A low-carbon optimal operation method for active distribution grids considering the spatial-temporal flexibility of data center

In recent years, the power consumption of data centers (DCs) has been growing rapidly. Leveraging the spatial and temporal adjustability of DC data loads can provide flexible and interactive resources for the power system, thereby enhancing the utilization of renewable energy on the grid and advancing low-carbon goals. This paper begins by examining the efficient integration of DC and distribution grids in the context of carbon neutrality and proposes an optimization method aimed at maximizing the synergistic efficiency of both systems. Building on a thorough analysis of the operational characteristics of various data loads, we develop a spatial-temporal flexibility model for DC and assess the real-time adjustable potential of DC loads. The optimization model focuses on minimizing both system investment and operational costs, as well as reducing carbon emissions. Ultimately, we construct a low-carbon operational optimization model for the distribution grid that incorporates the spatial and temporal flexibility of DC. To illustrate the effectiveness of the proposed model, we conduct simulation and analysis using the modified IEEE-33 system as a case study.

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Publication Details

Journal
IET conference proceedings.
Published
2025-03-01
DOI
https://doi.org/10.1049/icp.2025.0378
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

A low-carbon optimal operation method for active distribution grids considering the spatial-temporal flexibility of data center

Houqi Dong, Jiangang Lu, Wenxin Guo, Ruifeng Zhao
IET conference proceedings.
Distributed and Parallel Computing Systems
article

A low-carbon optimal operation method for active distribution grids considering the spatial-temporal flexibility of data center

Houqi Dong, Jiangang Lu, Wenxin Guo, Ruifeng Zhao
article en

Abstract

In recent years, the power consumption of data centers (DCs) has been growing rapidly. Leveraging the spatial and temporal adjustability of DC data loads can provide flexible and interactive resources for the power system, thereby enhancing the utilization of renewable energy on the grid and advancing low-carbon goals. This paper begins by examining the efficient integration of DC and distribution grids in the context of carbon neutrality and proposes an optimization method aimed at maximizing the synergistic efficiency of both systems. Building on a thorough analysis of the operational characteristics of various data loads, we develop a spatial-temporal flexibility model for DC and assess the real-time adjustable potential of DC loads. The optimization model focuses on minimizing both system investment and operational costs, as well as reducing carbon emissions. Ultimately, we construct a low-carbon operational optimization model for the distribution grid that incorporates the spatial and temporal flexibility of DC. To illustrate the effectiveness of the proposed model, we conduct simulation and analysis using the modified IEEE-33 system as a case study.

IET conference proceedings.Vol. 2024(33)
China Southern Power Grid (China) (CN), Tsinghua University (CN)
Openalex Percentile: Top 96%
Distributed and Parallel Computing Systems
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