knowledge architecture · energy transition

KNOWLEDGE LAB / KNOWLEDGE GRAPH / ENERGY TRANSITION / BUILT

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The grid queue isn't a capacity problem.

It's a knowledge problem.

125GW
grid connection queue
~45GW
peak electricity demand
~80GW
of the queue is data-centre applications

Ofgem has said a share of that data-centre capacity may represent speculative capacity-hoarding rather than committed projects.

Something clearly isn't working.

But I don't think this is only an infrastructure problem.

It's also a Knowledge Architecture problem.

Explore the interactive graph ↓

The organisations responsible for regulating, operating, connecting, settling and using Britain's electricity system don't interact with one shared representation of that system.

Different responsibilities.Different systems.Different schemas.Different definitions.

And different representations of the same physical assets and capacity.

Consider a deceptively simple question:

How much capacity is actually available here?

The answer can depend on which system you're asking. That becomes a problem when those systems need to work together.

I mapped seven parts of the grid-connection ecosystem and the knowledge relationships between them. Each edge asks a simple question:

How well does knowledge cross this boundary?

INTERACTIVE INSTRUMENT

Grid Knowledge Graph: relationship explorer

Node roles reflect real functions within GB grid governance. The specific edge classifications shown are an illustrative placeholder, built to demonstrate the instrument, not yet verified against primary Ofgem/NESO/ENA source material. They'll be replaced with sourced classifications.

ALIGNEDPARTIALLY BRIDGEDFRAGMENTED
Select a node to inspect its role and knowledge relationships.

Relationships are classified as:

ALIGNED

The systems share sufficient semantic understanding.

PARTIALLY BRIDGED

Translation exists, but requires reconciliation.

FRAGMENTED

The same underlying reality is represented incompatibly across the boundary.

Britain's energy system produces enormous quantities of data. The harder problem is whether two systems mean the same thing when they describe the same grid.

For example, Ofgem can require Distribution Network Operators to make connection information transparent. But regulation of the outcome doesn't automatically create a shared schema. Different DNO regions can therefore expose the required information differently.

A platform trying to construct a national view doesn't simply consume fourteen compatible sources. It may have to translate between fourteen representations of ostensibly the same domain.

That's knowledge debt.

Semantic fragmentation sounds abstract until someone has to reconcile it. So I built a small model.

INTERACTIVE INSTRUMENT

Reconciliation-cost simulator

ILLUSTRATIVE ANNUAL RECONCILIATION OVERHEAD
£840,000

This is not an industry cost estimate. It's an analytical model designed to make the economics of semantic fragmentation tangible. Change the assumptions above and see what happens.

I'm interested in what happens when we stop treating Knowledge Architecture as something that happens inside documentation teams. Energy systems are becoming increasingly:

distributedsoftware-definedinterconnectedAPI-mediatedautomatedand eventually more agentic

Those systems don't merely need access to data. They need enough shared context to understand what that data means.

That's where Knowledge Architecture becomes infrastructure.

This isn't a proposed product. It's a worked Knowledge Architecture experiment. It explores how techniques such as:

domain modellingknowledge graphssemantic relationshipsknowledge-debt analysisprovenanceand interoperability modelling

can make an infrastructure problem visible in a different way.

The underlying grid figures and organisational relationships are grounded in public Ofgem, NESO and ENA sources. The Knowledge Graph, relationship classifications, knowledge-debt scores and cost model are my analytical framework for exploring those relationships, not official industry figures.

THE SIGNAL
Physical infrastructure can share a grid without sharing a model of the grid.

And as energy systems become more interconnected and autonomous, that distinction matters.

SOURCE → MODEL → CONNECT → TEST → VISUALISE

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