Lead-acid batteries have in the last few decades earned considerably less attention than their lithium-ion (Li-ion) based brethren. Li-ion batteries fill our consumer devices, enable green energy and distributed grid applications, and store energy for the electric vehicles (EVs) promised to transform our future.
Unbeknown to most people, tens of millions of lead-acid batteries are in use across the country protecting some of our most vital infrastructure: telecommunications networks. However, these tens of millions of batteries are today not adequately maintained, and they represent a point of systematic risk in telecom networks nationwide. By applying the tech industry’s hottest topics—big data, automation, and Internet of Things (IoT)—the risk can be converted into a layer of confidence in network reliability and resiliency.
Where is the Risk and Why Does it Exist?
Telecom networks are organized into seven layers from the customer’s end device—Layer 1 (a cellphone or laptop, any device being used to connect to the internet) all the way to data centers and servers, where digital services are being provided (Layer 7). Most customers are not aware of the layers between them and the data center, but pretty much every piece of equipment in the middle layers is backed up by a lead-acid battery of some kind. Every cell tower (or their analog for broadband, field cabinets, and central offices) has anywhere from a handful to dozens of batteries to ensure that service is available, even if power to the site is lost.
The number of sites with backup batteries that carriers are responsible for maintaining is in the millions. For decades, there was no alternative to the time-consuming manual testing process that ensured these backup power systems were ready. Today, manual testing is still the predominant operation but it is so time consuming and carriers are so short staffed, they are lucky to even test their batteries in the last 12 to 18 months.
To make matters worse, the grid itself is posing more of a problem as it ages, and energy demands increase. Power outages are on the rise—in 2009, the United States had fewer than 3000 power outages. Just seven years later that number hit 3879, and while 2017 numbers have not been fully calculated, it appears the country may have topped 4000. Couple these outages with the latest cost estimates of downtime—approximately $9000 per minute—and the problem is obviously critical.
Big Data and Connectivity to the Rescue
One strange quirk of the telecom industry in the modern age is that for all the hype around connected objects, smart homes, and IoT, very little of the actual internet infrastructure is connected. Carriers are now changing that, and while battery monitoring is not new technology, investment has been minimal and most of the millions of backup power systems within telecom networks have been neglected.
In addition to the pressure on carriers to improve resiliency and reliability in the face of a more troublesome energy grid, advancements in battery monitoring and management are making the business case for investment better every day. Battery analytics are one of the driving factors. Of course, to perform useful data analysis, we need to be sure we are working with useful data. Today, the ability to collect and analyze battery data is a reality.
It may seem obvious to say that good analytics requires good battery data, but battery behavior is simple. The electromechanical nature of batteries makes their behavior fundamentally more unpredictable than other systems. At times, batteries can give clear indicators they are trending toward failure, sometimes six months in advance. Other times, a perfectly healthy battery can speed through phases of degradation, and fail in a matter of weeks.
One crucial measure of a battery’s State of Health (SoH) is the Open Circuit Voltage (OCV). OCV is the measure of a battery’s voltage when it has been removed from the charging bus—in other words, the battery is at rest. OCV is important because it indicates the battery’s ability of holding onto the charge put, and provide power during an outage. This measure is rarely recorded by technicians since there is no easy way to disconnect backup batteries from the charging bus.
When OCV (and a host of other measures) are recorded, there is a lot that can be gleaned in the data. In the example below, a large, national wireline carrier, was actively monitoring their batteries. The monitoring uncovered a steep drop in the rested OCV of the battery, and predicted that it would fail in a matter of months.
The battery’s path to failure—steep initial decline, slight rebound of OCV followed by a slow decline toward failure—is a common sequence that highlights the unpredictability in battery measurements. Without the trended data a single manual test during the stages of failure may not have induced a technician to replace the battery. With the data, the pattern is obvious. A weak battery like this could have robbed the string of about 75 percent of its backup capacity, so limiting the time to replacement is critical.
Improving the Outlook for Backup Power
The importance of backup power in telecom is growing. DC power plants have been neglected, but new technology means this can finally change. Carriers can soon bring a higher level of reliability and resiliency to their networks than was previously possible. No more missed failed batteries, no more surprises when batteries fail to hold the networking equipment up during an outage. Carriers should have remote visibility into the health of these assets. Instead of blindly hoping for the best with their backup batteries or struggling with manual maintenance, carriers should embrace automation and big data to make sure our connected futures stay connected all the time.
