While power utilities like to claim that they employ data analytics, they really don’t. Utilities tend to have last-gen business intelligence (BI) reporting solutions that they call “analytics,” but that typically amount to not much more than reporting tools or descriptive analytics (primarily based on older database architectures running SQL), as opposed to the real-time and predictive software using complex event processing, to which the term “analytics” is now commonly understood to refer.
Utilities are today seeking to become more proactive in decision-making, adjusting their strategies based on reasonable predictive views into the future, thus allowing them to side-step problems and capitalize on the smart grid technologies that are now being deployed at scale. Predictive analytics, capable of managing intermittent loads, renewables, rapidly changing weather patterns and other grid conditions, represent the ultimate goal for smart grid capabilities.
Based on GTM Research’s latest report, The Soft Grid 2013-2020: Big Data & Utility Analytics for Smart Grid, the leading areas of concern for utilities within data analytics are:
- Achieving an enterprise-wide IT architecture where all relevant data can be shared with all other necessary departments, systems and applications.
- Ensuring that the enterprise is big-data-ready vis-a-vis the data storage and data management layers of its architecture.
Once utilities begin to overcome these foundational architecture issues, they can then begin to move into the deployment of analytics. The bulk of momentum behind utility analytics deployment is coming from:
- Consumer-based analytics
- Situational awareness gained through synchrophasor/phasor measurement unit (PMU) reporting the health of the transmission grid on an ongoing basis
- Grid optimization analytics of the distribution networks (e.g., voltage management)
A recent GTM Research survey of more than 70 global utilities, which was conducted in partnership with the SAS Institute, displays how well different stakeholders understand the value that analytics provide. Not surprisingly, the survey confirms that utilities themselves report having the most momentum for analytics in the domains of customer management and grid operations.
FIGURE: In What Areas of the Business Do Analytics Seem to Have the Most Momentum?
Source: The Soft Grid 2013-2020: Big Data & Utility Analytics for Smart Grid, SAS Institute
The following is an article based on GTM Rearch’s latest smart grid market report, The Soft Grid 2013-2020: Big Data & Utility Analytics for Smart Grid.
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