Smart grid data analytics

The deployment of smart meters and other communication nodes within the electricity grid distribution network is generating a wave of new information that many in the utility industry have referred to as a “data tsunami.”

This highly granular, real-time information on electricity consumption and grid operations can be highly useful for utilities to improve the efficiency of power generation, transmission, and distribution, but harnessing these assets requires the development of robust systems and processes for data analytics.

According to a recent report from Pike Research, these requirements are stimulating the development of a new market for smart grid data analytics, which the cleantech market intelligence firm anticipates to generate $11.3 billion in cumulative revenue during the period from 2011 to 2015.

“The challenge for utilities in maximizing the benefits from smart grid data analytics is the ability to turn the huge volume of smart grid data into value,” says senior analyst Marianne Hedin. “As utilities move to the smart grid and expand it over time with the installation of thousands and sometimes millions of smart meters, they must address the most challenging question: How will they be able to manage and take advantage of the surge of data resulting from these smart meters and other intelligent devices on the smart grid?”

Hedin adds that as soon as a utility company begins to receive data, it must be able to transform the raw data into useful information. For instance, it must be able to review the data for any changes or events in the grid that trigger alarms within outage management systems and other real-time systems.

In short, an organization can be very data rich, yet very information poor. As a result, data analytics plays a major role – from the very beginning of a smart grid deployment.

Analysis indicates that the requirements of smart grid data analytics will surpass the capabilities of traditional business intelligence systems. As a result, pioneering utilities are working to develop situational awareness systems that apply business rules to incoming data, adjusting the parameters of grid operations automatically and in real time.

Predictive analytics capabilities are also becoming increasingly important as a means of helping utilities with highly detailed tactical operations planning with the full benefit of robust historical data sets.

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