Ten years from now, no one will believe that back in 2014 the vast majority of industrial machines were not specifically monitored.
You might assume that industrial enterprises are highly sophisticated and optimized. That's true for most of their resources, but not when it comes to energy. When our team at Lightapp visited hundreds of industrial facilities that spend from $100,000 to $5 million on energy every month, we discovered the same hard-to-believe truth time and again: most facilities only have a utility meter at the entrance to the facility.
That's it. There's no visibility into granular energy consumption. If there are additional meters on subsystems within the facility, they're used for production and manufacturing processes. Energy usage is simply not looked at holistically.
If you ask most CFOs how they can reduce their energy bills, they'll likely shift responsibility to facility engineers. CFOs receive the utility bills and pay them, but are usually unaware of energy saving opportunities. Without the tools to track and benchmark energy efficiency, they are unable to lead energy savings initiatives.
Interestingly, raw materials and supply chain optimization have undergone major improvements for the past three or four decades, and it would be almost impossible to find a factory that doesn't employ them. Expenditures on labor and maintenance have also been optimized where possible. Energy as a resource is one of the last significant spending buckets available for optimization.
If it isn't measured, it isn't managed. And if it isn't managed, it's wasting a heck of lot of energy. And nobody even knows about it.
Who can drive the change?
Market transformation and education doesn't occur in a day.
So far, we have been selling systems with no incentives at all. Yes, though this may surprise my friends in California, factories actually spend their own money on buying our systems.
In the last four decades, incentives have been provided for energy-efficiency measures that promise "measurable and verified savings." In general, constant monitoring and software systems are not incentivized. Though it provides many benefits, it is harder to prove how a system that operates constantly in the background is directly responsible for energy savings. Opower's service in the residential arena is one of the first exceptions.
Our request to regulators is simple: encourage the continuous monitoring of any energy-consuming device that uses more than 50 kilowatts or the equivalent in other types of energy. This can be achieved by providing incentives for monitoring systems, sub-metering installation, or software usage on a continual basis (SaaS). Results can also be attained by requiring measurement of any machine or process that consumes more than 50 kilowatts.
In a recent article published by Greentech Media, Jigar Shah pointed out the eight drivers of industrial energy efficiency. Number one on his list is policies and programs. Number two is energy management systems. Tying these together, we propose an easy-to-understand, highly cost-effective, overarching policy that will bring sub-metering and energy management systems together, creating tremendous benefits for industry factories and society at large.
We'll call it the 50-kilowatt initiative.
Why start monitoring at 50 kilowatts?
A 50-kilowatt or bigger machine, consuming electricity priced an average of $0.10 per kilowatt-hour and running at a 50 percent load factor, costs $20,000 a year. Assuming that sub-metering infrastructure costs $200 and the average savings are at least 5 percent, the cost of hardware is recovered in less than three months. But industry often employs devices using 400 kilowatts and more, so the business case becomes a no-brainer.
In residential applications, you only care about how much electricity you used. In industrial applications, that actually doesn't matter. You may have used 100 megawatt-hours one month and 50 megawatt-hours the next. Which is better? That's a trick question. The answer is revealed only if you know what the electricity was used for, the amount of finished goods produced, and the usage was normalized according to other causal factors (such as external temperature, humidity, etc.).
Energy Intensity, or energy per unit of product, is the real metric. If industrial facilities want to measure improvement, that is what they should track.
Today, in the best-case scenario, energy intensity is measured on a monthly basis (total energy consumption divided by amount of finished goods). But to get real value, energy intensity has to be measured on a product-by-product and line-by-line basis at a day-by-day and hour-by-hour resolution.
Image: Lightapp's industrial energy intelligence system shows the energy intensity (energy consumption per ton of finished goods) of an industrial customer going down 26% in less than ten months, with no capital investment. And yes, the effects of production volumes, external weather, etc. have been normalized.
The benefits add up quickly
For anyone outside the industrial sector, it would sound impossible that millions of dollars are managed based on barely any data. Still, before they meet us, most customers don't see any reason to put an effort into getting granular data. As a result, we often walk through the following unique benefits of detailed online continuous data monitoring with our prospective customers.
Identifying energy improvement opportunities: You might think that production lines in modern facilities (the kind you see in the movies) run at a constant level. That's a myth. Often, the factory workers themselves believe in it too.
Take the energy consumption of a plastic injection line in a busy factory, shown below. As you can see, the line is anything but straight. The valleys are opportunities to discover best practices while the peaks show us where to focus on energy reduction (when looking at the energy intensity, of course). Yet all these precious opportunities are lost if you only look at facility-level data.
Initiating behavioral changes: When granular data is available, specific targeted messages and alerts can be generated. It is very easy for chief experience officers to ignore or dismiss spreadsheets, theoretical calculations, or the marketing materials of vendors selling energy-efficient equipment. On the other hand, it's much harder to ignore specific and accurate data.
Which of these messages is more likely to initiate action: "Line six is currently using twice as much energy as expected based on its current production level," or "compared to last February, the factory consumed 3 percent more kilowatt-hours."
Identifying waste: This is one of the easiest issues to identify. Energy waste is quickly discovered on an hourly level at each machine and line, especially during periods when there is no production.
Discerning causal factors: What causes energy consumption to go up or down? In industry, the main factor is production levels. Looking at a monthly or annual bill at the facility level, it is impossible to understand the impact of quantities or batch sizes, shift and manufacturing parameters, or line reconfigurations.
Making energy-based operational decisions: Accurate energy data affects operations in a good way. Batch sizes are optimized, maintenance times are rescheduled and manufacturing lines are retuned. In most cases, when energy consumption is not optimized, the facility is not optimized. Often, energy usage is the first sign of a bigger problem.
Rate optimization: Data allows manufacturing facilities to respond to time-of-use utility rates. I have seen the effort that goes into explaining peak day pricing to customers. And guess what? If anyone understands it, it's only the energy manager, and factory response is minimal. However, when an hourly and daily score is kept, the costs and opportunities of a specific rate at the machine level are revealed. We see some of the biggest savings in this area. Suddenly, the facility as a whole sees the incentive in responding to rates.
Making smart capital investments: Making capital investment decisions becomes much easier when data is available. It is frustrating to make a multi-million-dollar investment in new energy-efficient equipment, only to see a small reduction in the bill at the end of the month, which may or may not be attributable to the purchase.
Financial insights and reporting: Data has a huge impact on financials. Through our partnership with one of the world's leading accounting firms, we learned that even very large industrial corporations sometimes consider energy as a fixed rather than a variable cost. Detailed energy data provides the tools to allocate energy accurately, at the product level. This enables significant, positive changes in the financial reporting. Sometimes it reveals that products are not profitable or not priced correctly. This factor in itself is one of the most significant benefits of granular monitoring.
Bottom line: Without data, a lot of money is left on the factory floor.
By setting standards for metering equipment on machinery over 50 kilowatts, we can dramatically expand the intelligence and energy efficiency of our industrial sector.
Lightapp develops a cutting edge industrial energy intelligence SaaS platform used by dozens of customers in the U.S. and Israel. Boaz Ur is head of business development and strategy at Lightapp. Previously, he managed the Demand Response Program portfolio at PG&E.