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EPRI Grid Analytics and Power Quality Conference and Exhibition

Date: June, 20-22, 2017

Location: Sacramento, CA

Topic

The Electric Power Research Institute (EPRI) and the Sacramento Municipal Utility District (SMUD) invite you to the 2017 EPRI Grid Analytics and Power Quality Conference and Exhibition. The theme for this year’s conference is “Getting Actionable Intelligence from Big Data”. As an integrated, more renewable based, communication driven, dynamic power system emerges it’s imperative that utilities are prepared at all levels for this transformation. The conference will provide a forum for electric power end users, distribution electric service providers, data managers and power quality (PQ) professionals, to gather, share experiences, and learn from one another in a collaborative environment. The week of events will also include pre-conference tutorials, on Big Data related topics The areas of focus for the 2017 conference will be Big Data and Grid Analytics focused on any of the following distribution or PQ topics: • Distribution Grid Modernization for Operations, Planning and Asset Management • Integration of Distributed Energy Resources • Information & Communication Technologies • Distribution System Resiliency Analytics • Innovative Utilization of Data from Existing and New Sensors Technologies • Power Quality Topics for Transmission, Distribution or End Use

Sheraton Grand Hotel Sacramento


1230 J Street

Sacramento, California 95814

Global Lead, Utilities and Industrial IoT 


OSI Consulting, Inc.

OSI Speaker

Advanced Data Architectures for Outage Analytics


With the proliferation of intelligent devices such as smart meters, grid sensors, distributed generation and other connected devices; utilities can now leverage massive amounts of data coming from many different sources. However, they’re challenged with extracting meaningful intelligence from the tremendous volumes of raw data being generated every day.

Solving this challenge requires a new way of thinking and traditional data architectures and analytics techniques must be reimagined to support the rapid proliferation of data from an exponentially expanding set of data types. New Industrial data and analytics platforms from GE Digital and Microsoft have been designed to rapidly ingest and integrate data to provide a semantic understanding of information across disparate systems. Deeper analytics techniques can then be applied intelligently through analysis methods and visualizations.

In this discussion, we will present; (1) The challenges associated with industrial data integration, (2) Advanced architectures required to quickly analyze distributed data, (3) Provide examples of outage analysis techniques and outcomes based on industrial data platforms from GE Digital and Microsoft.


Scott Harden