The evolution of power monitoring and maintenance

IIoT and Big Data have changed the power monitoring and preventive maintenance landscapes.

12/13/2017


Photo by NASA on UnsplashIn a perfect world, organizations would be able to keep their eyes on IT infrastructure and power management equipment constantly, making sure they are protecting critical power and running efficiently. The reality for organizations such as data centers and other facilities is that they have much more to tend to than the IT environment. Plus, people in an organization are likely to have different experience levels when it comes to responding to power issues.

As the industry evolves with Industrial Internet of Things (IIoT) and Big Data technologies, there has been a lot of innovation in power monitoring and management. Capabilities like predictive analytics offer a second set of eyes on mission-critical equipment, notifying necessary personnel of issues and helping proactively replace components to ensure systems stay up-and-running.

Downtime is disastrous

Downtime carries an enormous price tag, so it is critical to minimize interruption in operations. Consequences can result in corrupted files, hardware malfunctions, and the inability to access critical systems. These are just a few possible negatives outcomes of unexpected downtime, which can significantly impact the ability to conduct business.

Additionally, there is the potential for lost revenue and damaged reputations if business services such as online ordering, phone systems, or other sales tools are unavailable to customers. In many instances, there is very little lag time between system downtime and financial disaster.

While any data center or facility outage is damaging, the downtime downside is perhaps the greatest in a multi-tenant data center (MTDC) environment. A MTDC outage does not impact just a single organization as a service interruption in a private data center would. It can affect several or even dozens of customers depending on the size of the facility, multiplying the impact of downtime.

Despite these challenges, an effective power monitoring and management solution can help to ensure more reliable, higher quality and more cost-effective power. All of which helps to minimize the risk of downtime and disruption.

Changing times in power monitoring

As IIoT and Big Data innovations continue to make their way into IT infrastructures, companies are beginning to understand how they strategically can harness the power of data sciences to enhance organizational operations. Diagnostics, in alignment with advances in analytics, can now be leveraged to establish a power management strategy that greatly impacts operations.

Indeed, with the introduction of predictive analytics platforms that incorporate innovative algorithms and predictive modeling, power monitoring is shifting from a reactive to a proactive model. This new platform bridges data center infrastructure management (DCIM) and traditional operational tools to reduce the risk of downtime and allow organizations to focus on other initiatives that strategically impact the business.

With these types of functionalities, administrators now can predict component failures in power equipment days or weeks before the failures occur. For example, an administrator can be alerted to a potential issue through battery health indicators, reducing the risk of outage due to battery failure. These advancements are major milestones in the ongoing charge to reshape companies’ perceptions of the role power management plays in a holistic IT strategy.

Insights in action

Batteries are a great example of how next-generation power monitoring and management systems for infrastructures can predict the risk of component failures. Valved-regulated lead-acid (VRLA) batteries are a leading cause of failures in uninterruptible power supply (UPS) systems since they provide the power backup and degrade over time. An advanced power monitoring solution can capture some critical inputs surrounding battery health, such as:

  • UPS load percentage, operating mode, service and other logistics
  • Battery make and model—defining maximum and average life based on UPS rating
  • Battery age and temperature
  • Frequency and depth of battery discharge in minutes and percentage
  • Battery test results measuring voltage and resistance over time based on battery age

After inspecting and onboarding a UPS platform, a predictive remote monitoring and management solution can calibrate algorithms to specific factors like those listed above. Based on the parameters outlined in conjunction with the service platform, the solution also can programmed to respond to a predictive alert by arranging a planned maintenance inspection.

In addition to being notified in the event of an issue, organizations can receive monthly report aggregating device performance data, trends, and alarms. Similar to the dashboard, green, yellow, and red colors typically will be used to present an at-a-glance view into the operating status of power equipment.

Moving forward

It’s safe to say that employing the manual, reactive power monitoring approaches of the past isn’t sustainable in today’s fast-paced environments. Unfortunately, in many organizations, administrators still are working with basic point monitoring tools—tools that are designed to monitor a specific technology or component. Consequently, administrators must generate and sift through cryptic monitoring data manually, maintain multiple tools, and contend with conflicting or confusing alarms.

To prevent these issues, as well as to advance power management capabilities and increase efficiency, organizations should consider leveraging a next-generation platform. Whether an organization is managing a single power unit down the hall, or a globally distributed network of expansive data centers, it is critical to employ continuous monitoring—immediately alerting and routing issues so appropriate team members are informed in a timely manner.

Next-generation power monitoring and management platforms, leveraging the latest innovations in Big Data and analytics, are the mechanism that organizations need to address troubling trends before things get out of hand. It’s a win-win for an organization and its staff members who can focus more on strategic initiatives—thus increasing productivity and putting an end to the fire drills that can occur when unforeseen power events occur.

Arthur Mulligan is a product line manager for Eaton’s U.S. power quality service organization.



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