Saturday, August 21, 2010

Post # 37 - GIS and Smart Grid

A “geographic information system,” or GIS, integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. Many information technology experts believe that successful utility integration of GIS technology is essential to smart grid development.

But according to a new study by Ersi, a software development and services company providing GIS software, there currently is a wide range of GIS capability among utilities, with the largest often being the least smart grid ready. Ersi finds that data accuracy is spotty and often either incomplete or not GPS accurate. Interestingly, according to Ersi, the larger a utility’s size, the less likely it is to be “smart grid ready.”

Although Ersi obviously is not a disinterested bystander, its study contains interesting data about utility integration of GIS technology. In the last quarter of 2009, Ersi conducted what it calls a “smart-grid-readiness survey” of electric utilities around the world (though primarily located in the United States). About 60 percent of the 226 responding companies had fewer than 100,000 customers (what Ersi terms “mid-size”), 30 percent had from 100,000 to 2 million customers (“large”), and the remaining 10 percent had more than 2 million customers. (“very large”). Over 70 percent of the respondents view GIS technology as strategic to the smart grid; the remaining 29 percent believe GIS plays a significant role.

But with respect to accuracy and integration, only one-third of the responding utilities say they update their GIS data within ten working days of completion. Overall, the study finds that utilities report a lag time of up to 90 days to move data from the field into the GIS. Moreover, the study found a strong inverse relation between company size and the time it takes before completed work is reflected in the GIS data base. The larger the company, the longer it takes -- although the difference is considerably greater between the “very large” and “large” utilities than between the “large” and “mid-size” utilities.

Twenty-five percent reported that there is information older than six months that is not reflected in their GIS. Perhaps most significantly, only 15 percent report “high confidence” – defined as an error rate of less than 2 percent – in their GIS data. And, as noted above, Ersi concludes that the larger the utility the less likely it was to be among the most “smart grid ready” companies.

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