mP Energy was designed for various forecast requirements from smaller local municipal utilities to large international energy producers, suppliers, network operators and trading companies. It is a sophisticated and universal energy forecast application that meets every need in terms of functionality and cost-performance ratio.

Time series data is used as the basis for all calculations, which are predicted in connection with machine learning algorithms and other methods. The user also has numerous optimization options at their disposal, as well as very powerful options for rule-based forecasting or workflow definition, e.g. for the flow or control of automation processes.


For optimal demand forecasts for residential, industrial, and commercial customers – regardless of the profile class, be it HH or NHH meters, or short- or long-term horizons, mP Energy includes comprehensive features and prediction capabilities to improve forecast quality, helping e.g., to significantly reduce energy balancing costs.


Predicting required gas volumes as accurately as possible is crucial for your economic success. With mP Energy, short-, medium- and long-term demand forecasts can be reliably and sustainably produced. Based on various forecasting methods, the aggregated result time series can also be optimized several times a day, and if necessary, adjusted as required.

District Heating

Producing reliable load forecasts for district heating generation is not a trivial task. The more accurate the district heating load forecast is, the more efficiently plants and storage facilities can be regulated. Load forecasts thus play an important role in the economics and the efficiency of district heating networks.

Solar Energy

A reliable forecast for electricity generation by solar energy (photovoltaic) is the basis for stable power grids and low balancing energy costs. With mP Energy, all predictors such as solar irradiation, irradiation angle, cloud cover, temperature, and others, can be included in the forecast models of the generated energy.

Wind Energy

Wind energy is unquestionably one of the most difficult types of renewable energy to forecast with good accuracy. We would be pleased to show you how you can acquire an optimal forecast result out of your weather, location, and turbine data with the artificial neural networks algorithm used in mP Energy.

Hydro Power

The power generation of run-of-river power plants depends on many influencing factors. In mP Energy, the capability exists to process all available information and prediction factors for acquiring an extremely accurate generation forecast together with our algorithms and metaScript Master – our rule-based forecasting strategy.

metalogic GmbH

Westendstrasse 177
80686 Munich, Germany
Phone: +49 89 51 73 93-0
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