Low-carbon economic scheduling for multiple data centers considering spatiotemporal migration characteristics of computing loads

English Version Journal Login

您当前的位置：

首页 >

文章列表页 >

System Scheduling & Low-Carbon Operation | 更新时间：2026-09-17

- Low-carbon economic scheduling for multiple data centers considering spatiotemporal migration characteristics of computing loads
- BLASTING Vol. 48, Issue 9, Pages: 84-95(2026)
- 作者机构：
  
  1.山东大学电气工程学院，济南 250061
  2.山东电力工程咨询院有限公司，济南 250013
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(52377108)
- DOI：10.3969/j.issn.2097-0706.2026.09.007
  CLC：
- Received：03 August 2026，
  
  Revised：2026-08-10，
  
  Online First：13 August 2026，
  
  Published：25 September 2026
- 稿件说明：
移动端阅览
付利卓,王成福,鲁浩等.考虑算力负载时空迁移特性的多数据中心低碳经济调度[J].综合智慧能源,2026,48(09):84-95.

FU Lizhuo,WANG Chengfu,LU Hao,et al.Low-carbon economic scheduling for multiple data centers considering spatiotemporal migration characteristics of computing loads[J].BLASTING,2026,48(09):84-95.
付利卓,王成福,鲁浩等.考虑算力负载时空迁移特性的多数据中心低碳经济调度[J].综合智慧能源,2026,48(09):84-95. DOI： 10.3969/j.issn.2097-0706.2026.09.007.

FU Lizhuo,WANG Chengfu,LU Hao,et al.Low-carbon economic scheduling for multiple data centers considering spatiotemporal migration characteristics of computing loads[J].BLASTING,2026,48(09):84-95. DOI： 10.3969/j.issn.2097-0706.2026.09.007.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Operational optimization of multi-energy microgrids for data centers considering flexibility of computing loads and cold energy storage

Cross-park computing-electricity bilateral matching driven by Bayesian reputation and diffusion-policy potential game

Deep reinforcement learning method for energy-computing coordinated scheduling in integrated energy systems considering flexible data center tasks

Review of flexibility and adjustable potential quantification of transportation and computing loads for green power accommodation

Theoretical foundation， system architecture， and operational mode of integration of computing infrastructure and new power systems

Related Author

DU Yuhao

YAN Rujing

LI Menglan

CHENG Lefeng

YU Feng

SUN Runbao

ZOU Tao

QU Xinmei

Related Institution

Guizhou Jiangyuan Electric Power Construction Company Limited

College of Electrical Engineering， Guizhou University

School of Mechanical and Electrical Engineering，Guangzhou University

State Key Laboratory for Grid Disaster Prevention and Mitigation，Changsha University of Science and Technology

School of Electrical and Information Engineering，Changsha University of Science and Technology

AI导读

AI脑图

AI问答

⁰