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What if there was no need to (always) distribute the load among your pieces of equipment?

There are many reasons why you might want to distribute a load uniformly among several similar pieces of equipment: even wear, maintenance constraints, process security, contractual factors, habit… and often the impression that you’re saving money by “going slower”. Alas, the synergies you were counting on may well prove negative.

 

It’s all about efficiency

The primary cause is the non-linear efficiency of most items of equipment. It is all too easy to confuse a machine’s absolute energy consumption, which varies, by and large, with the load and the duration of use, and its relative consumption or efficiency, i.e. the amount of energy required per unit processed. “Take compressors, for example. Their efficiency, in kWh/m3, depends essentially on three criteria: the technology (electric compression or gas turbine), the required compression rate (final pressure/initial pressure), and the flow rate injected on entry”, explains Camille Boutinet, energy efficiency engineer at Blu.e. The resulting performance curve leaves no room for doubt: for a given rate, only a certain flow range will deliver high efficiency. “It is instantly clear that it is better to use a single compressor in its optimum operating range than two or more in a less efficient zone,” says Camille Boutinet.

 

Note: the electric compressor’s curve is lower: it is more energy-efficient.

 

When the energy performance indicators and the economic indicators differ…

The situation becomes a bit more complicated when we start talking euros, not kWh. The technical performance curve may prove insufficient here, or even be contradicted by the economic performance, expressed in euros per unit produced. This happens when a technology has a distinct advantage over another because of the price of energy: for the same power output, a gas compressor is always cheaper to run, at least for the moment,” says Camille Boutinet. Other criteria can come into play in various ways, depending on the equipment: subscription ceiling or floor prices, start-up losses, minimum duration of use, maintenance constraints, participation in a load-shedding scheme, etc. “Based on their performance curves and the energy they run on, we can draw parallel economic performance curves for all of the pieces of equipment: compressors, boilers, cooling plants, pumps, etc. We can then make choices and construct start-up sequences that deliver optimal energy efficiency,” says Camille Boutinet.

 

The gas turbine’s curve is lower: it is more energy-efficient throughout the range.

 

A small study for a large initial reduction

In practice (and ideally), performance curves can be constructed using the historic operating data. After studying the most frequent load demands, you will be able to construct equipment start-up strategies and immediately make substantial savings. “The energy savings vary widely, but can reach double-figure percentage reductions and an ultra-fast return on investment. Managers can adjust start-up sequences in real time and recommend precise operating instructions for each piece of equipment!” says Camille Boutinet.

 

Towards digital-driven continuous optimisation

A digital platform (such as blu.e pilot® for example) can be used to:

  • Create technical performance indicators based on data histories;
  • Construct the resulting economic indicators;
  • Superimpose the curves to easily spot the most efficient start-up sequences to apply;
  • Compare the results obtained and, depending on the use cases, extract the best practices.

 

And if you don’t have a tool just now, begin by starting up your machines one after the other, systematically aiming to operate at the rated capacity.