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What Does GIS and the Octopus Have in Common?

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Nothing.

They are opposites.

The octopus is the sea creature version of the chameleon, except better. Octopuses are masters of disguise. They turn colors. They even contort themselves to resemble deadly predators. They do this for their own protection. What you see with an octopus is probably not what you get. They are all about hiding, masking their identity, fooling their preys.

GIS is about discovery. It uncovers what others can’t. It is about unmasking patterns, uncovering hidden hazards, exposing flawed policies and practices. It beats down long held assumptions. It is perfect for digital transformation.  It can break old habits.

Here is an example of a hard habit to break.

 It’s the old ten worst circuit habit. It goes like this. Distribution planners compile a list of the ten least reliable circuits. Utilities measure the total time customers on that circuit are out of power during a specific time.  They then rank them on that basis from top to bottom. If a circuit ends up in the bottom, distribution planners place it on the ten worse circuit list.

Here’s the rub. Many utilities have implemented smart grid or at least a degree of circuit automation. This means that circuit pieces are not always fed the same way. Parts of circuits are automatically moved from one circuit to another, sometimes for very short periods of times. Other times, utilities reconfigure even temporarily for days or even months. The notion of poorly performing circuits can get quite cloudy. In fact, this concept might, like the octopus mask persistent pockets of poor circuit resiliency. 

Distribution planners will often reconfigure poor performing circuits taking bad sections and attaching them to good circuits. They take good sections and attach them to bad circuits. This takes the bad circuits off the bad circuit list, while moving the good circuits lower on the ranking. This may not focus on what really matters. Customers who were on bad sections of circuits may continue to get bad service.  Certainly, if customers are on the end of poorly performing circuits, moving them to better performing circuits could help. Yet, the factors that contribute to the bad reliability may persist.

According to the US Energy Information Administration, about half of all electric meters in the US are smart. That means utilities have access to power outage information down to 5-minute intervals or less. Yet even with these, utilities often will associate each customer to their normally assigned circuit. Even though the credit (or debit) of an outage event might be associated to one circuit, that outage could have occurred during a period when the customer was temporarily connected to a different circuit.  For the other half of the electric customers who don’t have smart meters, it become an arduous task of tying to figure out without real time data, when a customer was out of power which circuit that customer was connected to at that time.

The intent of the ten worse circuit list was to uncover and then correct reliability problems. It would be far more effective to focus on the customer rather than the circuit and the actual outage events themselves. Since GIS, unlike the octopus, reveals patterns and uncovers trends, utilities can map customer outages over time along with the location of where outage damage occurs. This is simple for utilities with smart meters. The smart meter data includes the exact time and location of the customer outage and it’s duration. For utilities without smart meters, it is more difficult, but not impossible. Most utilities will have records of outage events in their outage management system. However, they don’t have to associate customers to a circuit for this exercise. All they need is individual outage event data. This exercise reveals:

  1. Pockets of poor performance location
  2. Emerging trends in poor performance by location - trends over time, monthly, yearly or even longer.
  3. Outage duration and frequency from the customers perspective, not theirs.
  4. Power quality issues. As utilities implement smart grid, outage duration drops. Yet momentary outages or short power failures increase. 

GIS, visualizes customer impact clearly.

Utilities can use other spatial information. They can discover incidents of cars hitting poles to locations more likely to have accidents. They can visualize curved roads. They can even get a better understanding of their customer’s profile using their demographic data.

Once they do this, then they can identify where to improve resiliency. And correlate those measures to the circuits sections that are within the areas that need improvement.  Rather than focus on the legacy of the circuit, they can focus on the real issue – customer impact.  Sure, they can continue to track circuit section performance as well, particularly for those circuits that experience major events, but focusing on what the customer sees reveals patterns that may be hidden.

Think about what GIS and the octopus have in common. Nothing. Leverage the power of GIS for discovery. This avoids using legacy processes that could mask real issues.

To learn move about how GIS helps improve customer experience for utilities visit our customer engagement page.

Bill Meehan's picture

Thank Bill for the Post!

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Discussions

Matt Chester's picture
Matt Chester on Dec 11, 2019 10:08 pm GMT

According to the US Energy Information Administration, about half of all electric meters in the US are smart. That means utilities have access to power outage information down to 5-minute intervals or less. Yet even with these, utilities often will associate each customer to their normally assigned circuit. Even though the credit (or debit) of an outage event might be associated to one circuit, that outage could have occurred during a period when the customer was temporarily connected to a different circuit.  For the other half of the electric customers who don’t have smart meters, it become an arduous task of tying to figure out without real time data, when a customer was out of power which circuit that customer was connected to at that time.

Fascinating-- will this sort of feet dragging be less prevalent as the smart meter percentage drifts above 50%?

jacques busi's picture
jacques busi on Dec 16, 2019 9:35 pm GMT

Original approach...some confusion in the article between continuity of service and power quality...it’s quite seldom smart meters gets real PQ features ...specially time synchronisation is poor versus real PQ analyzer

Bill Meehan's picture
Bill Meehan on Dec 18, 2019 1:53 am GMT

Thanks for commenting - you are correct - smart meters are not intended for PQ - I was making the point that as utilities implement smart grid - self healing, momentary outages will likely increase - it will be good to know where they occur and what customers are impacted.

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