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The push to modernize the aging U.S. distribution grid and the need to bring low-carbon technologies onto the grid in Europe has sparked a new demand for distribution monitoring solutions. Fault current indicators (FCIs or FPIs as they are known in Europe) were a go-to technology in the past, but many utilities are realizing these technologies are falling short of meeting their needs for real-time monitoring in the following ways:

  • FCIs are not as accurate as smart grid sensors
  • FCIs cannot predict faults because they do not have Predictive Grid® analytics
  • FCIs are a point solution, whereas smart grid sensors can support multiple applications
  • FCI’s have hidden costs that make them more expensive than sensors

Throughout the course of this four-part blog series, we will address each of the reasons to conclude why smart grid sensors are a better investment than FCIs. To kick off the series, we dive into why you should care about having the most accurate solution and why Aclara’s Grid Monitoring Platform is more accurate than FCIs. 

Analytics Makes a Difference

Both FCIs and smart grid sensors are used by utilities to detect faults on the distribution lines. However, as shown in the diagram below, FCI’s do not have the necessary analytics to filter out false alarms. As a result, utilities accumulate unnecessary operational expenses from sending crews to chase these false alarms.

Why Smart Grid Sensors Are a Better Investment Than FCIs: Part 1

Better filter out false alarms with smart grid sensors

The smart grid sensors that are part of the Aclara Grid Monitoring platform, on the other hand, are not stand-alone, but integrate with our sensor management system (SMS) with Predictive Grid analytics – a giant technological leap forward from FCI’s in accuracy and filtering out false alarms. When FCI’s were put in head-to-head trials against Aclara smart grid sensors, they generated as many as four false alarms to every true outage event confirmed by our SMS.

By reducing false alarms, the Aclara Grid Monitoring platform is trusted by some of the world’s largest utilities to dispatch crews and to provide accurate data to other back-end systems such as SCADA, data historians, outage management systems, and distribution management solutions.

Analytical processing leads to better accuracy 

The Aclara Grid Monitoring Platform with Predictive Grid analytics is more accurate than alternative solutions because it takes smart grid sensor data through four layers of analytical processing to improve accuracy and effectiveness. When fault current is detected, waveforms of the event are captured along with some background information such as temperature, GPS location, and time, which is communicated over a wireless or cellular network back to the SMS. The software then builds a strong foundation for grid intelligence.

  • Layer 1: Event Capture
  • Layer 2: Event Classification
  • Layer 3: Trending, Planning, and Reporting
  • Layer 4: Predictive Grid Analytics

Additionally, Aclara SMS software classifies faults and disturbances that do not cause immediate outages in an effort to build intelligence about what might cause a power failure in the future. For example, incidents like momentaries or line disturbances are categorized and can be filtered to show trends across a circuit or during certain times of the year. The rules-based engine – a key component of our Predictive Grid analytics software can detect:
Outages due to blown fuses or overhead laterals

  • Load imbalance
  • Blown capacitor bank fuses
  • Blown fuses from vegetation/animal disturbances
  • Improper coordination of circuit protection timing
  • Slack span faults
  • Condition-based maintenance
  • Inputs to enhanced asset management systems
  • Waveform pattern analysis
  • Detection of imbalances and operational inefficiencies

The results are more sophisticated than an FCI or FPI and provide better identification of faults on both feeders and laterals. Aided by such a solution, utilities can promptly spot a fault’s location, leading to faster repair and power restoration, often even prior to the customer calling to report a power outage with the utility. This greatly increases the technologies accuracy and helps operations and distribution engineers get better, more trustworthy information to the field (Read how DTE Energy is using sensors to modernize their distribution network).

Stayed tuned for the second installment of our blog series where we will dive further into Aclara’s Predictive Grid analytics and its importance in preventing outages. Make sure you subscribe to our blog!


Download Our Predictive Grid Analytics Whitepaper


Read part 2 here

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