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The Velon Suites

Planning software written by power-system engineers

Nine Python modules that share one network model and run on your own systems. Give them the same inputs and they give the same answer.

Book a trial call→ See the modules↓

Grid capacity is now the main bottleneck

4,600 GWNew renewables to connect, 2025–2030: about twice the previous five years
11%Renewable output curtailed in parts of Europe, summer 2025
#1Most-cited sector barrier: grid saturation and instability
45%Renewables’ projected share of world electricity by 2030

Industry figures, 2025: IEA, Ember and a 2025 survey of 100+ energy professionals.

The modules, grouped by the question they answer.

Engine

Curtailment & congestion

How the system dispatches under network limits: what gets curtailed, where, why, and what it would cost to fix.

PDAProbabilistic Dispatch AssessmentOpen PDA
Branch loading · P10 / P50 / P90Why Value a project on how it dispatches, not its nameplate.
PRAProbabilistic Redispatch AssessmentOpen PRA
PTDF heatmap · circuit × hourWhy Know the cause and cost of curtailment, not just the number.
PBAProbabilistic Boundary AssessmentOpen PBA
Transfer · Boundary A → KWhy Boundary capacity decides what can actually connect.
PCAProbabilistic Capacity AssessmentOpen PCA
Hosting capacity · zonalWhy The wrong zone pays for congestion for its whole life.
Engine

System security

Whether the system stays stable and holds frequency and voltage, screened across every scenario and candidate point.

PSAProbabilistic Stability AssessmentOpen PSA
Rotor angle · damped swingWhy Falling inertia makes stability the connection gatekeeper.
PFAProbabilistic Frequency AssessmentOpen PFA
Frequency · RoCoF envelopeWhy Bigger single connections and less inertia make frequency harder to hold.
PVAProbabilistic Voltage AssessmentOpen PVA
PV nose-curve · V-marginWhy Weak grids and inverters make voltage the quiet blocker.
Engine

Costs & revenues

How to size and run a battery for the best return, across all the scenarios.

PEAProbabilistic Energy-storage AssessmentOpen PEA
BESS state-of-charge · arbitrageWhy A battery only pays back if it's sized right.
Foundation

One canonical model

A single checked dataset, and a reduced EMT-ready model, that every module uses.

PDOPower-system Data OrchestratorOpen PDO
Sources → canonical → every engineWhy Speed on a fragmented dataset just fails faster.
NRNetwork Reduction ToolkitOpen NR
Full model → reduced study modelWhy EMT studies are now the rule, not the exception.

Who uses the Suites.

Boundary utilisation · winter peakIllustrative
Candidate POIs · rankedIllustrative
Data-centre sites · grid headroomIllustrative

How we build the software.

We write the code

Our power-system engineers are also software developers. The code is modular Python, under version control, with automated tests.

Repeatable and traceable

The same inputs always give the same result, and every output can be traced to the case that produced it.

Works with your existing solvers

PSCAD, PowerFactory and PSS®E remain the validated engines, and our Python links to them. For AI agents that run whole workflows, see QMerse.

Runs where you need it

Hosted by us, in your cloud or on your own servers.

If your problem needs a different tool, we can write that too.

Where else we can help.

The engineers who build the Suites also run the studies, automate them and teach them.

ConsultancyPSCAD/EMT studiesQMerseAgentic AI workflowsTrainingPSCAD and EMTDC

Start with a trial on your own data.

We agree one question with you and answer it on your data over six to eight weeks. Then you decide whether to go further.

  1. 01Agree the question
  2. 02Set it up on your network data
  3. 03Go through the results together
  4. 04Carry on, or keep the results
Book a trial call→ contracts@velonenergy.com