Choosing the Right Battery Model for Data Center Simulations

TL;DR

This paper compares four battery models within a co-simulation framework for data centers, finding linear models offer a good balance of speed and accuracy, while simple models are less reliable.

Contribution

It introduces and evaluates four different battery models for data center simulations, highlighting the effectiveness of linear models in balancing realism and computational efficiency.

Findings

Linear models closely match physics-based models in short-term experiments.

Linear models are faster and easier to configure than complex physics-based models.

Simple lossless models are inadequate for accurate data center battery simulation.

Abstract

As demand for computing resources continues to rise, the increasing cost of electricity and anticipated regulations on carbon emissions are prompting changes in data center power systems. Many providers are now operating compute nodes in microgrids, close to renewable power generators and energy storage, to maintain full control over the cost and origin of consumed electricity. Recently, new co-simulation testbeds have emerged that integrate domain-specific simulators to support research, development, and testing of such systems in a controlled environment. Yet, choosing an appropriate battery model for data center simulations remains challenging, as it requires balancing simulation speed, realism, and ease of configuration. In this paper, we implement four different battery models for data center scenarios within the co-simulation framework Vessim and analyze their behavior. The results show that linear models, which consider inefficiencies and power limits, closely match the behavior of complex physics-based models in short-term experiments while offering faster execution, and not requiring knowledge on electrochemical reactions and circuit-level dynamics. In contrast, simple, lossless models fail to accurately represent complex behavior and provide no further runtime advantage.