Real-Time Utility Monitoring and Anomaly Detection

About Real-time Utility Monitoring
Real-time tracking enables Utilities to optimize energy distribution and balance load across the grid by identifying congestion points and redistributing power flow, thus significantly reducing energy losses. Utilities can also participate in demand response programs more effectively and integrate renewables into the grid, contributing to sustainable power generation. Additionally, early fault detection and remote action enable reduced maintenance costs and downtime.

Anomaly Detection
By detecting anomalies in real time, Utilities can take action right away to eliminate costly waste, save money, and improve overall building performance. For example, a commercial facility manager can receive an alert that a specific room is using more power than usual, allowing them to shut it down immediately and prevent excessive consumption. This helps them save on power consumption, energy bills, and water costs.

Anomaly detection is possible because real-time tracking systems provide granular data about energy and water usage. This information identifies inefficiencies and provides insights that were previously unimaginable. As a result, these systems help organizations reduce energy consumption and cost and improve their overall efficiency.

Compared to interval data, real-time tracking systems deliver more up-to-date information. For instance, a building engineer may have to walk down the basement every morning to read the utility meter and record the numbers. This can be time-consuming, inconvenient, and inefficient. By contrast, real-time tracking allows them to view information online without having to go down the basement every morning. Additionally, a real-time utility monitoring system like STARDOM FCN/FCJ hybrid PLCs can display energy information along with plant status information in one screen so that users have access to all the critical information they need without having to scroll through multiple screens. real-time utility monitoring

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