Prove energy savings with the help of linear regression

Meaningful regression models now make it even easier to demonstrate energy savings by statistically validating relationships between different measurement series and deriving expected values for energy consumption after a measure. Thanks to the parallel calculation of several models, various influencing factors can be flexibly included or excluded, which ensures optimum comparability. Our solution makes it possible to consider the difference between the expected and measured values as the actual savings achieved by the respective measure.

Targeted data selection

• Simple master data filtering using the hierarchy tree
• Various options for filtering measurement data
• Simple selection of independent and dependent variables

Fast and precise calculations

• Time saving through parallel calculation of several models
• Coloring of the statistical key figures in traffic light colors for a quick overview

ISO-compliant reporting

• Various options for visualizing the calculated and measured data
• Download option in all common formats for simplified reporting

Different representations for quick interpretation and overview

• Scatter diagram for pattern recognition and identification of trends
• Comparison diagrams with highlighted deviations
• Table with detailed analysis of all pairs of measured values including display of absolute and relative deviations

Instead of time-consuming manual calculations, fast, targeted data analysis using linear regression ensures optimized and well-founded decision-making. Different models can be compared efficiently, savings from energy efficiency measures can be reliably verified and both analysis and reporting can be simplified considerably - quickly, precisely and transparently.
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