Predictive Energy Grid
Different energy generators and consumers, which are combined to a multi-utility control center, should
simply run in an optimal way. However, what is “optimal”? There are conflicting targets, like increasing
usage of own power supply, reducing energy costs overall, cutting peaks, using machinery more
If renewable energy is also generated, complexity is increased. Energy trading can be a lucrative building block, too, if trade fair risks are reduced.
Our self-learning Artificial Intelligence Software Solution PREDICTIVE INTELLIGENCE supports you on all levels of predictive energy grid:
- Predict energy demand and generation.
- Calculate machinery efficiency, and thus, also costs.
- Simulate best possible multi-utility control center and control machinery accordingly, either by recommendations to operator or by automated machinery control.
- Realizing full potential of renewable energy usage.
- More precise energy purchase and sale, also for renewable energy.
- Predictively automated energy trading.
PREDICTIVE INTELLIGENCE automatically adjusts algorithms to understand changes in machine / human behavior. Customized algorithms are automatically rolled out.
Below mentioned reference projects prove which value add our self-learning analytics software solution PREDICTIVE INTELLIGENCE realized:
EnBW: Full Potential For Renewable Energy Usage
Innovative analytics approach enables future-oriented solutions for renewable energy
Self-Learning Predictions for optimizing Power Plant Operation and Energy Trading
Energy Peak Cutting
Stadtwerke Saarlouis: Renewable Energy Prediction
Flexible and Precise Predictions despite High Volatility
Netzwerke Saarlouis: Gas Prediction
Twice as Precise than State of the Art Solution
Energy Demand Analysis
Predictive Energy Flow