There are big changes in the utilities industry and they’re coming from all directions: government regulations at both a country and global level are altering how utilities do business, competition is growing, they’re dealing with issues like integrating renewables and an aging infrastructure, and consumer demands are changing.
Technology such as big data and predictive asset analytics can help utilities navigate the ever-shifting landscape, take advantage of new opportunities arising from these developments, and manage new challenges.
In a nutshell, internet-connected smart devices and sensors collect data that can then be analyzed using tools such as predictive analytics.
Let’s break it down into some of the areas where predictive analytics can help:
Predictive analytics tools monitor the performance of utilities’ assets. They create a model of ‘normal’ operating behavior based on historical norms and then compare that model to real-time operating conditions to alert when actual data is deviating from the predicted norm.
The systems continuously monitor assets to provide early warnings of potential failures. This improves equipment reliability and performance by detecting potential problems before they occur, which prevents potential failures or unit shutdowns. Early knowledge of a problematic situation gives utilities time to assess the situation more thoroughly for a controlled outcome, such as scheduling maintenance during a planned outage, rather than rushing for an emergency fix.
Unexpected failures and shutdowns can be extremely costly to utilities. Customers depend upon utilities to provide reliable power and an outage is disruptive and costly for both customers and utilities. For example, the average cost of an unplanned U.S. data center outage is nearly $9,000 per minute.
Because predictive analytics help anticipate where failures are likely to occur, utilities can focus their efforts on the most vulnerable and highest priority assets.
Cost savings and sales
Predictive asset analytics minimize costly, time-consuming, unscheduled downtime by identifying issues early on—resulting in increased availability of the assets—and avoiding unexpected maintenance work that can force utilities to rearrange previously planned schedules and potentially require extra work hours to fix a preventable error.
You can get the most out of your assets and improve business by integrating predictive analytics into your utility asset management program.