Energy-Efficient Electrical Design Strategies for Small-Scale Data Centers

As the market for data processing and edge computing grows, small-scale data centers (SSDCs) become facilitating infrastructure for provisioning decentralized digital services. As much as their number is on the rise, SSDCs suffer from less-than-ideal electrical designs inherited from large-scale ones, realizing high energy losses and higher expenditures. The paper describes an in-depth investigation on energy-efficient electrical architecture for SSDCs, with special emphasis on low-loss distribution, high-efficiency conversion, smart power factor correction, and modular renewable energy interconnects. By strictly investigating the performance effects of these approaches in principal figures such as Power Usage Effectiveness (PUE), energy conversion effectiveness, and load balancing effectiveness, the study identifies the best rules for electrical architecture which can be transferred across a variety of small-scale configurations. Additionally, the incorporation of smart monitoring and load management infrastructure is proposed as an effective means for realizing long-term energy performance. Differing considerably from prior works which conceptualize energy effectiveness regardless of data center size, the paper distinguishes the unique constraints and opportunities in SSDCs such as constrained spaces, fluctuating loads, and lack of maintenance assets and maps them against pragmatically modular electrical practices. The study generates a set of repeatable, sustainable rules for the planning of energy-efficient electrical architecture for SSDCs, in aggregate, paving the way toward less carbonous distributed computing infrastructure. The paper is a prelude to future empirical testing and policy initiatives aimed toward realizing low-energy edge computing infrastructure.

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Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-08-07
DOI
https://doi.org/10.32996/jcsts.2025.7.8.85
Primary Topic
Advanced Data Storage Technologies
Type
article
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article

Energy-Efficient Electrical Design Strategies for Small-Scale Data Centers

M. Yasin Akhtar Raja
Journal of Computer Science and Technology Studies
Advanced Data Storage Technologies
article

Energy-Efficient Electrical Design Strategies for Small-Scale Data Centers

M. Yasin Akhtar Raja
article en

Abstract

As the market for data processing and edge computing grows, small-scale data centers (SSDCs) become facilitating infrastructure for provisioning decentralized digital services. As much as their number is on the rise, SSDCs suffer from less-than-ideal electrical designs inherited from large-scale ones, realizing high energy losses and higher expenditures. The paper describes an in-depth investigation on energy-efficient electrical architecture for SSDCs, with special emphasis on low-loss distribution, high-efficiency conversion, smart power factor correction, and modular renewable energy interconnects. By strictly investigating the performance effects of these approaches in principal figures such as Power Usage Effectiveness (PUE), energy conversion effectiveness, and load balancing effectiveness, the study identifies the best rules for electrical architecture which can be transferred across a variety of small-scale configurations. Additionally, the incorporation of smart monitoring and load management infrastructure is proposed as an effective means for realizing long-term energy performance. Differing considerably from prior works which conceptualize energy effectiveness regardless of data center size, the paper distinguishes the unique constraints and opportunities in SSDCs such as constrained spaces, fluctuating loads, and lack of maintenance assets and maps them against pragmatically modular electrical practices. The study generates a set of repeatable, sustainable rules for the planning of energy-efficient electrical architecture for SSDCs, in aggregate, paving the way toward less carbonous distributed computing infrastructure. The paper is a prelude to future empirical testing and policy initiatives aimed toward realizing low-energy edge computing infrastructure.

Journal of Computer Science and Technology StudiesVol. 7(8)
Openalex Percentile: Top 73%
Advanced Data Storage Technologies
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