Inspiration

There are already applications within the Power business that allow health and status monitoring of a power plant and its assets (i.e.- Operations Optimizer). There are also applications that enable asset modeling, or the ability to view the entire install base composition (i.e.- Power Digital Passport).

What is missing, however, is the ability to forecast potential gains from equipment additions and upgrades that GE offers within its product catalog. With the Alstom acquisition and the usage of Digital Twin, GE Power is in a position to provide balance-of-plant solutions to any customer.

What it does

This tool uses preexisting data (such as the data that lives in the Operations Optimizer application), as well as the install base. Digital Twin functionality is then utilized to replicate current operating scenarios on different equipment models, allowing identification of potential gains or losses on upgrades or replacements.

How I built it

We utilized the given timeseries Waukesha dataset as inspiration to visualize as-is performance and forecast to-be scenarios.

Using Predix microservices such as timeseries, we augmented the dataset to create multiple product lines to replicate Digital Twin scenarios.

In line with modern application architecture, we pushed two separate Predix applications: 1 client & 1 server. Each application is independent of the other and allows for full GE store capability.

What's next for Digital Power Plant Forecast

The digital power plant forecast will hopefully be integrated into the "killer apps" of the business, allowing for full integration of both asset health monitoring and full product line comparison.

Using the mobile-ready front end technologies that Predix provides, this application will be mobilized in order for different audiences (plant managers, customers, GE sales, etc.) to take advantage of its capability. Mobilization will be especially meaningful for those audiences on the floor.

By providing the integration into the GE store, this application can utilize historical trending and analysis to predict more accurate financial outcomes as a result of our growing product catalog.

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