ADMS VVO Optimizes the Grid You Think You Have.
EDGE® AVO Optimizes the Grid You Actually Have.
Volt/VAR Optimization (VVO) has long been viewed as an efficiency tool: a way to trim energy consumption, improve power quality, and support Conservation Voltage Reduction (CVR). With the widespread adoption of Advanced Distribution Management Systems (ADMS), utilities now have more analytical capability than ever to model feeders and coordinate voltage-controlling devices.
And yet, even with modern platforms in place, many utilities still struggle to operate voltage optimization aggressively, persistently, and confidently, particularly during periods when affordability and peak demand matter most.
The reason is simple, but fundamental:
Most voltage optimization systems are built on what the grid is believed to look like, not how customers are actually experiencing it in real time.
The Model-Centric Foundation of Traditional VVO
Traditional ADMS-based VVO systems share a common architectural premise: the distribution model is the primary source of truth.
Voltage control decisions are centralized. SCADA measurements provide visibility at limited points on the feeder. Customer and end-of-line voltage are inferred, and fixed safety margins help account for uncertainty.
In practice, the control process often looks something like this:
Distribution model → SCADA measurements →
inferred customer voltage → safety margin → control decision
This approach reflects real operational constraints. No distribution system is perfectly mapped. Secondary conductors and connectors, phase errors, load variability, and other system changes introduce uncertainty that cannot be fully eliminated.
So traditional voltage control effectively answers this question:
“Given what the model believes, what voltage settings are safe?”
What other utility control systems use an estimated outcome to derive real-world setpoints?
AMI Gives Utilities More Visibility. But What Role Does It Play?
Advanced Metering Infrastructure (AMI) dramatically improves visibility into customer voltage.
In most ADMS environments, AMI voltage data commonly helps utilities:
- Validate CVR results after the fact
- Support reporting and regulatory review
- Improve feeder models over time
- Identify planning-grade voltage concerns
What it typically does not do is:
- Define live operational limits
- Serve as a binding control input
- Dynamically determine how far voltage can safely be reduced
With ADMS solutions, AMI helps validate the model, but the model still drives control decisions.
As a result, voltage optimization often remains conservative by necessity, particularly during load volatility, switching, or other system changes.
What That Means for CVR in Practice
When customer voltage is inferred rather than continuously observed, utilities often have to operate cautiously.
That can mean:
- More conservative voltage reductions
- Conditional CVR operation
- Operators backing off during uncertainty
- Difficulty sustaining operation near the lower voltage boundary
The system can find CVR opportunity, but it struggles to live there.
Energy savings still occur, but they may be more episodic than persistent.
What could a little more voltage headroom mean?
1% additional voltage reduction For a small utility, this can produce upwards of 10 GWh in annual savings, amounting to approximately $1.4 million per year in customer bill savings. For a large utility, that opportunity can increase to hundreds of GWh and more than $10 million in customer bill savings.
DVI’s EDGE®: Flipping the Script
EDGE®’s Advanced Voltage Optimization starts from a fundamentally different premise:
Customer voltage is not an outcome to estimate. It is a boundary to respect.
Instead of asking:
“How low can devices be set to probably keep customers in the allowable voltage range?”
EDGE® asks:
“How low are customers allowed to go?”, and informs grid control devices to behave accordingly.
That is the fundamental shift.
AMI Becomes the Operating Boundary
In EDGE®, customer voltage data plays a different role.
Utilities define the minimum acceptable customer voltage for different use cases. AMI reveals actual customer conditions, and control logic adapts based on measured response rather than inferred profiles.
The lowest-voltage customers help define the permissible operating envelope.
Measured customer voltage → lowest-voltage boundary → available headroom → feeder-level control response
Voltage margins no longer exist only as static buffers.
They become dynamic, observed headroom.
This does not eliminate the role of SCADA, communications, or engineering judgment. It changes where operational certainty comes from.
What Better Voltage Visibility Unlocks
With continuous visibility into customer voltage, the same operating boundary can support multiple grid needs.
Everyday Efficiency: CVR
Under normal conditions, EDGE® can operate in a CVR-focused posture, holding customer voltages as low as the utility chooses while remaining within defined limits. That supports sustained energy reduction and affordability benefits without requiring customer signups or behavioral changes.
Peak Demand: DVR
During peak usage periods, however — when demand, loading, and system costs are highest — EDGE®’s continuous visibility into customer voltage enables something more:
Because EDGE®:
- Knows in real time how close customers are to the lower limit
- Sees voltage movement as load ramps up
- Responds feeder-by-feeder and moment-by-moment
It can intentionally and confidently drive voltage to the very bottom of the allowable range during peak conditions — without guessing, and without violating customer voltage limits.
This is not event-based demand response. It is precision demand suppression, embedded in voltage control.
Emergency Conditions: EVR
During emergencies, when curtailment activities may otherwise be contemplated, EDGE® provides an Emergency Voltage Reduction (EVR) mode. Under special conditions, utilities may operate into the ANSI C84.1-B range (110 V on a 120 V nominal). EDGE®’s continuous monitoring of worst-case customer voltages allows utilities to temporarily lower voltage into this range safely, providing significant additional demand relief.
Why This Matters During Peaks
Traditional voltage systems may become more conservative during peak conditions because voltage profiles are changing quickly, models are under greater stress, and operational risk increases.
EDGE® does the opposite — not because it is more aggressive, but because it is better informed.
During peaks, voltage can become a first-class demand lever, helping utilities reduce load proportionally without requiring customer action, dispatch, or behavioral changes.
CVR reduces energy during everyday operation. DVR and EVR provide additional demand relief when system conditions call for it. Both depend on the same thing: knowing where customers actually are.
And the peak opportunity can be significant:
3% additional voltage reduction during peak conditions can amount to $6 million or more in demand charge savings for a small electric cooperative, or hundreds of megawatts of additional capacity for an investor-owned utility.
EDGE® Complements ADMS
EDGE® does not replace traditional ADMS capabilities.
ADMS remains essential for functions such as:
- Switching and outage coordination
- Fleet-wide operational awareness
- System-level analytics
EDGE® adds another layer of operational visibility where centralized models can struggle most:
- At the customer edge
- During periods of volatility
- Near the true lower voltage boundary
The distinction is less about replacing one system with another and more about changing the source of certainty used for voltage optimization.
The Difference That Matters
The difference is not simply better algorithms or faster control loops.
It is about what the control system knows.
ADMS VVO optimizes the grid you think you have. EDGE® AVO optimizes the grid you actually have.
When affordability, peak demand, and system constraints all matter, that distinction becomes increasingly important.
Want the Deeper Technical Comparison?
Explore how model-based voltage control and measurement-anchored optimization differ in architecture, operating boundaries, CVR, and peak-demand applications.
