As we move closer to a smarter grid, it becomes apparent that the innovative systems and technologies will touch nearly every position in a utility. In the first of this four-part "Day in the Life" series we explored how a lineman’s job might benefit from the new capabilities of the smart grid. Today we look at how a distribution engineer’s job might be affected.
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8:00 a.m. As our engineer arrives at work, she learns via a text message generated from the utility’s outage management system that several homes are affected by an unplanned power outage in the problem division. The engineer checks her mobile device to verify that the closest line crew with the right skills and tools has already been dispatched to fix the problem.
8:45 a.m. The line crews run into a problem while trying to restore power as they find a non-standard construction technique at the point of failure. Instead of calling the engineer into the field, they use the video camera on a cell phone to show the engineer the situation. The engineer uses asset management and geographic information system (GIS) information to identify the exact equipment that she is looking at, and works with the lineman to solve the problem.
10:15 a.m. As the line crew works on repairs, our engineer receives real-time field reports on her mobile device. The outage management system sends text messages to the cell phones of customers that have signed up for them, letting them know when service will be restored at their homes.
10:30 a.m. After managing the power restoration, the engineer prepares for a budget and planning meeting she has with management about the problem district. Armed with the detailed data (down to the quarter-hour) from the advanced metering infrastructure (AMI), she evaluates the exact voltage profile and loading of the district’s feeders on a per phase basis.
The engineer pulls the actual meter load and voltage data into a distribution analysis package to establish the base case, which is now populated with actual data, not a theoretical starting point. With the updated planning tools and the improved data analytics developed to process the new AMI information, she is able to rapidly determine where there is a need to upgrade conductors or install capacitors, and where it is most urgent. The manager provides an updated population projection for the district, which the engineer uses to estimate load growth, schedule the upgrades, and submit revisions to the capital plan.
3:00 p.m. The engineer receives an urgent automated message that a distribution transformer is overloaded to 300%. She views a geographic representation to determine the location, size, and age of the transformer and reviews the daily distribution transformer reports to identify recent trends related to this transformer’s loading characteristics. With these details, the engineer determines that the transformer needs to be replaced, and with the accurate load information from the AMI, she sizes the new transformer very accurately. She creates a work order that is automatically processed through the work management system, which will assign the job to a line crew, who will then replace the transformer during regular business hours.
In the days before these new smart grid resources, the utility would have waited until the transformer failed and then replaced it—often during evening hours at overtime labor rates—incurring an extended outage for the customers served by the transformer.
By interfacing directly with the smart grid system throughout her day, the engineer makes effective use of the detailed and near real-time data to help daily tasks and the grid itself become more efficient.
Louis Szablya is a director of smart grid integration with SAIC, where he helps clients identify and resolve integration issues that arise as smart grid technologies are adopted.
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