Predictive and Balancing System for the Energy Sector
Forecasting future market behavior is key to effective management in the energy sector. The accuracy of this forecast can significantly impact not only the economic situation of enterprises, but in current times also the continuity of energy supply.
The innovative predictive and balancing system dedicated to the energy sector combines computational methods and artificial intelligence, providing holistic analysis of incoming data.
Features:
- Accurate forecasting models for values critical to the energy market, such as:
- electricity prices
- energy production from renewable sources (RES), including PV and wind farms,
- demand for thermal and electrical energy.
- Multiple forecast horizons
- short-term forecast (below 24h),
- long-term forecast.
- Granularity of energy demand models – forecasts for entire regions (e.g., cities) as well as for individual buildings.
- AI supported by mathematical models – integration of deep neural networks and stochastic differential equations.
- Data integration module from multiple sources – ability to utilize data from various sources and in multiple formats.
- Automatic calibration – activation of model retraining mechanism when accuracy on new data falls below the established threshold.
- GPU accelerator utilization to speed up computations performed on dedicated servers.
- Flexible deployment model – the system can be deployed in on-premises environments, public cloud, or in a hybrid model.
Benefits:
- Approximate view of the future – high-accuracy prediction of selected values: production, energy demand, and energy prices.
- Easier and more reliable decision-making process – acquired data and analyses support investment processes as well as planning processes in generation, distribution, and consumption.
- Increased awareness of factors influencing future values through feature importance.
- Time savings dedicated to analyses.
- Loss reduction and informed management, particularly during energy crises.
Offer:
