Data Center Blog #3: Expanding Data Center Energy Monitoring Beyond the Meter

What was once a straightforward challenge of securing reliable grid capacity has become a more complex problem, involving constrained interconnections, long lead times for generation equipment, and growing utility expectations for flexibility. This is quickly becoming the key bottleneck for data center capacity deployment, even as many data center operators are jumping ahead in the gas turbine order line. 

Parts 1 and 2 of this series discussed how Seeq can be used as a strategic lever to enhance efficiency and increase uptime by leveraging industrial analytics, AI, and monitoring of critical facility infrastructure to reduce outages, improve SLA performance, and lower operating costs. 

As data center operators increasingly deploy on-site generation, such as gas turbines, to accelerate capacity, the boundary of the data center is effectively expanding beyond the regions of operator expertise. Power infrastructure now includes not just IT load, cooling systems, transformers/PDUs and grid ties, but also generation assets that must operate as a coordinated system. Monitoring architectures have not kept pace with these changes. 

The Limits of Traditional Visibility

Most data centers still rely on a combination of DCIM, BMS, and OEM-specific systems. While these tools provide valuable insight within their domains, they rarely deliver a unified view of how energy flows through the entire facility. 

This fragmentation makes it difficult to answer fundamental operational questions: 

• How do fluctuations in IT load propagate to transformer loading or turbine dispatch?
• Are on-site generators operating efficiently under real conditions, or simply meeting availability requirements?  
• Where are the true constraints when the facility is pushed to its limits—cooling, electrical distribution, or interconnection capacity?  

Without integrated visibility, decisions about load flexibility, generation strategy, or grid participation are made with incomplete information.

Extending Monitoring Across the Energy System

A more complete approach treats the data center as an integrated energy system. Seeq enables this by aggregating and aligning time-series and both relational and unstructured contextual data across traditionally siloed sources for AI-augmented analytics, monitoring, and action.  

This allows operators to: 

• Correlate grid import/export behavior with internal demand or adjust to grid pricing 
• Monitor transformer performance and thermal stress in the context of real workloads  
• Analyze gas turbine operation, including ramp behavior, efficiency, and dispatch patterns  
• Build a unified energy balance that connects generation, distribution, and consumption  

The result is not just more data, but a clearer understanding of how the facility behaves under dynamic conditions.

Improving OEM Collaboration and Service Outcomes

Grid providers need flexibility from large industrial and data center energy consumers but have historically been burnt by these contracts as discussed by Seeq’s Daniel Foster-Roman in his blog. To account for a dramatic increase in power needs for AI far beyond what grid providers can supply, data centers are taking on a larger role in managing their own generation. Long-Term Service Agreements (LTSAs), traditionally based on fixed assumptions about operating conditions, are increasingly misaligned with how data center assets are used. 

By providing a shared analytics environment, Seeq allows both operators and OEMs to work from the same operational data in a secure environment on a share-as-needed basis to protect IP from both parties. This enables: 

• Validation of performance against real duty cycles  
• Earlier detection of abnormal operating conditions  
• A shift toward more predictive, condition-based service models with OEM IP protected 

This level of transparency improves both asset performance and the effectiveness of service agreements. 

Moving Toward Integrated Energy Operations

The industry expectation that data centers can provide flexibility to the grid is unlikely to be met in the near term as data center demands skyrocket. Instead, flexibility increasingly depends not just on capacity and current IT load, but the ability for operators to shift to onsite generation in real time. With the right industrial AI foundation, operators can move beyond disconnected visibility and begin managing the data center as a fully integrated energy system, including their increasingly prevalent on-site generation assets.  

Seeq provides that foundation by connecting disparate data sources, enabling rapid, scalable analysis and data sharing with OEMs, all of which further asset monitoring, and enabes data center operators to keep up as IT load demands skyrocket. 

To learn more about Seeq, stop by our booth May 27th – 28th at the 6th Annual High-Density AI Data Center Infrastructure Summit in Reston, Virginia.