Data Analytics & Application in the Energy Sector

Attended a lecture this evening at Engineers Ireland by Jennifer Jennings, a data scientist at ESB (Irelands main Electric utility). She dropped some good understandings on us regarding ESB’s use of data analytics/data science/machine learning to solve problems of interest to energy utilities. Particularly of interest, was their approach to detection of partial discharges for power line fault detection. In

Data Analytics Process

Attended a lecture this evening at Engineers Ireland by Jennifer Jennings, a data scientist at ESB (Irelands main Electric utility). She dropped some good understandings on us regarding ESB’s use of data analytics/data science/machine learning to solve problems of interest to energy utilities. Particularly of interest, was their approach to detection of partial discharges for power line fault detection.

In ResourceKraft, we find that with data analytics, identifying the question that needs answering is often more difficult than actually answering the question. Jennifer did not attempt to soft-pedal this challenge. She emphasised the use of the CRISP DM standard to iterate towards the right question to the right answer. “DM” stands for “Data Mining”, which was a big term back in ’96 when this standard was defined. Regardless, the iterative loop inherent in here applies just as well to our brave new worlds of machine learning and data analytics.

ResourceKraft has many years of experience designing and building custom solutions to ensure that your energy analytics solution works for your business. Feel free to contact us on hello@resourcekraft.com to discuss further.

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