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Home › Automatic Phase Identification: Utilizing Intelligent Line Sensors to Improve Circuit Phasing Accuracy

Case Study

Automatic Phase Identification: Utilizing Intelligent Line Sensors to Improve Circuit Phasing Accuracy

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Background

While Distribution Automation continues to provide advanced monitoring and control at strategic points on distribution circuits, advanced Line Sensor Monitors are fast becoming a cost-effective alternative as either a precursor to future Feeder Automation deployments or a complementary add-on to circuits with existing Feeder Automation. Feeder Automation deployments, while achieving dramatic reductions in reducing the customer minutes associated with outage duration, are typically limited to a portion of the total utility circuits and for a limited number of locations on those circuits (1-2 locations). Sentient Energy customer’s line sensor deployments range from deployments on circuits without Substation SCADA or Feeder Automation to deployments on circuits with full Substation SCADA and very large numbers of Feeder Automation sectionalizing devices. In either case the addition of the Line Sensor Monitors are providing additional and significant duration reductions with the added benefit of providing advanced analytics and applications to reduce outage frequency and improve various aspects of feeder optimization in areas such as load balancing, voltage stability and power quality.

Sentient Energy currently has over 30,000 advanced line sensors installed on utility circuits and customers are now beginning to take advantage of the benefits beyond outage duration.

The Challenge

Accurate phasing designation on distribution circuits has been a challenge for electric utilities for many years since phase referencing is still primarily established based on pole framing positions of overhead feeder and lateral conductors. Even at the feeder backbone level, phase “rolling” that occurs when conductors are positioned differently between pole locations or deployment data entry errors can cause grid equipment such as line sensors being incorrectly associated to conductor phases. Even if installed 100% correctly at deployment time, subsequent construction changes or post-storm restoration on circuits can cause conductor phasing to change affecting GIS, OMS, DMS and real-time monitoring devices. These changes accumulate over time, leaving utilities with increasingly faulty information about connectivity and interdependence of their distribution infrastructure. Just as inaccurate mapping data would make a pilot veer far of course, phasing database errors lead to wasted time and resources, increased imbalances and more frequent outages, suboptimal interconnection and even potentially dangerous switching decisions at utilities. Moreover, they reduce dispatchers’ confidence in their most advanced control and management systems, often leading to a reversion to the “tried-and-true” methods of several decades ago, trapping the utility and its customers in the past.

The Test Case

Sentient’s most advanced sensor deployment is Florida Power & Light (FPL) with 17,000 line sensors currently installed and an additional 8,000 devices planned for 2017. The currently deployed devices were installed on conductors with phase assignments made based on conductor positions on poles. Phasing accuracy is dependent on the installation process and the ongoing accuracy is dependent on utility processes to ensure permanent network changes affecting phasing are accounted for in various asset systems. While it was assumed that some level of phasing errors exist, there was no real knowledge as to the level of accuracy associated with phase assignment to line monitoring devices until data from the line monitors began to reflect fault and interval load data that was not in agreement with other operational data resulting from outages or transient faults. To address this uncertainty Sentient Energy developed a new analytic capability to provide accurate phase detection leveraging the advanced analytic capabilities of its MM3 Line Monitor. Sentient Energy deployed this new analytic software module, called Auto Phase Identification, to its MM3TM Master Monitor at Florida Power & Light (FPL) via FPL’s Silver Spring Networks mesh communications system. Using Sentient’s Sensor Gateway technology, this over the air upgrade for 9,000 devices of FPL’s large sensor fleet was completed quickly and didn’t require any field visits – a few mouse clicks were sufficient.

The Solution – Intelligent Line Sensor Auto-Phase Identification

Leveraging the key capabilities of GPS clock precision and electric-field sensing, the MM3 sensors now provide daily phasing analysis, confirmation, exception detection, visualization and reporting across the entire feeder backbones that are being monitored. Exceptions are noted and communicated in reports and in Sentient’s AmpleTM Phase ID application where users can view a summary of exceptions by area, substation and feeder.
sentient-energy-Automatic Phase Graphic 1 1024x663 1

Figure 1: Sentient Energy’s Auto Phase Identification Architecture

After upgrading 9,000 of the currently installed MM3 Line Monitors these devices immediately provided reports of phasing validation by comparing the assigned phase at installation to the automatic phase identification performed by each sensor

The Results- In Progess

To gauge the magnitude of potential phase identification errors in FPL’s database, an analysis was performed across 9,000 MM3’s with the new AutoPhase Identification capability. The results are depicted in Figure 2.

sentient-energy-Automatic Phase Graphic 4

Figure 2: Auto Phase Detection Results

The results indicate an overall conflict rate or 12%. Field validation was performed on a sample of the devices and the results of the phase identification was validated and the various sensor asset databases were corrected.

Other significant results include:

  • It was confirmed that Auto-phase Identification can be achieved using a single reference site for the entire utility. Further analysis indicates that no reference devices may be required.
  • Phasing exceptions for C phase overhead conductors were significantly less that A & B phase
  • With phase validation scheduled daily, the need for line sensor labels indicating phase is no longer required
  • Newly arisen conflicts will be detected via the daily report, providing quick indication when new work on the distribution system has led to a misconnection
  • Line sensors provide the critical field data to effectively ensure a 100% accuracy of the utility’s phasing information.

Next Steps

As FPL activates existing MM3 Line Monitors already installed and deploys an additional 8,000 devices in 2017, Auto Phase Identification will be enabled effectively ensuring phase accuracy without previously required labels and data entry of phasing information. The Auto Phase Identification software is available to Sentient customers for easy over-the-air upgrade from the Ample system. Sentient stands ready to support utilities with this new capability with the anticipation that phasing conflicts could be higher for other customers. Sentient has also added online phasing conflict reports in its Ample Analytics Software to reflect the ongoing results of Auto Phase Identification as shown in Figure 3.

sentient-energy-Automatic Phase Graphic 2 1024x408 1

Figure 3: Ample Analytics System Phasing Results Reports

In 2017, Sentient Energy is introducing new Line Sensors for lateral lines, underground cables and feeder level locations for voltage measurements. By providing coverage across the entire distribution circuit down to lateral conductors phasing accuracy can be extended to these locations and be used to validate and correct supporting utility applications that depend on phasing accuracy as depicted in Figure 4.

sentient-energy-Automatic Phase Graphic 3 1024x732 1

Figure 4: Utility Systems Dependent on Accurate Phasing Data

The improvements in the quality of the data related to phasing is expected to reduce deployment complexity and time, while ensuring the quality of fault detection, feeder balancing and other planned analytics and applications. The age-old utility challenges of phasing accuracy can be addressed with automated phase detection and conflicts resolved across all affected utility applications on a continuous basis and in a timely manner, closing this critical information gap and helping utilities finally taking full advantage of all their data-dependent operations systems

About Sentient Energy

Sentient Energy makes electric power delivery safe, reliable and solar ready. Sentient Energy offers the Utility Industry’s only grid analytics system that covers the entire distribution network with intelligent sensors that are quick and easy to deploy, as well as analytics that detect and analyze potential faults and other grid events that can disrupt electric service or present potential hazards. We lead the market with the largest mesh network line-sensor deployments in North America, and partnerships with leading utility network providers including Silver Spring Networks, Landis + Gyr, Cisco, and AT&T.

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