Transformer Loading, Driving Enterprise Decisions with ArcGIS Online
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In the past MTEMC has oversized their transformers across the utility due to a lack of consumption data in GIS. MTEMC joined SSP Innovations to auto-load SAP consumption data, perform aggregation for peak usage, and to visualize the data in ArcGIS Online via a thematic map. Field troubleshooters use Collector for ArcGIS to view the load profile for any transformer showing peak usage against the transformer size. This results in cost savings and has generated drivers for many other uses of the data and of ArcGIS Online.
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Transformer Loading, Driving Enterprise Decisions with ArcGIS Online
- 1. Transformer Loading Driving Enterprise Decisions with ArcGIS Online Esri User Conference 2015
- 2. Agenda Introductions Business Drivers Business Challenges Solution Overview Establish Relationships Data Aggregation Reporting & Visualization Demo Business Benefits
- 3. Introductions Nathaniel Everett | Middle Tennessee EMC • GIS Technical Lead • Covers ArcGIS / ArcFM / Designer • Information Services Department Skye Perry | SSP Innovations • Principal Consultant • Esri & Schneider Electric Technical Architect • Utility-Focused ArcGIS Online Specialty Partner • Began work with MTEMC in 2013
- 4. Business Drivers Transformer Failures Occur Regularly Troubleshooter assesses transformer in the field Transformers are replaced Often up-sized to handle an overloaded scenario (25 kVA to 37.5 kVA) Data is not available to see consumption / loading information Result Inefficiencies in Network Cost Impact
- 5. Business Drivers Engineering Asked For Help Desire to utilize consumption data to determine transformer sizing Provided an Example Report that would help Provided all Engineering Calculations
- 6. Business Challenges No DB relationship between Service Location & Transformer Network Traceable Relationship in GIS SAP CIS Consumption Data Not Available in GIS Current Monthly Reads, Use with AMI in the Future How Best to Expose Reports & Map to users
- 7. Current Data Model April 24, 2014 Page 1 Service Point Service Location Device Location Meter Service Point Service Location Device Location Meter Service Point Service Location Device Location Meter Transformer Standard 3 House Scenario Live Example Data Live Example Data Live Example Data Single House House Service Location Device Location Meter Solar Panels (GenPart) Service Location Device Location Meter Barn SAP Data Table
- 8. The Solution Engaged with SSP Innovations to Design and Develop SSP is the in house Esri / Schneider Electric support vendor SSP & MTEMC Broke the Effort into Three Phases: 1. Establish Maintainable Relationships from Xfr to Service 2. CIS Consumption Load & Aggregation 3. Reporting & Visualization
- 9. Phase 1 – Xfr to Service Schema changes on Service Point Track Xfr Company Number By Phase Initial script to establish relationships Trace via Electric Network SQL Script to Not Impact Versioning Performance AutoUpdaters to maintain relationship
- 10. Phase 1 – Byproduct Data QAQC of Energized Phases & Connectivity NoXfrFnd – Indicates that no energized power is being fed from a valid transformer bank MultSrcXfr – Indicates that multiple transformer banks were found upstream of the service point
- 11. Phase 2 – CIS Data Usage Chose SSP Nightly Batch Suite for Fast Batch Apps Series of three integration applications 1. Load the raw CIS consumption data into GIS Applied Engineering Calculations 2. Aggregate max consumption to Transformer Unit (by phase) By Month & Season 3. Create Summary Feature Points for Each Xfr Asset
- 12. Phase 2 – CIS Aggregation Run on weekends to exclude production impact
- 13. Phase 2 – CIS Aggregation Single Phase Aggregation
- 14. Phase 2 – CIS Aggregation Three Phase Aggregation
- 15. Phase 3 – Reporting Utilized SQL Server Reporting Services Out of the Box Web Reports Provided Query Screen to Engineers:
- 16. Phase 3 – Reporting Three Level Report – Level 1 Shows Transformer Unit
- 17. Phase 3 – Reporting Three Level Report – Level 2 Shows Adjusted Meter Consumption
- 18. Phase 3 – Reporting Three Level Report – Level 3 Shows Raw Meter Data from SAP
- 19. Phase 3 – Visualization Utilized ArcGIS Online – Created Thematic Map Showing Xfr Load vs. Capacity
- 20. Phase 3 – Visualization Exposed via ArcGIS Online as a WebMap Troubleshooter uses their phone or tablet when they arrive on scene Zoom via GPS in the device View transformer loading data by color Click any transformer to view details Live Demo…
- 21. Transformer showing under-loaded scenario: Phase 3 – Visualization
- 22. Transformer showing overloaded scenario: Phase 3 – Visualization
- 23. Business Benefits Operations Empowered Engineers & Troubleshooters with New Data Provided Real Time Data Access in field from ANY Device Allows for educated decision making Engineering Can Review Existing Xfr Installs Against Usage May reallocate network Net Result is Cost Savings, Better Efficiency, & System Awareness
- 24. Business Benefits IT / GIS Demonstrated capabilities of ArcGIS Online Have fully functioning DMZ / internal ArcGIS Server architecture Ready for additional data publishing, editing, and collection via ArcGIS Online Includes Active Directory Authentication and SSL (https) Will Allow for Other Patterns to be Implemented Quickly & Easily
- 25. Questions? Skye Perry Principal Consultant SSP Innovations skye.perry@sspinnovations.com Nathaniel Everett GIS Technical Lead Middle Tennessee EMC nathaniel.everett@mtemc.com
- 26. Transformer Loading Driving Enterprise Decisions with ArcGIS Online Esri User Conference 2015
Editor's Notes
- Abstract: In the past MTEMC has oversized their xfrs across the utility due to a lack of consumption data in GIS. MTEMC joined SSP Innovations to auto-load SAP consumption data, perform aggregation for peak usage, and to visualize the data in ArcGIS Online via a thematic map. Field troubleshooters use Collector for ArcGIS to view the load profile for any xfr showing peak usage against the xfr size. This results in cost savings and has generated drivers for many other uses of the data and of ArcGIS Online.
- Nathaniel to cover the agenda at a high level
- Nathaniel introduces himself and Skye introduces himself
- Nathaniel to cover the business process around replacing transformers and the issues that arise from over sizing the transformers
- Nathaniel describe the pattern of how the project emerged including initial meetings with engineers to come up with the idea.
- Nathaniel to focus in on the business challenges we identified at the beginning of the project. Most folks in the room should understand these challenges. The AMI aspect is worth mentioning since in the future we want to make this available using more real time data.
- Nathaniel, keep this one brief but touch on the 4 level join that we use to get from the service location to the meter in CIS. BUT harp on the fact that there was no relationship from the meter to the xfr – had to come from the network.
- Nathaniel to talk about engaging SSP, Skye can take over to talk about the solution if that works… break it into 3 phases
- Skye will cover the schema changes by phase, how we created AutoUpdaters that ran real time and generated a script.
- Skye will explain how a by product of processing the entire system was capturing some QAQC cases that engineering could then go back and fix.
- Skye will talk about the NBS usage and what each of the three apps performs.
- Skye, Nathaniel jump in here, can talk about how the CIS data was joined through the model all the way up to the xfr based on the new network established join.
- Skye show the data in action and how it was aggregated
- Skye show the data in action and how it was aggregated
- Skye talk about SQL Server and why the reports were created… query input driven by engineering.
- Skye explain the report (quick slide)
- Skye explain the report (quick slide)
- Skye explain the report (quick slide)
- Skye talk about visualization via Esri mapping… mention split of single feature into phased (2/3) features in this layer.
- Skye talk about how ArcGIS Online was used to expose the data… turn it over to Nathaniel for a live demo. CAN SKIP THE NEXT COUPLE SLIDES IF NATHANIEL COVERS IN THE DEMO – LEAVE IN THE PRESENTATION FOR PUBLISHING
- Mostly for publishing since NE will do the demo
- Mostly for publishing since NE will do the demo
- Nathaniel keep going to talk about the business benefits
- Nathaniel keep going to talk about the business benefits Lend toward what MTEMC can do in the future based on the success of this project…
- Take questions and wrap it up.
- Abstract: Middle Tennessee EMC has not historically had their customer consumption data available in GIS to drive business decisions. This resulted in a general theme of over sizing their transformer replacements across the service territory. MTEMC recently joined forces with SSP Innovations on a project to automatically load SAP customer usage data into GIS, perform regular aggregation to determine peak usage for both winters and summers, and to visualize the resulting data points in GIS via a color-coded heat map. This feature data was then exposed to the field via an enterprise implementation of ArcGIS Online. Troubleshooters can now use Collector for ArcGIS to locate themselves on the map and to view the most recent load profile for any transformer showing a comparison of peak usage by phase against the transformer size. This directly results in cost savings via better sizing decisions and has generated drivers for many other uses of the visualized load data and of ArcGIS Online for enterprise enablement. Join us to review the current project, the future plans, and to see a demo of the solution! Final (500 characters): In the past MTEMC has oversized their xfrs across the utility due to a lack of consumption data in GIS. MTEMC joined SSP Innovations to auto-load SAP consumption data, perform aggregation for peak usage, and to visualize the data in ArcGIS Online via a thematic map. Field troubleshooters use Collector for ArcGIS to view the load profile for any xfr showing peak usage against the xfr size. This results in cost savings and has generated drivers for many other uses of the data and of ArcGIS Online.