By Brian Crow, P.E., ESRI Utility Team
Geographic information systems (GIS) help power companies put their data to work in ways that make their businesses more efficient and effective. Meter reading data, which is a utility’s bread and butter, is also valuable for monitoring and improving the distribution network. Leveraging the utility’s investment in GIS solutions provides an advantage by turning the meter database into a tool for assessing trends, recognizing patterns and analyzing load flows in ways that were only dreams a few years ago.
GIS significantly extends the capabilities of outage detection and notification systems, engineering analysis programs, and other enterprise applications through interfaces with automated meter reading and advanced metering infrastructure (AMR/AMI) solutions.
The Brass Tacks
Utilities are using GIS to process AMR/AMI data and quickly determine the extent of outages by plotting outage calls on a map. The user traces the primary conductor the outages are associated with and selects all meters down line of a protective device or other network device. Next, the user sends the meter list to the AMR/AMI server and “pings” the meters to check for voltage response. The information that returns, or does not return, is then plotted in the map and the true extent of the outage is easy to see. At the end of the restoration, prior to the crews leaving the area, the software user again “pings” the meters in the outage area to see if any single meter is still without power.
Engineers and analysts can use interval meter data to view system changes in voltage and load flow throughout the day. Hotspots on the system are noted and a history of these problem points can be displayed to show a trend. By adding weather and temperature data to the analysis, causal factors become evident and scenarios can be projected for assessing future impacts.
Understanding the relationship of the data to position on the distribution network aids planners with upgrading and maintaining facilities. Reasons for reoccurring problem points become apparent through spatially displayed maps. For example, an area that seems to be a hotspot based on daily max readings, in fact, may only be a hotspot during a time of day when the majority of the feeder is producing baseline readings. Low-voltage events can be easily quantified in specific areas and procedures instigated to remedy the problem. GIS server technology can allow this analysis to automatically be performed and notify interested employees when events occur that are outside of the norm.
Planning, Studies and Aggregation
To perform transformer loading studies, an analyst can aggregate meter data up to the transformer. Under-utilized transformers can represent no-load losses on the system, which cost the utility hard dollars. The analyst can use GIS to study locations where a high density of under-utilized transformers are located and best determine where to send crews to change out groups of transformers to the appropriate size. (GIS can calculate and show costs and savings associated with targeted asset management.)
Aggregating tools, such as spatial analyst software is useful for highlighting areas where transformers are at risk of being overloaded. Many urban neighborhoods are undergoing revitalization where old homes are being renovated or torn down and new larger homes are being rebuilt. During renovation or rebuild projects, the existing transformer size is not analyzed by the utility. Over time, the load increases on the transformer without anyone knowing it. Low voltage events may be a precursor to future problems. GIS is useful for aggregating load data from the meters connected to the transformer to show the true measure of operation.
Figure 1: Load density and year-over-year load growth projections
Planners can also use GIS to allocate load across an area. For example, calculating kilowatts per square yard/meter supports the analysis of load growth across a surface. Load growth visualization can be useful in determining areas that need facilities upgrades or new substations. This allocation review could also aid in targeting areas for specific management during emergency load shed events.
Blink and You’ll Miss it
Historical blink or outage data is valuable for analyzing right of way. For example, blink data can indicate a trend when viewed over time inside the GIS that might have otherwise been unnoticed. Historical playback of outage events over a time period using time-base GIS analysis can also relay an underlying pattern or a frequency that is unacceptable. GIS network maps highlight areas that may need attention prior to their regularly scheduled maintenance date. This spatially displayed data is an effective and exact tool for increasing reliability and improving restoration times during major storm events. Utilities historically maintain right of way on a strict multi-year schedule. Additional analysis using GIS and AMR/AMI data could prove that the schedule is too long, too short, or should be customized to the particular patterns of specific substations or feeders.
Figure 2: Transformer peak loading aggregation
Efficient routing of drive-by meter reads can be accommodated with GIS. New technology for calculating radio frequency propagation reduces the route miles traveled by meter readers. Visual notification of successful reads on a map will allow the driver to backtrack and capture data from misread or non-read meters prior to leaving an area. GIS offers dynamic route management and optimization. In the face of inclement weather, traffic problems or other types of delays, the smart-routing software can recalculate routes on the fly.
GIS also aids managers with the day-to-day operations of the automated meter reading network. A fixed collector system can map the relaying hops the data takes on its way to the collector. Inefficiencies in the network traffic are quickly noted on a map and investigated. Address matching and verification can be checked by cross referencing customer information address data with commercially available street network data and coordinate data from the meter location.
Business departments can also take advantage of the enterprise GIS. For example, marketing department staff may want to track habitual non-paying customers. They use GIS to create a map that shows consolidated areas with significant numbers of these habitual customers. Based on these findings, staff could create a plan to target those customers to solicit pre-paid metering or remote disconnect AMR devices.
The applications for GIS combined with AMR/AMI technology seem endless. The power that GIS brings to data analysis and visualization-tied to the quantity and quality of data from the AMR technology-significantly links these two enterprise technologies together. Utilities are realizing the more their employees use GIS, the more possibilities they are finding for effective applications that reduce costs and improve service to their customers. The evolution of GIS technologies that now include web services and GIS server technology for application development is creating a fertile bed for power companies to design solutions that are affordable and improve operations within many of their departments.