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Home › Solutions › Interruption & Disturbance Analysis

Interruption & Disturbance Analysis

Why Disturbance Analysis is Important

To improve power system reliability, it’s essential to understand the root cause of power system interruptions, ranging from sustained outages to instantaneous disturbances. Analysis usually requires oscillography or “waveform” data associated with that event.

Waveform analysis is used to inspect faults and evaluate protection schemes. If waveform data is available only at the substation it may be too far from the event. Adding intelligent sensors in additional locations extends visibility and allows utilities to capture waveform data closer to the source of the problem.

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Power lines.

How Intelligent Sensors Measure Interruptions & Disturbances

MM3™ and ZM1™ intelligent sensors are installed on overhead feeders and laterals, and the UM3+™ monitors underground circuits. The Ample® Analytics Platform serves as the data repository and analytics platform for event analysis.

Ample presents the time of the event, the phase or phases impacted, fault magnitude, duration, and sequence of events through the steps of protection. This information gives engineers a better understanding of events and whether protection performed as designed.

Key Features

Sentient Energy sensors and Ample streamline the analysis of system faults and disturbances with advanced waveform capture and effective data management and analytics.

  • Automatic collection of all sequence of event data and oscillography
  • Time synchronized waveforms across phases and locations (+/-64 µs)
  • 256 samples/cycle (UM3+ underground intelligent sensor)
  • 130 samples/cycle (MM3, ZM1 overhead intelligent sensors)
  • 1st-31st harmonics (UM3+ underground intelligent sensor)
  • 1st-22nd harmonics (MM3, ZM1 overhead intelligent sensors)

Interruption & Disturbance Analysis Benefits

Sentient Energy’s intelligent sensors with Ample Analytics are a proven way to quickly implement more accurate event analysis. Understanding the causes of interruptions is a key to improving SAIDI, SAIFI and MAIFI metrics and preventing sustained outages in the future. In addition to the waveform data, MM3, ZM1 and UM3+ sensors provide fault detection (cFCI) and interval load logging (Log-I).

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