Once the factors of influence are identified, the relationship between these drivers and energy consumption (or production) can be established by a technique known as regression analysis. Regression analysis attempts to describe the relationship between consumption/production and its drivers with a mathematical equation (i.e. model). An advanced regression model is integrated directly into the RETScreen Performance Analysis Module.

The first step is to establish a baseline period for the analysis. Often, a Time Series Graph is used to help identify the baseline. Once the baseline is set, it can be used to predict future energy consumption or production during a period for a specified set of conditions described by the drivers. Then, future use (or production) can be compared with the prediction to determine whether the use (or production) is higher or lower than predicted. The difference between actual and predicted values is calculated for each period and added together, creating a “running total.” This is referred to as the CUSUM, or CUmulative SUM, of the differences. The CUSUM is also referred to as the cumulative savings total. This, and other capabilities, such as Control Charts for tracking actual performance of a project in comparison with the targeted performance, is also incorporated into the Performance Analysis Module.

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