The General Availability of Azure Machine Learning and Smart Grid Management


We have written about of our Azure Machine Learning (ML) services many times before and up until today it was in public preview. Today we are delighted to announce that we have released Azure ML for general availability. You can read all about the announcement here.

With the announcement we have highlighted a number of customers that are using Azure ML.  In the announcement we cite an exampleimage in Utilities with our partner eSmart Systems of Norway who is pioneering smart grid management using our tools. A traditional smart grid includes multiple data silos, including SCADA networks, building automation systems and substation meters. In this environment, it can be difficult to forecast consumption and prevent bottlenecks or outages. For a utility company, upgrading its entire infrastructure would be costly. Even when upgrades are made, e.g. new smart sensors or meters, data gets collected but is not readily accessible. eSmart Systems uses the Azure cloud platform to integrate and analyze usage data and create forecasts. Azure Machine Learning is the "brains" of the solution, running the data models for predictive analytics. The analytics are used to predict capacity problems and automatically control load in individual buildings.

Sigurd Setelev, Chief Strategy Officer of eSmart Systems, says:

“For what we’re doing at eSmart, we needed a cloud solution because of the sheer volume of data being collected; if we were to do it on premise we’d need a lot of storage. We also do a lot of data crunching using Hadoop, which also requires a lot of infrastructure. What we really like about Azure Machine Learning, and Azure in general, is that everything we do is through services available in Azure and we don’t need to monitor virtual machines.”

This is just one of the broad range of ML scenarios that we are seeing in Power & Utilities. Others include:

  • Utilities with large amounts of smart meter data, interested in understanding customer energy usage, propose tariff plans, assess program effectiveness
  • The need to identify customers that will have concerns about their bills and contact the Utility call center before they actually receive their bills
  • Wind farm company with sensor data streaming from turbines, wants to predict failures in near-real time by applying learning from historical data
  • Collection of sensor data and doing financial, risk, and condition based maintenance using causality and predictive analytics
  • Utilities with multitude of disparate systems interested in creating single point of truth and enabling self-service BI & improved reporting
  • Smart Meter roll-out and needs to prove the benefit to the regulator

I often tell partners and customers that the opportunities are only limited by your imagination and with Microsoft ML we have made it easy to turn your imagination into reality!

While I have focused on ML in this Blog, this was not the only Azure announcement that we issued today. We announced several new and enhanced Microsoft cloud data services including: a preview of Azure HDInsight running on Linux, the general availability of Storm on HDInsight, and the availability of Informatica technology on Azure. You can all about these here.

May the Cloud be with You! – Jon C. Arnold


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