# Greenhouse Gas Emissions and Reliability and Maintenance One of the hot topics is the environment and the term

The big question is: how can we in reliability and maintenance show our management that we can have an impact on company greenhouse gas emissions?

It is actually quite simple.  The key is just knowing the impact of the R&M improvement on energy and then using a multiplier for energy consumption.  For instance, for any improvement that involves natural gas, the multiplier is 0.0532 Metric Tons per MMBtu reduced.  Therefore, if you were to discover that you had steam distribution lines that were not insulated, you could determine the energy cost savings and the reduction in greenhouse gas emissions, while the processes dependant upon the steam would be improved.

Heat Loss per 100 feet of Uninsulated Steam Line*
Distribution
Line Diameter
(inches) Heat Loss per 100 Feet of Uninsulated Steam Line (MMBtu/yr)
Steam Pressure (psig)
15 150 300 600
1 140 285 375 495
2 235 480 630 840
4 415 850 1,120 1,500
8 740 1,540 2,030 2,725
12 1,055 2,200 2,910 3,920
• Table from ‘Improving Steam System Performance,’ US Department of Energy

For example, if you found 200 feet of uninsulated 2-inch pipe at 150psig in a plant where the value of steam is \$6/MMBtu, the following savings would be realized from a 90% efficient insulation system:

- 200 ft x 480MMBtu/yr per 100ft (4.8MMBtu/yr) = 960 MMBtu/yr
- Energy Cost Improvement: 0.9 eff x \$6/MMBtu x 960MMBtu/yr = \$5,184/yr
- CO2 Emission Improvement: 0.9 eff x 960MMBtu/yr x 0.0532 = 46 Metric Tons CO2/yr

Makes for a much more interesting business case in these times.

Now, here is where your Electrical Signature Analysis (ESA) systems come into play.  What happens when we start looking at electrical energy cost reductions as a direct result of motor system energy improvements?  There are charts available through the Energy Information Administration that show greenhouse gas emission multipliers by State that are based upon the mix of power generation and distribution systems.  However, for the purpose of the examples here, we will use the national average of 1.34lbs CO2/kWh and 0.606 Metric Tons/MWh (conversion: 1,000 kWh = 1 MWh).  In effect, these numbers are related to how much CO2 is released from the power plants producing the energy.

In the first example, we will consider a repair versus replace scenario.  A 50 horsepower motor operating 6,000 hours per year (3 shifts, 5 days per week, 50 weeks) has been found in need of rewind repair by Motor Circuit Analysis (MCA) and bad bearings are detected using ESA.  The ESA data is used to determine the motor efficiency and loading: 50 HP, 75% loaded, 91.5% efficient at an energy cost of \$0.06/kWh and \$10/kW demand.  If you were to replace the motor with a premium 94.5% efficient motor that costs \$2,400 what would the difference in energy be?  If the repair cost was \$1,500, what would the simple payback be?  What is the difference in greenhouse gas emissions assuming an average of 0.5% reduction per rewind (US DOE)?

First, we determine the kW demand difference:

50HP x 0.746kW/HP x 0.75 load factor x ((100/91.0)-(100/94.5)) = 1.14 kW

Demand Charge Reduction = 1.14kW x \$10/kW x 12 months = \$137/yr
Energy Use Reduction = 1.14kW x 6,000hrs/year x \$0.06/kWh = \$410/yr

Total Energy Cost Reduction: \$547/yr which would relate to (\$2,400 - \$1,500)/\$547 = 1.6 year simple payback.

Greenhouse gas emission reduction for replacing the motor would be:

1.14kW x 6,000 hours x 1.34 lbs CO2/kWh = 9,166 lbs CO2 reduced

We would then compare to the 0.5% reduction in efficiency:

50HP x 0.746kW/HP x 0.75 x ((100/91.0) – (100/91.5)) = 0.2kW

0.2kW x 6,000 hours x 1.34 lbs CO2/kWh = 1,608 lbs CO2 increased

When applied to the number of motors repaired or replaced in a facility per year, these numbers can become significantly larger.  The use of ESA after a new premium efficient motor is installed can confirm the kW improvement.

Virtually all reliability improvements to motor systems will result in an energy improvement and resulting greenhouse gas emission reductions.  For instance, if we consider proper belt selection, alignment and tensioning.

Over 60% of electric motor driven equipment includes fans, pumps and compressors with a majority of those using belts and pulleys to connect the electric motor to the load.  Losses from belt slippage, energy used to flex the belt as it goes around the pulleys, and belt stretch limit standard belts to having a maximum efficiency of 94%.  This means that 6% of the power produced by the motor is lost.

Energy efficient cog belts have a combined improved efficiency of at least 2% and last longer, meaning greater reliability and less maintenance required, which relates to improved labor effectiveness.  The savings in kWh is calculated as follows:

ES = (HP/n) x 0.746kW/HP x LF x 2% x H

Where ES is energy savings, HP is horsepower, n is the motor efficiency, LF is the load factor, and H is the annual operating time.  For example, a 50 HP, 92% efficient motor operating 75% loaded, 6,000 hours would have the following energy savings:

ES = (50/0.92) x 0.746 x 0.75 x 0.02 x 6,000 = 3,650 kWh/year

From an energy standpoint, assume an average energy cost (demand and consumption) of \$0.06/kWh, then the energy cost savings would be \$219 per year, greenhouse gas emission improvements would be 4,891 lbs of CO2 per year.

Infrared can also have a significant impact.  Let’s consider a 0.5 Ohm loose connection on a system drawing 100 Amps.  The consideration would be (I^2R)/1000 = kW = (100Amps^2 x 0.5)/1000 = 5kW (a high temperature would result, by the way).  If this system operated 6,000 hours, then the greenhouse gas improvements from detecting and tightening this connection would be ((5kW x 6,000 hours)/1000kWh/MWh) x 0.606 Metric Tons CO2/MWh = 18.2 Metric Tons CO2 per year.

If one of your company’s focus is on environmental impact, you may want to consider the inclusion of greenhouse gas emission reduction as part of your business case or recommendation.