMG.
UR - http://www.scopus.com/inward/record.url?scp=85153329221&partnerID=8YFLogxK
U2 - 10.1109/MIAS.2023.3261105
DO - 10.1109/MIAS.2023.3261105
M3 - Article
AN - SCOPUS:85153329221
SN - 1077-2618
VL - 29
SP - 23
EP - 38
JO - IEEE Industry Applications Magazine
JF - IEEE Industry Applications Magazine
IS - 4
ER -
