The same mechanism — real-time scarcity inference, bounded signals, fair allocation — addresses the most pressing distribution network challenges facing operators today.
Static dynamic operating envelopes are a blunt instrument. They constrain all exports uniformly regardless of actual feeder conditions. Enleashed replaces them with real-time coordination signals that reflect what the feeder can actually absorb at each interval.
Near-boundary operation falls by over an order of magnitude in simulation
More flexible demand can be accommodated without augmentation
Proactive coordination defers capital spend by maximising existing asset utilisation
Thermal limits, voltage bounds, and DOE profiles consumed per interval
Congestion tightness index and voltage deviation combined into a single signal
Bounded buy/sell prices reflect actual local headroom — not a static envelope
EVs, batteries, and controllable loads shift within their declared windows
No curtailment, no manual intervention, full audit trail for regulatory reporting
Curtailment is the system's admission that it cannot coordinate fast enough. In high-penetration solar areas, it is the dominant constraint management tool by default. Enleashed converts surplus periods from curtailment events into coordination opportunities.
Surplus export is absorbed by coordinated flexible demand rather than curtailed
Households maximise export earnings from rooftop solar through better price signals
Renewable generation that would have been wasted is absorbed locally
Overvoltage signals and positive export balance indicate local surplus
Composite α̃ close to 1 — abundant supply, demand can be recruited
Price signals incentivise flexible demand to consume during surplus windows
EV charging, hot water, storage charging absorb the surplus
Generator and consumer both earn; network constraint resolved
Unmanaged EV charging is the largest emerging source of feeder-level demand peaks. Static time-of-use tariffs shift the problem rather than solve it — they create new peaks at cheap-rate hours. Enleashed coordinates charging against actual feeder conditions, not static price schedules.
Based on literature evidence for shiftable EV charging with improved real-time signals
Coordination through price signals — no direct control of individual chargers
Fair Play ensures under-served participants are prioritised in subsequent intervals
Flexibility window declared: need X kWh, latest by time T, power up to P kW
Real-time thermal headroom and forecast conditions determine available capacity
Cheapest feasible interval within the declared window — aligned with low-constraint periods
DERMS or smart charger responds to the coordination signal — no direct control
If charging is deferred, priority weight increases for subsequent intervals
Every deployment starts in shadow mode — running against real system data in parallel before any operational transition.
The coordination engine runs in parallel with existing mechanisms using real DNSP data. Outputs are compared against incumbent behaviour. No operational risk — evidence built before any transition.
Live deployment on a defined set of feeders — 10–20 high-DER feeders with DNSP integration. Real assets, real coordination signals, measured outcomes against agreed milestones.
Demand-side participants (EV fleets, community batteries, industrial loads) enrolled into the coordination layer. Two-way value capture demonstrated across supply and demand.
Expand to additional feeders and network areas. Engage regulator on formalising the coordination layer within emerging market design frameworks.
We're actively scoping initial deployments with DNSPs and system operators. Shadow mode means zero operational risk to get started.