When users consider what comprises their power monitoring and power management systems, they can think of many components. There are the more obvious devices and sensors found on facility equipment and building mechanisms. But, one might also consider the digital cloud environment where power monitoring data is collected, stored, and analyzed. For any organization to succeed, there needs to be a smart and comprehensive usage of data analytic tools to discover insights and optimized performance. For a facility’s power monitoring solution, that resource should be continuously improving power resiliency and efficiency.
Power Analytics and Algorithms, Briefly Explained
How does all that data, collected through power monitoring systems, become meaningful insights and, in some cases, urgent alerts for action? In short and simple terms, proprietors of power monitoring systems and equipment develop algorithms to recognize different items. Algorithms either detect deviations from what it is trained to look out for or identify particular aspects of an operation.
Software engineers often use machine learning to develop algorithms in order to complete the data analysis. They train the algorithm with massive amounts of data from the devices and environment where it will be deployed, so it knows what conditions and patterns to recognize.
Levels of Power Monitoring and Analysis
A connected device is implemented by equipment, room, or at a very localized level. The power monitoring sensors and meters can process and detect data anomalies in milliseconds. While the recognition time is fast and accurate, there are drawbacks to relying on connected devices alone for power monitoring. Namely, the localized data access gives facility managers a very limited scope of understanding as to what is going on since it only retrieves and analyzes recent data readings of that equipment. Further, a connected device can alert you of a deviation but often can’t perform higher levels of analysis to provide optimization suggestions.
Edge computing relies on more data gathered by a collection of connected devices. Power monitoring at the edge level can happen on-site in dedicated server rooms, or at edge data centers. Because this level of energy monitoring draws data from a wider pool of data, it can deploy more sophisticated functions, such as identifying the source of disruptions to your systems or enforce self-correcting and self-optimizing adjustments as needed.
Employing power monitoring tools at the cloud level grants your system the most data to work with, thus allowing for even greater analytic reports and advisory actions. At this level, your organization can retrieve data from connected devices from within your operations, others’ networks, and your customers’ data. All in all, this creates the potential to attain a fuller understanding of your global operations when it comes to energy requirements and consumption rates.
Power Up Your Power Monitoring with Schneider Electric
EcoStruxure Power platform digitizes and simplifies your facility’s electrical distribution system. Its host of connected products and sophisticated analytical services help organizations take charge of their power management goals and requirements. Not only can EcoStruxure Power help you prevent power disruptions, but the platform and software can also identify ways to maximize your operational efficiency. This allows you to create even more value for your customers.
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At Critical Systems, the people come first, from our employees to our customers. We strive to attract and develop the best talent in the business. Our goal is to deliver innovative solutions for the purpose of making every building secure, efficient, and effectively managed. Serving the Washington D.C., Northern Virginia, and Baltimore regions, SEBCSI provides innovative solutions for your commercial building or facility. Visit our website and follow us on Facebook, Twitter, Instagram, and LinkedIn today! If you’re looking for more information or interested in working with us on your next project, please contact us!