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disconnected, so the investment generates no power – and no
return…].
This is a result of grid intelligence, derived from increa-
sed sensing and more intelligent control. Grid intelligence will
grow in the coming years and this is good news for consumers
and for the planet.

Integration at industrial level

With the consolidation of the concept of industry 4.0, a move
towards the internalization of energy of a component of the in-
dustrial process, instead of an externality, gained momentum.
Its roots may be found in the affirmative progress of a
complex simulation concept denoted “digital twin”. In a nuts-
hell, a digital twin is supposed to achieve a digital representa-
tion, as detailed as possible, of a process or set of processes,
including a whole manufacturing process, including the beha-
viour of all physical elements such as production chains, pro-
cessing machines, transportation and internal logistics, etc., in
such a way as to reproduce all behaviour in the time domain,
triggered by events or trains of decisions mimicking the real
world. It’s a computer simulation, so it’s “digital”, and attempts
to exactly mirror a physical system, so it’s a “twin”. Do, if you
start the clock and let it running, you will watch a film of the
developing of a possible reality.
The objectives of implementing and running digital
twins of industrial processes are multiple. In most cases, they
are in one way or another linked to the purpose of observing
the effects of investment or operation decisions, to optimize
processes. It is the full power of detailed realistic simulation
played against a hypothetical alternative of a complex nume-
rical optimization modelling, which at some point must resort
to simplifications or linearization or similar tricks to achieve
computable solutions. Digital twins may be run in Monte Car-
lo-style mode, and the simulations allow the detection of bott-
lenecks, insufficiencies, or other factors that affect production,

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