Nine Velon-built Python modules under one canonical power-system model — built by Velon for transmission system operators, the major developers running large grid-connection studies, and the hyperscale data-centre operators siting GW-scale loads. Every deployment is bespoke and built around your approved environment. Start with a trial call.
The build-out is no longer the hard part — connecting it is. Industry forecasts put roughly 4,600 GW of new renewable capacity on the world's grids between 2025 and 2030, about double the previous five years, and in 2025 renewables overtook coal in global generation for the first time. The new demand is just as concentrated: gigawatt-scale data centres and offshore wind farms now arrive at single connection points large enough to move an entire boundary. What decides whether any of it can run is the transmission system, not the technology — and that decision is a power-systems study. Where to connect, how much to build, and whether the network can host it without curtailment or instability: the Velon Suites answer each from one canonical model, fast enough to run across hundreds of candidate points.
Industry figures, 2025 — IEA, Ember and a 2025 survey of 100+ energy professionals. The siting, sizing and hosting-capacity questions they raise are exactly what the suite computes.
Year-round security-constrained dispatch with the grid as a first-class constraint. Reinforcement screening, stability headroom, hosting capacity — across every boundary in your network.
Hundreds of candidate POIs ranked on curtailment risk, capture rates, stability margin and reinforcement need — under your own market scenarios. The bedrock of every IC business case.
The same screen your TSO will run — before they run it. Curtailment exposure, voltage and stability headroom, redispatch risk and BESS sizing. Concrete inputs for site selection, ramp planning and connection negotiation.
Each engine surfaces a family of specialist applications. They share the same data ingestion, network reduction and scenario library — and write back to the same KPI ledger.
Decides how to size and operate a battery for maximum value. BESS arbitrage and value-stack co-optimisation across the scenario library — sizing, dispatch envelope and the calendar-cost trade-off.
BESS state-of-charge · arbitrageWhyA battery only pays back if it's sized right.
Proves how the system actually dispatches under network limits. Half-hourly security-constrained dispatch across the year with the grid as a first-class constraint — the bedrock of every Pillar-2 KPI.
Branch loading · P10 / P50 / P90WhyValue a project on how it dispatches, not its nameplate.
Pins down what causes curtailment and what it costs. PTDF / LODF sensitivities localise every constraint event back to circuits, areas and connection points.
PTDF heatmap · circuit × hourWhyKnow the cause and cost of curtailment, not just the number.
Finds the most power a boundary can carry, safely. Maximum transfer across each boundary under every credible N-1, with asset-optimised dispatch of QBs and HVDCs.
Transfer · Boundary A → KWhyBoundary capacity decides what can actually connect.
Tells you where new generation, BESS or load should connect. Per-zone headroom and locational signals computed on a single canonical model.
Hosting capacity · zonalWhyThe wrong zone pays for congestion for its whole life.
Gives every study one trusted, traceable dataset. The foundation layer — pulls market, weather and network data into a single canonical model that every Velon engine inherits.
Sources → canonical → every engineWhySpeed on a fragmented dataset just fails faster.
Screens whether the system stays stable after a disturbance. Rotor-angle and transient screening — TSI, small-signal damping, critical clearing time — across the scenario library at every candidate POI.
Rotor angle · damped swingWhyFalling inertia makes stability the connection gatekeeper.
Checks the grid can hold frequency after a loss. System inertia, RoCoF and frequency-response containment headroom — surfaced as a margin per scenario and POI, hour by hour.
Frequency · RoCoF envelopeWhyBigger single connections, less inertia — frequency is harder to hold.
Confirms voltage holds and sizes the reactive support. PV/QV stability margin, short-circuit ratio and reactive-support siting — automated across every candidate POI in the scenario library.
PV nose-curve · V-marginWhyWeak grids and inverters make voltage the quiet blocker.
Turns a full grid model into a lean, EMT-ready study model. Boundary-aware reduction with Python + DPL automation on commercial solvers — feeds PSA, PFA & PVA.
Full model → reduced study modelWhyEMT studies are now the rule, not the exception.
Velon writes deterministic, production-grade software: versioned, tested and auditable from input to result. The Velon Suites shown above are one example of what that produces — but the same team builds bespoke tools of any kind around the workflow you actually run.
Power-system engineers who are also software developers — modular Python, proper version control, automated tests. Not macros, not spreadsheets.
The same inputs give the same result, every run. Every assumption is timestamped to a named source; every output traces back to the case that produced it.
PSCAD, PowerFactory and PSS®E stay the validated engines. Our software orchestrates them — stochastic sweeps, custom criteria, dashboards — and never locks you in.
Velon-hosted, your cloud or fully on-premises, behind your controls. Bespoke per operator — built around your data, market design and grid code.
Not limited to the Suites. The modules above are Velon-owned software we can package and deploy for these industries — but if your problem needs a different tool, we build that too, to the same engineering standard.
A short call to talk through the workflow you want and the question worth proving. From there we scope a focused trial on your own data — a few engineers, one defined question, a concrete deliverable in six to eight weeks. No black-box outputs, no lock-in.
A real slice of your network — boundary capability, curtailment exposure or a stability screen you'd otherwise build by hand.
Your grid code, market design and boundary topology, run against the commercial solvers you already license.
Joint sessions with your engineers — every result traceable to its case. You judge it on your own data.
Scale into a bespoke deployment tailored to your operation, or simply keep the deliverable. The decision is yours.
Start with a trial on your own data. Six to eight weeks. A defined question. A concrete deliverable. Then decide.
Send a one-paragraph scope — the system, the codes that apply, and the question you need answered. We typically reply within two working days.
Related: Consultancy · LumiMerse · EMT & grid-code compliance
