A.Stanchev, Plamen and Hinov, Nikolay and Zlatev, Zoran (2025) Integrating Data Center Infrastructure into Smart Grid Energy Management Systems. In: 33rd National Conference with International Participation "Telecom 2025", 20-21 Nov 2025, Sofia, Bulgaria.
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Abstract
The exponential growth of digitalization and
artificial intelligence workloads has positioned data centers among the fastest-growing electricity consumers worldwide.
Traditionally viewed as passive loads, modern data centers
possess advanced energy infrastructures, such as uninterruptible power supply (UPS) systems, battery storage,
and intelligent cooling, that can be leveraged as flexible
resources for smart grid operation. This paper proposes an
integration framework between Data Center Infrastructure
Management (DCIM) and Smart Grid Energy Management
Systems (SG-EMS) to enable bidirectional energy and
information exchange. The proposed architecture coordinates
local assets within data centers with grid-level control for
demand response, peak shaving, and renewable energy
utilization. A case study of a 10 MW data center equipped with a 1 MWh battery and 2 MW photovoltaic plant demonstrates that coordinated control can reduce peak grid demand by up to 18%, lower daily energy costs by approximately 17%, and provide sub-second frequency response without affecting IT service performance. The results confirm the potential of data centers to act as virtual energy storage units and active participants in smart grids. Future developments include AI driven predictive control, digital twins for co-simulation, and secure interoperability between DCIM and SG-EMS platforms.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences Engineering and Technology > Electrical engineering, electronic engineering, information engineering |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Zoran Zlatev |
| Date Deposited: | 05 Feb 2026 08:57 |
| Last Modified: | 05 Feb 2026 08:57 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/37838 |
