Data Everywhere, But Not a Byte to Use
There is considerable discussion about data, how it can improve energy efficiency and reduce the use of electricity.
Frequently, it’s about capturing data of energy usage in the home so as to reduce the use of electricity and cut CO2 emissions. Magazines, such as Intelligent Utility and EnergyBiz, have frequent articles on the subject, but focus on the limited concept of reducing the use of electricity to cut CO2 emissions.
The only technology that can significantly reduce the use of electricity, is the LED, in the home, in industry and commercially. See, Only LEDs Can Significantly Cut Electricity Usage.
Using data to know when to turn on the dishwasher is not the real opportunity.
Controlling home appliances and other equipment has frequently been referred to as the Internet of Things, but it is too narrow a concept.
The importance of data isn’t that it might reduce the use of electricity. The real opportunity lies in improving quality, reliability and lowering costs … for both companies and customers.
General Electric Company appears to have embraced this concept faster than most companies.
Other companies also recognize the importance of data in the digital world, but GE has invested in the necessary software engineers, located in San Ramon, California, and has organized around a concept, which it calls GE Digital.
For example, Baker Hughes released its “FieldPulse model-based, predictive analytics software, enabling operators to optimize production by giving them a clear understanding of an asset’s performance in real time.”
In one sense, GE has an advantage that some other companies lack, in that it has multiple products and installations that can benefit from analyzing data.
But what is involved in making use of digital data?
The initial step is to be able to install sensors in the equipment that’s being manufactured and installed, or in assets, such as pipelines. It can be a sensor to measure stresses on turbine blades and buckets, or to measure flow rates of fuel pumps, etc.
Sensors can be installed on any component or equipment where data on stresses, temperatures, flow rates and on nearly anything that moves, bends or stretches, or can give off signals can be captured. Data can also be captured on what people are doing, such as the time a truck driver spends standing idle due to a breakdown somewhere else in the system of material movement.
The next step is to capture the data, which can amount to trillions of bytes that seem unrelated to each other, and then storing them while making them accessible to various programs. Use of the cloud allows for this interoperability and analysis of data using multiple algorithms.
The next, and probably the most difficult activity, is to understand how the data can be used to forecast problems, predict when equipment should be maintained, the type of maintenance required, how parts can be designed to improve life, how equipment scheduling can be improved, how operator and machine interfaces can be improved plus a thousand other attributes that can result in improved quality, reliability and costs.
And this requires developing algorithms and the analytics that will utilize the data to achieve the desired results.
Finally, compare this vision of digital data utilization with using LEDs for street lighting to reduce the use of electricity.
LED street lights can reduce the use of electricity by 80 to 90%, while using data will result in only small, though still cost effective, reductions in the use of electricity.
Using data to reduce the use of electricity has a tiny payoff, such as knowing when to turn off the LED streetlights … Or use the dishwasher or clothes drier.
Using data to cut electricity usage is a myopic view of the importance of digital data.
Utilities have major opportunities for using data to improve reliability and control costs.
This is why using data is important, not merely to reduce the use of electricity to cut CO2 emissions.
Sensors on transformers, reclosers, capacitors, breakers and regulators, for example, to measure temperatures, surges, voltage drops, and impedances and also to capture other data on the distribution system can help isolate problems more quickly and reduce down time for homeowners and businesses, while also reducing costs.
Smart City and Smart Grid are euphemisms that purport to imply the use of data, but which ignore the hard work and sophistication required to achieve improvement in quality, reliability and lower costs. A smart meter for example, isn’t the key to a smart grid: At best, it’s merely a sensor.
Reducing the use of electricity so as to cut CO2 emissions is the wrong objective for capturing and using data.
The big payoff will come from using digital data to improve quality, reliability and costs … for manufacturers, utilities, drillers, airlines, etc., and customers.
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Nothing to Fear, explains why attempting to cut CO2 is a fools errand.
Nothing to Fear is available from Amazon and some independent book sellers.
Link to Amazon: http://amzn.to/1miBhXy
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