Pilot automates transformer data transfer

An important part of the mission of Asset Management is to protect the most important physical equipment of the Western Area Power Administration (WAPA). Power transformers, which convert voltage at different levels, feature high on this list.

Ranging from US $ 1.5 million to US $ 4 million each, transformers are among WAPA’s most expensive transmission equipment. They also have one of the longest lead times. A method of calculating a health index score for these assets is necessary for many maintenance and investment decisions.

One telling factor in a transformer health rating is the megavolt ampere, or MVA, that flows through the transformer. Most loaded transformers tend to have a shorter lifespan than lightly loaded transformers.

Scattered over WAPA territory

While the connection between MVA load and asset health is relatively straightforward, getting this data from all transformers is anything but. The sheer amount of data makes collecting, storing and analyzing a daunting task. WAPA’s data acquisition and supervision control system, or SCADA, receives data from the transformer every 2 to 4 seconds. It is not just a mountain but a mountain range of information.

To further complicate matters, different regions of WAPA have different SCADA systems and methods of data storage. Asset Management does not have access to these systems and uses the Maximo recordkeeping system as a data repository to maintain integrity index information. Despite the importance of these assets to system reliability, WAPA did not have a standard practice, routine or tools to collect and update MVA data from transformers.

The asset management program launch project set out to collect this data in 2015 to calculate the first processor health index scores, and the experience has been revealing. Maintenance had to take three years of data from SCADA and that data had to be sifted and cleaned to make sure the information correlated with the right equipment. This process had to be done one asset at a time as there was no established method for verification.

“It was a huge undertaking that took months,” said information technology specialist Matthew Bailey. Only then could data be entered – manually – in Maximo. “We had to ‘shrink’ the data. Just transferring it all at once to Maximo would overwhelm the system.”

This lack of integration meant that the tedious and laborious process was only performed every three years, leaving planners and analysts to perform critical calculations with old data. As Bailey learned more about how data was used, it became clear that the practice of data management was ripe for an overhaul.

New tools are changing the game

Fortunately, the changing technological landscape provided the opportunity. Over the next several years, WAPA licensed the enterprise version of PI Historian – PI referring to the “factory interface” – which allowed WAPA to expand its use for data storage throughout the world. organization.

This evolution towards a standardized platform made it possible to access new tools, including one called Asset Framework. “It was the missing link in connecting SCADA data to other systems,” Bailey said.

Asset Framework has made it possible to organize the data stored in PI Historian in a more meaningful way, for example by adding asset identification data with devices used in the field. It also allowed PI Historian to store and calculate near constant input data in smaller chunks that could be transferred more frequently to Maximo. A pilot project was the next step to test whether or not these capabilities could be applied to transformer load data.

Testing through teamwork

The Rocky Mountain and Southwestern Desert regions were the first to build and deploy PI Asset Framework and send that data to WAPA’s central PI system. This made the region transformer load data available for transfer from PI Historian to Maximo.

The effort to create an automated process to link PI Historian data to Maximo assets began in spring 2020. Using the RM and DSW transformers as sample data, the proposed framework assigned identification numbers to the assets. assets that can be used on all platforms. The pilot also established an integration between TIBCO and PI Asset Framework that ultimately allows PI data to be sent to systems such as Maximo.

An interdisciplinary group has come together in a spirit of collaboration to achieve this goal. Members of the IT team, head office and regional asset management specialists, and subject matter experts on Maximo, PI Historian, and Enterprise Architecture all contributed to the project.

There were a lot of challenges and obstacles involved, Bailey acknowledged. “But the team did a great job overcoming them,” he said. “And we did everything remotely during the pandemic!”

Part of the larger image

The framework successfully retrieved accurate weekly MVA data, calculated transformer load, and transferred that data from PI Historian to Maximo. Trending over time, this data will refine the Health Index analysis and paint a more detailed picture of the condition and performance of critical assets in WAPA’s fleet. Another important advantage of the methodology is that it reduces the time commitment and human error which are part of a manual process.

“Data integrity is a key principle of the Asset Management strategy to deliver consistent and clean asset data to our end-user customers,” said Chris Lyles, vice president of Asset Management. “Developing this framework minimizes the human element of manual load calculation and helps us achieve a much better end state. “

The success of the project suggests that the process is scalable and could bring the same benefits to other regions as their data is integrated into PI Historian over the next two years.

“We’ve proven that we can get data to our consumers much faster with this new framework,” Bailey noted. “It can potentially be applied to other assets besides transformers.”

The standardized PI system that served as the basis for the pilot project is a central part of WAPA’s data as a strategic effort. The implementation of centralized storage for data makes it more accessible and more consistent in presentation.

As it becomes easier in WAPA to locate and analyze information for business decisions, short- and long-term users will better understand the value of real-time data.


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