Do it yourself - Counting tap changer operations

ni4ai

October 19, 2020

What a tap changer does

Tap changing is the process by which some transformers can adjust the voltage at the head of a distribution network by changing the coils ratio between their primary and secondary sides. Transformers with this capability are called load tap changers or LTCs. The power demand on a network rises and falls over the day, leading to an inverse rise and fall in the voltage drop along the network. LTCs compensate for this varying voltage drop by stepping the voltage at the head of the network up and down, to keep the voltage at the end of the network within permissible limits.

A tap changer is a mechanism embedded in many transformers that operates to keep the service voltage within reasonable bounds. As pictured below, tap changers use a mechanical switch to adjust the turns ratio between the primary and secondary windings on the transformer. These adjustments occur in response to changes in loading conditions on the distribution grid.

What to look for in the data

Tap change events are characterized by a stepwise increase or decrease in voltage magnitude, such as the one pictured below. These events can easily be detected visually. The challenge here is to detect them computationally.

Do it yourself

Write an algorithm for counting tap changer operations by looking for stepwise changes in voltage like the one pictured above.

Track how frequently tap changer operations occur. Can you determine whether tap changer operations occur more frequently at certain times of day compared with others? Extra credit challenge Can you determine if variable sunshine triggers more frequent tap change operations?

Author

ni4ai

NI4AI is short for A National Infrastructure for AI on the Grid. We are an ARPA-E funded initiative designed to eliminate barriers to developing new analytical tools for the grid. We provide a software platform, open access datasets, content, and access to a community of analysts exploring new applications for real-world sensor data.