Readers with reliably-metered compressed-air installations are invited to participate in an exercise using a comparison technique called *parametric benchmarking*.

**Background**

Traditionally, air-compressor installations have been benchmarked against each other by comparing their simple specific energy ratios (SER) expressed typically as kWh per normal cubic metre. However, as this daily data kindly supplied by a reader shows, there may be an element of fixed consumption which confounds the analysis because the SER will be misleadingly higher at low output:

It seems to me that the gradient of the regression line would be a much better parameter for comparison; broadly speaking, on a simple thermodynamic view, one would expect similar gradients for compressors with the same output pressure, and differences would imply differences in the efficiency of compression. The intercept on the other hand is a function of many other factors. It may include parasitic loads; it will certainly depend on the size of the installation, which the gradient should not.

I am proposing to run a pilot exercise pooling anonymous data from readers of the *Energy Management Register *to try “parametric” benchmarking, in which the intercepts and gradients of regression lines are compared separately.

**Call for data**

Participants must have reliable data for electricity consumption and air output at either daily or weekly intervals: we will also need to know what compressor technology they use, the capacity of each compressor, and the air delivery pressures.

In terms of the metered data the ideal would be to have an electricity and air meter associated with each individual compressor. However, metering arrangements may force us to group compressors together, the aim being to create the smallest possible block model whose electricity input and air output is measurable.

Please register your interest by email to with ‘compressor benchmarking’ in the subject line: once I have a reasonable group of participants I will approach them for the data.

*Vilnis Vesma*

*4 January 2017*