Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Wednesday 8b.1-kincaid

10 views

Published on

Trees and Utilities Conference 2017

Published in: Environment
  • Be the first to comment

  • Be the first to like this

Wednesday 8b.1-kincaid

  1. 1. Eversource Energy: Utilizing LiDAR and High Resolution Imagery to Assess Span Level Vegetation Risk on Distribution Networks
  2. 2. Managing 38,000 Distribution Miles 2 Tasked to maintain more than 9,000 miles in annual road side program• 16,017 System Miles • 3,600 Cycle SMT miles • 500 Cycle ETT miles • 2,927 Net ROW Acres • 490 ROW Miles • 11,250 System Miles • 2,700 Cycle SMT Miles • 75 Cycle ETT Miles • 2,079 Net ROW Acres • 237 ROW Miles MA • 11,100 System Miles • 2,800 Cycle SMT Miles • 150 ETT Miles • 6,723 Net ROW Acres • 633 ROW Miles NHCT
  3. 3. Eversource - Continuous Reliability Improvement 3 Continuous improvement for SAIFI and CAIDI  Enhanced risk tree removals  Enhanced tree trimming specifications 3,600 Program Miles 15,000 Removal Target 2,800 Program Miles 25,000 Removal Target 2,800 Program Miles 20,000 Removal Target
  4. 4. Enhanced Mid Cycle Pruning Program 4  Current focus is on poor performing circuits after trends develop  Because of tree density, Eversource manages to specifications as opposed to prescribing how each tree is maintained  MA Tree Wardens are very powerful and have great latitude to impact whether spec clearances are actually achieved  LiDAR surveying empowers a more proactive approach to intercede before a trend of interruptions develop
  5. 5. Eversource Vegetation Specification  Traditional Human Patrols: • Subjective analysis • Adherence to the spec is subject to tree warden approval and property owners • Time consuming • Accuracy of the observations are subject to human error 5
  6. 6. 6 Distribution LiDAR and Imagery Collection
  7. 7. 2017 Mid-Cycle Vegetation Risk Assessment  1,075.21 miles of MA Distribution Project Objectives and Deliverables: • Identify and report vegetation risk • Improve the accuracy of vegetation risk identification • Improve the speed of data collection • Create an archive of LiDAR and imagery to benefit the enterprise • Reduce field visits 7
  8. 8.  41,712 Distribution Poles • 10 area work centers / 93 feeders Waltham, Somerville, Southboro-N, Plymouth, Cape/Vinyard, New Bedford, Southboro-S, Walpole, Mass Ave, Hadley • 2 man crews, on rotation • 51 total days (May 27 – July 16) 36 working day duration 15 weather days • Effective work planning and ground truthing Data Acquisition 8
  9. 9. Evolving Analytics: Mapping The Eversource Spec  Technology Driven Approach • Objective analysis • Consistent • Rapid data collection • Electronic audit trails • Additional analysis can be performed 9
  10. 10. Bringing It All Together 10
  11. 11. 2017 Mid Cycle Vegetation Risk Assessment Summary and Results • 18,642 Spans Assessed • 15,484 had a Spec Encroachment  Overhang  Side encroachment  Under growth • 1,261 Spans - Overhang Danger • 3,374 Spans - Radial Clearance • 3,441 Spans - Side Clearance 11
  12. 12. Querying Vegetation Risk Data 12
  13. 13. LIDAR Visualization 13
  14. 14. O&M CONTROL Areas of highest risk are clearly defined and analytics support prioritization. COMPLIANCE Clearly identified areas that deviate from the Eversource trim specification RELIABILITY Geospatially and objectively identify cycle busters that may impact reliability. SAFETY This assessment was completed with 2 resources. No utility truck rolls, no parking on side streets, no poke sticks Benefits Achieved
  15. 15. UTILITI ES Enterprise Value Distribution Data Analytics and Uses GIS and ADMS Vegetation Management Infrared Inspection Asset Inspection and Inventory Telecom Attachments and Joint Use Engineering and Pole Loading
  16. 16. Next Steps 16  Utilize Data for Program Optimization  Maximize the value of the data across Eversource  Additional Use Cases: Asset Inspections, GIS enhancements, etc.  Develop Total Risk Model  Vegetation Risk Values, Customers Affected, Poor Performing Circuits, Location of Hazard Trees, Condition of the Tree  Engage system arborists to develop deep trust in the data and analytics
  17. 17. QUESTIONS? 17

×