A few weeks ago, Utility Dive reported that grid constraints are threatening to delay or even derail hyperscale data center projects across the U.S.
“New data centers are running headlong into grid capacity walls. Wires can’t be built fast enough. DERs, say some, might be the shortcut.”
(Utility Dive, Oct 6, 2025)
Hyperscale data centers, the massive facilities built by cloud and AI giants like Amazon, Microsoft, and Google, can each consume 100–500 MW, equivalent to a mid-sized city.
Their growth is reshaping transmission planning and exposing the limits of the traditional interconnection model. It’s a story that’s becoming increasingly familiar inside control rooms: new forms of load are arriving faster than the grid can evolve. And once again, operators are being asked to bridge the gap between ambition and physics.
In my former life of managing control center operators, I’d tell them something I learned early in my career:
“A computer will never be the one who receives the impact for a distribution incident — it will always be the operator who trusted the data without verifying it.”
It was a reminder that technology doesn’t absolve accountability but rather that trust in automation has limits when reliability is on the line.That principle still holds true, but today, we’re entering a new phase. One where operators aren’t just monitoring technology; they’re collaborating with it. We’re asking them to interact with DER controllers, distributed devices, and aggregators that make decisions semi-independently. The operator’s role is no longer just to control, but to understand, verify, and coordinate with a growing constellation of automated systems.
This shift, from controlling assets to choreographing participants, is redefining what it means to operate the grid.
The Pressure Point: Data Centers vs. the Grid
Data centers are no longer just consumers, but system actors, capable of influencing local reliability, market stability, and even transmission planning.
At the same time, distributed energy resources (DERs) (solar, batteries, flexible loads) are being cast as the agile counterweight to these massive, immovable loads.
In theory, DERs can relieve node congestion or create virtual capacity, giving overloaded substations a temporary pressure release.
In practice, it’s messy.
Every DER added to the grid shifts the balance between control and coordination.
Every data center that comes online compresses the margin for error.
“To operators, this isn’t just an engineering problem — it’s an operational culture shift.”
The Shift: From Control to Choreography
Traditional grid operations were built on a simple assumption: we know what we own, and we control what we know.
But DER-enabled grids don’t work that way. They’re probabilistic, decentralized, and fast-moving.
Control centers are evolving from commanding assets to orchestrating participants, and that requires a new mindset.
Three realities are defining this shift:
Autonomy is rising.
DERMS platforms and aggregators are making dispatch decisions locally — sometimes faster than EMS or SCADA can register them.Trust boundaries are blurring.
Operators now depend on actions they can’t directly verify (curtailment signals sent over APIs, forecasts built by third parties, and flexibility bids aggregated across a thousand homeDecision latency matters.
Relief that arrives too late can make instability worse. And automation that acts too early can clash with higher-level control logic.
“DERMS promise autonomy — but autonomy without situational trust creates chaos.”
The technology stack (hosting capacity analytics, real-time distribution telemetry, predictive coordination engines) can bridge part of that gap. But tools alone won’t solve it as technology only amplifies human coordination; it doesn’t replace it.
The Frontier: Building Trust Between Humans and Machines
The next frontier of grid modernization isn’t DER adoption, it’s operator adaptation. To choreograph distributed assets effectively, control centers must rethink what “control” actually means and take tangible steps today to prepare their teams and systems for it.
Current gap: Most DER telemetry today is fragmented, lagging, or abstracted behind aggregators. Operators see whathappened — not why.
Action steps:
Integrate cause-effect context into displays: show dispatch rationale (market signal, local voltage, price threshold) alongside output.
Establish a DER situational awareness layer within the EMS/ADMS environment, one that flags not only MW but intent (forecast deviation, curtailment, market event).
Require “explainable automation” from vendors and aggregators, metadata that tags each DER action with a human-readable reason code.
Prototype cross-discipline dashboards: allow operations, planning, and market teams to see the same DER behavior with shared annotations.
Goal: move from visibility of state to visibility of intent.
Current gap: Most utilities lack explicit policies defining when and how operators can override autonomous DER actions especially when those DERs respond to market or aggregator signals.
Action steps:
Codify override policies that define thresholds for intervention (e.g., voltage deviation, SCADA latency, conflicting setpoints).
Include DERMS and aggregator controls in annual NERC/NPCC/North American ops governance reviews treating them as operational participants, not external systems.
Establish joint response protocols between control center and DERMS teams for loss-of-visibility or conflicting signals.
Run tabletop exercises simulating automation misbehavior or communications loss to test decision flow and escalation paths.
Goal: preserve human authority without paralyzing automation speed.
3. Training → Evolve from Deterministic to Probabilistic Thinking
Current gap: Traditional training scenarios assume predictable system response which no longer holds in a DER-dense, weather-driven grid.
Action steps:
Update simulator scripts to include uncertainty: variable DER response rates, forecast errors, delayed aggregator actions.
Add scenario-based exercises that force operators to make decisions under ambiguity (e.g., incomplete data or conflicting DER telemetry).
Cross-train distribution and transmission operators to interpret DER behavior and its system-level consequences.
Incorporate AI-assisted tools in simulation to help operators learn when to trust vs. question recommendations.
Goal: build cognitive flexibility, the ability to operate under partial visibility and variable automation.
4. Culture → Redefine What “Good Operations” Looks Like
Current gap: The legacy culture of “tight control = safety” doesn’t translate cleanly into distributed systems, where resilience often depends on graceful degradation and shared decision-making.
Action steps:
Celebrate coordination over command. Recognize operators who proactively collaborate across disciplines, not just those who “hold the line.”
Embed DER operations in daily stand-ups and post-event reviews treating DERMS events like transmission outages or market dispatches.
Create “human-in-the-loop” design councils pairing senior operators with IT, planning, and vendor teams to review automation features before rollout.
Track trust metrics, how often automation recommendations are accepted vs. overridden, and why.
Goal: normalize shared control as a marker of operational maturity, not loss of authority.
Putting It All Together
If you were to distill these into a one-page leadership checklist, it might look like this:
Dimension | Now (Current State) | Next (Actionable Step) | End Goal |
|---|---|---|---|
Visibility | Reactive monitoring | Add intent + rationale to DER telemetry | Shared situational context |
Authority | Undefined override rights | Codified automation boundary policies | Trust-based governance |
Training | Deterministic playbooks | Scenario-based uncertainty drills | Adaptive decision-making |
Culture | Command & control | Guide & govern mindset | Distributed trust |
Closing Thought
“The real modernization challenge isn’t integrating DERs — it’s integrating trust.”
And that trust has to flow in both directions, both from operators toward automation, and from automation toward operator oversight.The fastest path to new interconnections might run through DERs, but the most reliable path still runs through the people who make sense of them. Operators remain the connective tissue of modernization, translating technology into reliability, and automation into confidence.
The control frontier is shifting, and those who learn to choreograph, not just command, will define what resilient operations look like in the decade ahead.