ENERGY TWIN

AI plugin that analyses and predicts energy consumption, highlighting anomalies and potential savings.

EnergyTwin is an advanced SkySpark plugin that analyses and predict energy consumption — designed to optimise PV solar production by identifying problems and revealing future opportunities for savings and efficiency.

Resolving the fragmentation and complexity of energy data

As the original primary source of data, we work with several different sources of satelite prediction (NOAA, NCEP, GFS) which guarantees the robustness and reliability of the base prediction.

Superceding existing tools with adaptive machine-learning AI

Once established, the AI intelligently refines that base model through a variety of numerical models cross-referencing it with data from locally placed sensors.

A powerful PV and battery design tool that responds to key inputs

As the original primary source of data, we work with several different sources of satelite prediction (NOAA, NCEP, GFS) which guarantees the robustness and reliability of the base prediction.

How does Energy Twin work?

STEP 1

Analyse historical data

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STEP 2

Refine base model with realtime data

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STEP 3

Have an expert evaluate anomalies

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STEP 4

Identifies optimal tariff structure

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STEP 5

Monitor and continually revise

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STEP 1

Collect food waste

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STEP 2

Add and start cycle

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STEP 3

Heat activates bacteria

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STEP 4

24hr breakdown cycle

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STEP 5

Empty compost material

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Designed by Energocentrum in Prague.

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