Reducing Energy in Industrial Plants Using Equipment Sequencing

Reducing Energy in Industrial Plants Using Equipment Sequencing

Control schemes that reduce industrial energy cost.

By: Allan Evora

While visiting industrial facilities, I often see aspects of energy efficiency overlooked. Your dynamic manufacturing facility needs a mechanism in place to address constant changes (e.g., production levels, adding more machines, etc.) and utility cost increases.

How can you address these changes and still provide the necessary resources to operate the facility in an economical manner?

Here are some control schemes that can be used within your plant to help you run your plant more efficiently and reduce energy cost.

 

The problem with compressed air

The most often overlooked utility is compressed air. The reason? Most manufacturers have predeveloped control solutions for managing sequencing of chiller and boilers. The compressed air industry hasn’t been as forthcoming with designs that incorporate equipment sequencing.

Did you know as much as 10% of energy use within an industrial facility is often allocated to the production of compressed air? In heavy industrial facilities, it can be as much as 30%. To compound that, generating compressed air is a very inefficient process. To generate a 1hp air motor to produce 100 psi requires 7-8hp supplied. Electrical consumption related to producing compressed air can add up to a significant expense.

 

Energy conservation strategy

To address operational needs while minimizing energy consumption, most facilities tackle low hanging fruit first. Some have gone through engineering studies to develop correct setpoints and fix energy wasters/inappropriate uses. (I’ve been in many industrial facilities where compressed air is used to clean the floors, which is an extremely expensive way to clean the work environment.)

Once you’ve addressed the low hanging fruit, it’s time for implementation that involves a control system.

 

Production vs. demand levels

Just like your car is most efficient on the highway, most chillers, boilers, and compressors are designed to output their utility at a design point which is near to the maximum output. We want to operate those machines as close to the setpoint as possible, which means we need to understand the demand for each utility in your facility.

It gets tricky when the facility’s utility requires more than one machine, with one machine operated at partial load. For example, you may need to decide if your compressed air should be delivered via two machines at partial load, or one machine optimally. Only after you understand how often you’re operating at those setpoints should you choose the machine design.

 

Implementation

Let’s say your facility requires 5,000 tons of chilled water. There are a few methods you can use to specify chiller capacity.

1) Specify three 2,000-ton chillers. Ideally, you’d run two chillers at full capacity and one at 50% capacity. This would also give you reserve for the future.

2) Specify two 2,000-ton chillers and one 1,000-ton chiller. This allows you to address current needs, but may not allow future expansion. In addition, extra machines take up more space and require more instrumentation to measure temperature and flow rates. However, when you require just 3,000 or 1,000 tons during winter and early spring, the smaller chiller may be able to address partial load conditions in a more cost-effective manner.

Obviously, these scenarios assume you aren’t stuck with existing equipment.

A note on variable speed machines: variable speed chillers and compressors can increase maintenance, capital costs, and personnel training. But a variable speed machine can address partial load conditions as a trim machine. Depending on your environment and how much your load level varies, you may be able to use this technology to address operational needs and still minimize energy consumption.

 

Metering

The equipment sequencing strategy is pretty simple, but does require intention. It also requires instrumentation.

Your control scheme (PLC or DDC) will have to make decisions on which machines to sequence on and off based on real-time measurements coming from installed, calibrated equipment (meters).

The problem is, a lot of old machines do not have the capability to measure the real-time process variables required to measure and track the effectiveness of event sequencing control.

 

When should you cycle on a new machine?

Let’s say your plant calls for greater production levels requiring more compressed air and you have to cycle on a second machine. The setpoints at which you transition from one to two, two to three, etc. are predetermined within your control sequence.

One of the things you must account for is hysteresis. Hysteresis allows you to avoid excessive cycling of equipment.

At a certain point in time, you’re going to have to add a second chiller. Once the second chiller is cycled on, if the load falls below the setpoint at which the second chiller came on, we aren’t going to turn the second chiller off. If we turned that chiller on and off at a discrete setpoint, if the load were to vary around that line, it would cycle excessively, reducing its lifetime.

 

Equipment sequencing in practice

Here’s a practical application of equipment sequencing we designed for a fiberglass manufacturer. Their centralized air compressor room had multiple machines running on a schedule. The manufacturer knew that during certain times of the year, certain compressors would run based on production levels.

There was no mechanism for measuring the amount of energy consumed by the compressed air system, and nothing matching compressed air generation with required load. Additionally, our engineers found inappropriate uses of compressed air taking place.

The project was a phased, retrofit implementation. In the first phase, we installed electrical submeters to record power and pressure to a plant historian, and matched that up with running compressors.

By looking at the cost of electricity and specific power use by the compressor system, the owner was able to benchmark energy use for compressed air. Compared to industry standards, they were found to be in excess.

The next step was to upgrade compressor controls. All-in-all, Affinity Energy was able to reduce the compressed air energy expense by 15%, which represented $150,000 a year. Now they have a tool that allows them to continually assess the efficient operation of the compressed air system. As the plant expands or shrinks, they can make modifications to ensure their energy intensity is in line with energy expenses.

 

Equipment sequencing is simple

We want to run as many machines at their optimal levels as possible while minimizing the number of machines that need to run. This includes best practices related to determining cycling setpoints, prioritization of runtime accumulation, and installing submeters.

Like most things in life, to get a payback, equipment sequencing requires an investment. Affinity Energy has helped owners in industrial facilities, central energy plants, and data centers implement control strategies that help address the operational needs while minimizing energy consumption.

Let us help you!

Allan Evora - Founder | Affinity EnergyAllan D. Evora is a leading expert in control systems integration and president of Affinity Energy with over 20 years of industry experience working in every capacity of the power automation project life cycle. With a background at Boeing Company and General Electric, Allan made the decision to establish Affinity Energy in 2002. Allan is an alumnus of Syracuse University with a B.S. in Aerospace Engineering, graduate of the NC State Energy Management program, and qualified as a Certified Measurement & Verification Professional (CMVP).

Throughout his career, Allan has demonstrated his passion for providing solutions. In 1990, he developed FIRST (Fast InfraRed Signature Technique), a preliminary design software tool used to rapidly assess rotary craft infrared signatures. In 2008, Allan was the driving force behind the development of Affinity Energy's Utilitrend; a commercially available, cloud-based utility resource trending, tracking, and reporting software.

Allan has been instrumental on large scale integration projects for utilities, universities, airports, financial institutions, medical campus utility plants, and manufacturing corporations, and has worked with SCADA systems since the early ‘90s. A passion for data acquisition, specialty networks, and custom software drives him to incorporate openness, simplicity, and integrity into every design in which he is involved.