Optimizing microgrid composition for sustainable data centers

As computing energy demand continues to grow and electrical grid infrastructure struggles to keep pace, an increasing number of data centers are being planned with colocated microgrids that integrate on-site renewable generation and energy storage. However, while existing research has examined the tradeoffs between operational and embodied carbon emissions in the context of renewable energy certificates, there is a lack of tools to assess how the sizing and composition of microgrid components affects long-term sustainability and power reliability. In this paper, we present a novel optimization framework that extends the computing and energy system co-simulator Vessim with detailed renewable energy generation models from the National Renewable Energy Laboratory’s (NREL) System Advisor Model (SAM). Our framework simulates the interaction between computing workloads, on-site renewable production, and energy storage, capturing both operational and embodied emissions. We use a multi-horizon black-box optimization to explore efficient microgrid compositions and enable operators to make more informed decisions when planning energy systems for data centers.

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Publication Details

Journal
DepositOnce
Published
2025-11-15
DOI
https://doi.org/10.14279/depositonce-24978
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
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Optimizing microgrid composition for sustainable data centers

Jonathan Bader, Odej Kao, Julius Irion, Philipp Wiesner
DepositOnce
Cloud Computing and Resource Management
article

Optimizing microgrid composition for sustainable data centers

Jonathan Bader, Odej Kao, Julius Irion, Philipp Wiesner
article en

Abstract

As computing energy demand continues to grow and electrical grid infrastructure struggles to keep pace, an increasing number of data centers are being planned with colocated microgrids that integrate on-site renewable generation and energy storage. However, while existing research has examined the tradeoffs between operational and embodied carbon emissions in the context of renewable energy certificates, there is a lack of tools to assess how the sizing and composition of microgrid components affects long-term sustainability and power reliability. In this paper, we present a novel optimization framework that extends the computing and energy system co-simulator Vessim with detailed renewable energy generation models from the National Renewable Energy Laboratory’s (NREL) System Advisor Model (SAM). Our framework simulates the interaction between computing workloads, on-site renewable production, and energy storage, capturing both operational and embodied emissions. We use a multi-horizon black-box optimization to explore efficient microgrid compositions and enable operators to make more informed decisions when planning energy systems for data centers.

DepositOnce
Industry, innovation and infrastructure
Openalex Percentile: Top 15%
Cloud Computing and Resource Management
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