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The secrets of great grid modeling

One particular conference session in San Antonio this week puts the “distribution” in DistribuTECH 2020. A couple of smart insiders from the Electric Power Research Institute (EPRI) and a few utility insiders (from Duke, Salt River Project and Alabama Power) joined together to tell a standing-room-only audience a few insights into how modeling is evolving (and how utilities can get a handle on that evolution, even get in front of it a bit).

“Our industry really depends on complex network models,” said Randy Rhodes, Technical Executive at EPRI to start off the session. “And it’s getting harder and harder to manage that.”

Why? Well, all the changes in the grid, all the new connections and points, and the onslaught of more and more and more data—along with more coordination (and more access) required across the board.

“Our traditional thinking about the way in which we build the models for power flow is changing,” he added. “We’ve got many sources providing data into the applications and then many more applications [than in the past] that want to run that data.”

So, how hard can it be to build a good model?

According to Rhodes, it’s similar to one man climbing one mountain without a rope and trying to do the impossible (or what was thought to be impossible). But, behind that successful climb was practice that involved a team of peers and coaches and an entire background of collaboration—it just isn’t seen in the final story.

Additional members of the panel also emphasized that background collaboration and tapping into to expertise around your own utility, as well as from other utilities and vendors, too.

Along with that major bit of advice of talking and listening and making this almost a crowdsourced project (to get a handle on that modeling evolution), the panel made these additional suggestions:

  • Invest in data clean-up (and then keep investing in data clean-up).
  • Know your bumps and your bottlenecks. Don’t ignore how much manual prep is required for your modeling or how long the journey is for that data to move from the field to the tech in planning—and just how those inefficiencies may impact the build out, results and final timing of what you’re trying to model.
  • Find out all the fingers in this data pie. Who has access and what exactly are they doing with the data?
  • Keep an eye on regional model differences (such as transformer types, shared neutral conductors, device bypasses) and model population challenges (such as integrating solar data, auto throw overs, reserved capacity and remotely programmable devices).
  • Look at scaled agile methodology for very large projects (but be aware that this shifts your focus to near-term).

 

We’ll be covering the entire DISTRIBUTECH 2020 conference live on the blog and on Twitter and LinkedIn. Come join the conversation. Or visit us onsite at the booth at 2809 or read more below:

 

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