March 31 - April 4 | Hanover, Germany
March 31 - April 4 | Hanover, Germany
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Energy Operator

The AI agent supports energy operation and can be used as an advisor or autopilot. The Energy Operator helps you to adapt energy procurement to energy market prices and grid charges in a cost-optimized manner - without reducing production volumes. Combined with flexibility marketing and market intelligence.

Energy Operator
Challenges
Decarbonization & transformation
Rising CO2 prices and decarbonization targets are forcing other ways of procuring and converting energy with fewer fossil fuels. Electrification leads to additional dependence on the electricity market.
Increasing volatility
Energy prices on the electricity market are becoming lower on average. Due to the weather dependency of renewable energies, volatility is increasing: there are more hours with extremely expensive peaks and more hours with negative prices. Often within a few hours of each other.
Consumption-controlled energy component operation
Historically, systems such as CHPs have been heat-led with a focus on efficiency, which leads to constant and low consumption. Conversely, this leads to consumption at all times, especially at times with extremely high market prices and grid charges.
Production planning without energy information
Historically, energy has not been included in detailed production planning. It can therefore easily happen that an actually flexible production step is started exactly at a quarter of an hour with expensive electricity and an existing peak load.
Bedarfsprognosen
Meist werden die Energiebedarfsprognosen für die einzelnen Werke komplett extern vom Energieversorger ohne genaueres Wissen über das Werk oder intern mit wenig Daten entwickelt. Durch ungenaue Prognosen erhöht sich das Ausgleichsenergierisiko und die Nebenkosten.
Flexibility potential
Energy infrastructure
The aim here is to convert energy and fill storage facilities in a targeted manner when energy is green and cheap. This relates to the operation of power plants, converters and storage facilities on the factory premises - for example, the use of e-boilers or combined heat and power units (CHP units). In this way, the energy supply of the entire plant can be optimized without changing the supply for production.
Production
Flexibility can also be achieved by adjusting production by shifting demand to time windows with more favorable energy prices. In this way, production costs can be reduced by incorporating energy forecasts into the detailed planning of production.
Cost-optimized control of power plants and converters

With our AI agent Energy Operation, the energy components can be controlled in such a way that

  • the same amount of media is provided for production requirements,

  • but by intelligently converting and storing the energy supply at times that are green and cheap.

Schedule production at green and favorable times

With our AI agent, energy can be integrated into the detailed planning of production. For example, energy-intensive batch processes or batches can be scheduled at times with low energy costs and no peak loads.

Profitable cross-market flexibility marketing

Offer existing flexibilities on the various markets together with your energy supplier or marketer. For example, the combination of

  • balancing energy,

  • Day-ahead and

  • Intraday marketing

and automatically forward available quantities & price signals to your marketer.

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Demand forecast
Data-driven demand forecast for the entire plant reduces the risk of balancing energy and thus reduces ancillary costs for electricity demand.
Sector-linked
The energy component control and production recommendation system is sector-coupled across all forms of energy.
Cross-plant
The AI-Agent Energy Operation considers all plants in the balancing group together and makes joint recommendations.
Target/actual comparison
Live data integration enables differences between real operation and planned operation to be identified directly and countermeasures to be taken.
Energy markets and grid charges
The AI agent uses forecasts of the short-term energy markets and grid utilization for cross-market and grid charge cost-optimized operation.
Take a look at the database for the AI agent
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