Prediction

Energetic systems cannot rely simply on predictions based on intuition, experience or assumptions. We have to act responsibly and utilize mathematical methods and technological know-how for the most relevant and precise data.

This approach will enable cutting costs, make processes more accurate and - the most important – eliminate possible crisis situations (gas leaks and explosions, power blackouts, …).

Examples of utilizing predictions

  • Predicting locations of risky pipelines saves maintenance and repair costs of gas suppliers
  • Photovoltaic electricity suppliers are dependent on prediction of intensity and duration of solar exposure – the temperature inversion can for example cause a complete decommission of photovoltaic power plants and influence the electricity price
  • With the correct data about temperature inversion electricity can be purchased at lower prices while optimizing own production share
  • Electricity suppliers face an unexpected growth in local production (e.g. photovoltaic plants and wind power plants) which may cause dangerous overloads of  systems
  • Prediction of electricity production and optimization of its purchase efficiently covers consumption and reduces costs
  • Information on the future network input enable optimization in advance and protection of low and middle-voltage systems against overloads

We offer these prediction systems

Predictive maintenance for utilities

  • Designed for operators in the Energy sector (electricity, district heating, gas, water)
  • Timely information on the necessary repair of certain components in distribution system
  • Cutting maintenance costs using advanced analytics

Weather forecasts for photovoltaic companies

  • Timely information on the duration and strength of sunshine
  • Information about possible freezing
  • Help to manage production and distribution more efficiently
  • Optimization of electricity purchases

Failures in machinery companies

  • Timely information on possible machinery failures
  • Calculation of various aspects (e.g. load-strain-stress, number of performed maintenances, history of machinery operation, surrounding conditions etc.)
  • Protection against the business-critical failures
  • Maintenance costs reduction

Optimal production for energy producers

  • Information on the most efficient utilization of each source available in advance
  • Cutting production costs with optimal utilization of all accessible resources

 

Documents for download

Prediction​​

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