Zhou, Y., Paredes, A., Essayeh, C., & Morstyn, T. (2024). AI-focused HPC Data Centers Can Provide More Power Grid Flexibility and at Lower Cost. arXiv preprint arXiv:2410.17435.
This paper investigates the capability and cost of AI-focused HPC data centers in providing power grid flexibility compared to traditional general-purpose HPC data centers.
The researchers analyze real-world datasets from 7 AI-focused and 7 general-purpose HPC data centers, along with data from 3 cloud platforms. They develop optimization models to evaluate the maximum flexibility potential and associated cost for various power system services, considering factors like job scheduling, delay penalties, and cost scaling based on real-world pricing models.
The study highlights the significant potential of AI-focused HPC data centers in contributing to power grid stability and flexibility. Their inherent operational characteristics make them particularly well-suited for providing valuable grid services, potentially creating a win-win situation for both data center operators and power system stakeholders.
This research provides valuable insights for power grid operators seeking to leverage data center flexibility and for data center operators exploring new revenue streams and contributing to a more sustainable and resilient power grid.
The study acknowledges limitations regarding the assumption of a linear relationship between data center utilization and electric power. Future research could explore more complex power consumption models and investigate the impact of dynamic energy pricing on flexibility provision strategies.
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arxiv.org
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by Yihong Zhou,... ב- arxiv.org 10-24-2024
https://arxiv.org/pdf/2410.17435.pdfשאלות מעמיקות