load scheduling
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2022 ◽  
Vol 71 (2) ◽  
pp. 4101-4114
Author(s):  
R. Joshua Samuel Raj ◽  
V. Ilango ◽  
Prince Thomas ◽  
V. R. Uma ◽  
Fahd N. Al-Wesabi ◽  
...  


2021 ◽  
pp. 1-16
Author(s):  
M. L. Merlin Sajini ◽  
S. Suja ◽  
S. Merlin Gilbert Raj ◽  
S. Kowsalyadevi ◽  
Charisma Maria


2021 ◽  
Vol 252 ◽  
pp. 111399
Author(s):  
Jing Wang ◽  
Sen Huang ◽  
Wangda Zuo ◽  
Draguna Vrabie


2021 ◽  
Vol 7 ◽  
pp. 4705-4721
Author(s):  
Ahmed Shaban ◽  
Hagag Maher ◽  
Mahmoud Elbayoumi ◽  
Suzan Abdelhady


2021 ◽  
Vol 2042 (1) ◽  
pp. 012091
Author(s):  
Nuoa Lei ◽  
Zhu Cheng ◽  
Zhi Cao ◽  
Eric Masanet

Abstract Intelligent load scheduling is an emerging approach that has the potential to facilitate extreme sustainable data center (DC) operation. However, scarcity of straightforward tools in the public domain challenges decision makers performing quantitative analysis of the DC load planning and its potential benefits. In this work, a novel integrated decision-making framework was developed to address this issue, which provides the basis for the multi-objective optimization of carbon-, water-, and economic-intelligent load scheduling. The proposed framework was demonstrated with a case study DC in California, which showed the usefulness of the proposed framework in informing sustainable DC operations.



2021 ◽  
Author(s):  
Lekshmi R Chandran ◽  
Nikhil Jayagopal ◽  
Lekshmi Shyma Lal ◽  
Chaithanya Narayanan ◽  
S Deepak ◽  
...  


Author(s):  
Kewen Lu ◽  
Xuelin Liu ◽  
Zhongliang Ai ◽  
Zhonglin Liu ◽  
Dan Tao ◽  
...  


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