The central question in measuring energy efficiency: how did energy consumption change from the baseline period to the reporting period?
Energy data is loaded into the OpenEEMeter as a “trace”, a single-dimensional time series of measurements tracked by a single physical meter or smart meter. For instance, many projects are broken into two traces: one natural gas trace, and one electricity trace.
The OpenEEmeter accepts a few special fields of project data:
Building energy usage can be organized into three categories: heating load, cooling load and base load. During cold weather conditions, a building needs to be heated to achieve a comfortable temperature; similarly, hot conditions require cooling. Other elements, such as refrigeration and lighting, remain more consistent over the course of the year and can be represented in the base load.
The relationship between energy use and temperature is reflected in the building consumption profile shown below. Heavier use occurs during periods of high and low temperatures (summer and winter) while usage during more temperate periods (spring/fall) is more moderate.
The OpenEEMeter fits a linear model to this data and can use this model to estimate the building’s energy consumption, given outdoor weather conditions.
The OpenEEmeter also calculates a number of standard outputs, which can be used to perform additional analytics tasks.
Another way to quantify energy efficiency savings is "normal year savings." This is the expected annual savings over a “normal” weather year. The “normal” weather year is an idealized, hypothetical year which is constructed by drawing from observed weather data. This effectively “normalizes” the data by removing some weather uncertainty, and allows for comparison over a number of years.
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