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Occam's Razor and OMS

Ross Boozer's picture
Senior Business Systems Analyst PSEG

I have experience in ADMS, GIS, and OMS. I like to talk about the electric industry, technology, science, and putting those together to solve problems.

  • Member since 2020
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  • Mar 10, 2021
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If you're familiar with Occam's Razor, you know the simple solution to a problem is the most likely. If you're not familiar with Occam's Razor, you know this is true but you haven't heard it stated in such a way. We all know this is true. We can offer a very complicated solution to a problem. It might be right. But, given the choice between ten steps to a solution and a hundred steps, we're probably going to try ten first. The basic principle of Occam's Razor, hopefully, stated simply.

If you're familiar with OMS, you'll know that the Outage Management System is a key part of a utilities tools in restoring power to customers. If you're not familiar with OMS, you have yet to realize that when you call or text or push buttons on your phone to report an outage, you're giving OMS some of the basic information it needs to figure out who is out of power and how best to prioritize your problem when there are many decisions to be made about restoration. I feel compelled to remind everybody here: always report your outage.

OMS is responsible for taking the information from customer calls, analyzing those calls, and giving dispatchers and operators good information on the location and size of an outage so we can get somebody out there fixing problems as fast as we can. Occam's Razor is responsible for guiding our analysis to make the best guess as to what happened and where, the majority of the time. But how are we doing this and how are they related?

If I have a single customer reporting an outage, my best guess is that one person has a problem. If the neighbor calls, I can do some circuit analysis, or pull up my trusted GIS, or see if I might have some digital imagery available to say how likely is it that two people next to each other have two separate problems. I can tell you from Occam's Razor, I can tell you from anecdotal experience, and I can tell you by the logic that guides most outage prediction decisions: not very likely. If this makes sense, we can go bigger. We have two neighbors saying they are out of power. In this example, we can give this a quick "transformer outage" stamp and move on. Who else is out of power? Okay it looks like a customer up the road has a problem with another transformer outage a little further down the road. We see where this is going. What is the common point of connection for all of these customers? Oh and is also able to respond to a fault event in some way? You've got it: a fuse blew and is encompassing all of our distinct points of customer reported outages. We can go to the recloser and repeat. We can go to the circuit breaker and repeat.

We take Occam's Razor in the OMS world to say: assume a single problem. If we do this when we have thousands of customer calls, we can have a hundred outages, or we can have one outage. We need to find a common point among everything we know and work from there. We need to make decisions quickly in a storm for restoration and for public safety. We can use logic. We can put that logic in our software. We can train our folks with that simple logic. We can restore customers safely. OMS and Occam's Razor. It's not something I think about very often or explain very often. It's such a core part of what we do. But, it's important that we understand it and use it to it's fullest, or simplest, potential.

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Matt Chester's picture
Matt Chester on Mar 10, 2021

If I have a single customer reporting an outage, my best guess is that one person has a problem. If the neighbor calls, I can do some circuit analysis, or pull up my trusted GIS, or see if I might have some digital imagery available to say how likely is it that two people next to each other have two separate problems. I can tell you from Occam's Razor, I can tell you from anecdotal experience, and I can tell you by the logic that guides most outage prediction decisions: not very likely. If this makes sense, we can go bigger. We have two neighbors saying they are out of power. In this example, we can give this a quick "transformer outage" stamp and move on. Who else is out of power? 

I've never had the benefit of being in the control center when calls like this start to come in-- I'm curious how quickly these diagnostics are run and completed? Especially using the modern tools in the OMS world that you mention, is this more or less an instant calculation, or are you still running through possible scenarios like Dr. House and his team? 

Ross Boozer's picture
Ross Boozer on Mar 11, 2021

Hi Matt. Thanks for reading. First, I think it's great to say "I don't know something" or "I've never done that" because I sometimes forget not everybody spent time "on the floor" in a control center. A helpful reminder for me and something I think we need to fix for your personal knowledge. I'm sure we could find somebody who would be willing to invite you to have a look for yourself. The trick would be to do it during a storm!

Okay, as far as how quickly, I would give a very broad "it depends" because you have so many varying degrees of technology available right now. Not everybody is using AMI for example. Customers don't have their power company on speed dial. More specifically, a few seconds to a few minutes. Especially at night when people have to first wake up to realize the power is out. Of course this is also up to the utility to determine how much time can pass between calls coming in before an outage is locked down from analysis. You want to give a few minutes for all of the data to come in, AMI, calls, and SCADA. But you don't really want an open analytical window where you run the risk of pulling in an unrelated outage. I remember watching an outage come in at night in a rural area. A few transformers. Then a few fuses. Then bam, tripped to lockout, all calls captured in out outage, dispatch, fix, restore.

Finally, you wonder if this is instantaneous. I would actually say, yes. As soon as the data is available, we're looking at it. When more data comes in, we're adding that to our analysis. It's happening 24/7. If more information comes in later, we supplement our analysis. In real time. As real time as possible. As accurately as possible.

Matt Chester's picture
Matt Chester on Mar 11, 2021

Fascinating-- really appreciate your detailed answer and insights. Keep them coming!

Bob Meinetz's picture
Bob Meinetz on Mar 10, 2021

Ross, finding an repairing outages is not unlike debugging computer code. Many times, I've been finishing up a magnificent application with a final few tweaks - then when I run the application again, suddenly nothing works the way it's supposed to.

Before rewriting code (and possibly making the problem worse), I have to remind myself to first "Shift-Alt-Z" (undo) the changes I just made, to back-step until the app works again.

Though obviously that's not an option with line repair, it's my Occams' Razor - before finding the solution, ya gotta find the problem first!

Ross Boozer's picture
Ross Boozer on Mar 11, 2021

Bob, I think you got to the heart of it. It's not really about why is OMS special, it's about what are the fundamental approaches to solving a problem. I was illustrating that for OMS and how that's actually a core part of program functionality. But, as you know, debugging can benefit from the same approach. Stop. Think. Try again.

I like to say when I work with data, it's hard to fix a delete with a delete. Undo. Slow down. What am I actually trying to solve? Am I actually solving it?

Unfortunately with outages, undo isn't on a keyboard.

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