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Question

Experience with analytics models?

We are in the process of identifying the various technologies (both applications and platforms) that utilities have used to deploy analytics models. We would like to hear from other G&T utilities what their experience has been with a platform and a description of the actual use cases. As solutions are typically use case specific.

Answers

I was involved in one case that employed a combination of Oracle's OBIEE platform and the R language (RStudio) to perform various analytics ranging from management reporting and risk management to operations support activities.

Ben Ettlinger's picture
Ben Ettlinger on Aug 21, 2019 1:38 pm GMT

Thanks or your insight. We will look into this.

what kind of models are you deploying? is it for ISO biding optimization? or unit IOTs/sensor data analytics? 

Ben Ettlinger's picture
Ben Ettlinger on Aug 21, 2019 1:37 pm GMT

Thanks for your reply;

Would be interested in experience with both…….no models yet in queue just trying to survey what people have done and how they have done it

 

Real-time extreme control technology for large-scale grids may be useful for you. It contains the mathematical apparatus and algorithm for accurate calculation the combination of extreme values of control actions on a set of jointly operating one-dimensional industrial facilities and their implementation in real time. These values take into account the influence of the environment on one-dimensional objects, their mutual influence on each other and the technical condition (wear, pollution, clogging, etc.). Details - see the website  www.noologistics.ru and the book "The Noo Logistics" - www.amazon.com//dp/B07CY2XMXP.

One of the popular analytics tools we’ve seen is Opower and FirstFuel which are being used for consumer and residential energy analysis.  Typically, energy usage is compared with previous periods and neighbors and the results are communicated to enrolled customers via email and text using graphically templates for the purpose of encouraging energy consumption behaviors.

We are now starting to see customers build substantive data warehouses for the purpose of collecting the data to understand customer behavior and perform predictive analytics.  The objective is to evaluate triggers for enrollment in various programs as well as leverage communications data and internal information systems to enhance engagement.   By leveraging various data sources, including billing and outage (or leak data) provides CSR’s better tools to service customers.  The goal is to know your customers' needs in advance of a call or like interaction.

Ben Ettlinger's picture
Ben Ettlinger on Sep 5, 2019 1:43 pm GMT

Thank you the responses, They are all helpful.

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