It’s Friday at 3 PM. The line crews are just arriving back at the service center. The weather forecast looks grim. A big Nor’easter is due to hit sometime tomorrow. Heavy wet snow could happen. Coastal flooding might be severe. Wind could be steady at 50 mph, gusts over 90. The storm may shift north and miss the area altogether or intensity and bear down on the region.
What do operations managers do? What tools will they need to make the right decisions given the level of uncertainty they face? Budgets are tighter than ever. COVID-19 has severely impacted revenues. Many of the crews are unavailable for work also due to the pandemic. How to minimize the impact of the storm.
What to do before the storm hits?
One of my favorite thought leaders Simon Sinek once quipped, “more information is always better than less.” Unlike COVDI-19, storms hit the region regularly. Utilities know their behavior. Predictive models are plentiful. Utility employees know where networks are most vulnerable. Sometimes in their heads. Or in notebooks. Or on paper maps. Utilities also know where natural hazards are most likely to hit. They know areas subjected to flooding, landslides, tornadoes. They know that valleys experience higher winds. They know a lot. On spreadsheets or data files or on paper maps. Or just know from experience.
They have lots of history.
When I was with the power company, I worked with a guy named Stanley. He was the regional manager of an overhead line service center. All too often I would hear Stanley complain that the people “downtown” were tone deaf to the problems in the field. When something bad would happen, Stanley would inevitably say, while shaking his head, “I could have told you that was going to happen.” Stanley relied completely on his experience. Yet his view was only so wide. He didn’t have access to the insight that the folks downtown had. They in turn didn’t have street smarts that Stanley had.
Making the right decision about crew deployments, staging, material management is to leverage as much information from as many sources as possible. Pulling them together is the real magic. While the data may come from different places and have different formats, they all have one thing in common: location. That’s why GIS is the tool to merge the downtown insights with the field street smarts and so much more. Then decision making is based on facts and science. The science of where.
Storm preparation is a three-legged exercise. It requires superior data management – pulling data together from many sources. Including the network configuration and condition. It is a spatial analysis problem. How to properly predict the distribution of damage. Lastly, it is a dissemination problem. How to communicate to the myriad of people involved. Their GIS if used to its fullest extent is the perfect tool for doing all three. It pulls all this data that Sinek recommends in one place. It understands patterns and relationships. And it communicates directly and immediately from the board room to the dashboard. The physical ones in the trucks and the analytic ones like ArcGIS Dashboards.
There is an old expression called, decision making by the seat of your pants. I will admit that during my time running electric operations, I made decisions based on my immediate gut reaction. They were based on the limited set of conditions that I faced at that time in that place. Certainly, as in Stanley’s case, the decisions were based on his long years in the field. But his access to complete data was limited. Hi access to science-based tools that ArcGIS provides was nonexistent. Finally, his ability to communicate his experience broadly to all but a small group of followers was narrow.
So how do the operations managers make the simple decision of how many crews to deploy the night before the storm hits?
Don’t wait until then! Prepare well in advance. In these three ways.
First, always have an on-going network vulnerability assessment ready. It uses the network model based on the ArcGIS Utility Network. Next, set up an ArcGIS Dashboard for evaluation. Bring in tree trimming history, inspection data, open work orders, historic weather patterns, low-lying flood areas, COVID-19 layers and much more data. Then use Insights for ArcGIS to create what if scenarios. Play these scenarios regularly. Then assign probability to these scenarios. This will guide operations manages to determine:
Where damage is likely to occur
How to deal with COVID-19 vulnerable areas
If they have enough material
Where to stage material and crews
How many damage jobs are likely to occur?
How many crews will be needed to restore power in the shortest amount of time
The earliest when to seek outside help
Where to stage/house and feed outside crews
The exact mechanism to communicate damage, outages and restoration times
Other stuff
The GIS provides the data, analytics and dissemination tools to answer these questions. The technology must be staged well in advance of any emergency event. Then after the event, transparency of the decision making is readily available.
My colleague and friend Stanley has long since retired. Given his experience and the use of the most modern GIS tools I wonder what he could have accomplished.
To learn more about the use of GIS to support the electric utility business, register for our upcoming webinar series.
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