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Analytics investment delivers dividends for Infigen Energy

Rohan Pearce | July 14, 2016
Renewable energy producer looks at boosting the detail of the data it receives from its windfarms

The single-machine proof-of-concept project monitored three of the company's windfarms, and the implementation took a handful days. After the pilot, the company decided to go "all-in" with the platform, expanding it to all generation facilities, as well as its IT systems (including delivering security monitoring and integration with the single sign-on product used by the utility).

nfigen went with a distributed mode production implementation of Splunk to give it flexibility to grow. Although the end users were originally intended to be the OCC and IT team, it has since spread throughout the business.

"Word got out about the implementation - people saw some of the dashboards we were able to produce - and we decided to open access to people across the company," Sanchez said.

"Right now it's not only the OCC operator or the IT personnel that will see something, but, for example, the risk and compliance manager will get an alert if something goes wrong, or any of the executives, such as the CFO, will be able to log in and see what is happening with the windfarms."

Sanchez said that business continuity planning and disaster recovery capability have been boosted because even in the event of the OCC being evacuated, staff can continue to monitor the interaction between generation facilities and AEMO signals from any device.

The company has a licence that allows it to ingest up to 10GB of data a day, and it is currently averaging 6-8GB across all the monitored systems. In the medium term the plan is to increase the amount of data ingested as the company experiments with more analytical tools such as machine learning.

Sanchez said that although the control system receives aggregated windfarm data every 10 minutes, the SCADA systems themselves receive sub-second data.

"We have some potential projects where we will be able to ingest more granular data - to the minute level," Sanchez said.

Source: Computeworld Australia

 

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