Utility Project Profile Database

GIS Improvements – Meter, Transformer, and Phase Mapping at Duke Energy

  

ANALYTICS AREAS

 

  1. Which of the following analytics areas apply to your project (see definitions at end of document)? Place an “X” in the appropriate boxes.

 

 

Implementation underway

 

 

Project completed

Future

 

Meter data analytics

___X___

 

 

_______

_______

Credit and collections

_______

 

 

_______

_______

Call center optimization

_______

 

 

_______

_______

Fraud detection

_______

 

 

_______

___X___

Campaign management

_______

 

 

_______

_______

Customer segmentation

___X___

 

 

_______

_______

Pricing optimization

_______

 

 

_______

_______

Demand response programs

_______

 

 

_______

___X___

Energy efficiency programs

_______

 

 

_______

___X___

Distributed generation management programs, including electric vehicles

_______

 

 

_______

_______

Transformer management

__X____

 

 

_______

_______

Substation equipment management

_______

 

 

_______

_______

Overall transmission & distribution management

_______

 

 

_______

_______

Outage management

__X____

 

 

_______

_______

System modeling

_______

 

 

_______

_______

Power quality optimization

_______

 

 

_______

_______

Advanced distribution management

_______

 

 

_______

_______

Analytics for real-time network operations

_______

 

 

_______

_______

 

Other: 

 

 

PROJECT OVERVIEW

 

  1. In two or three sentences or a short paragraph, please describe this project (include business drivers, how project aligns with utility’s corporate strategy, project goals, results achieved/desired outcomes).

Leverage both SCADA data and AMI data to determine and find value for the company. GIS information, specifically meter transformer mapping and meter to phase mapping can be corrupted over time. Having correct GIS information is key for understanding, improving and analyzing assets. It is not cost effective to send field crews to verify all maps. The goal of the project is to find a way to use AMI voltage and PI data to correct GIS.

BUSINESS VALUE

 

  1. Describe actual and/or anticipated QUALITATIVE (e.g. better customer service) and QUANTITATIVE (e.g. ROI, cost savings, revenue increases) benefits of this project.
    • Note: Any and all quantification of benefits helpful including estimates, ranges, percentage increases or decreases in costs, resources, etc.

 

Improved customer service and allow for improved customer communications around outages. Upon field verification they have found 2%-25% inaccuracy per circuit. The code predicted 23% of transformers have incorrect meter transformer mapping. Field verification showed promising results; 100% correct phase mapping and 95% correct meter to transformer mapping. Cost of initial field verification will be higher and will dwindle down as confidence interval improves.

BUSINESS PROCESS IMPACTS

 

  1. List the key business processes impacted (or expected to be impacted) and describe the nature of those impacts.

 

Business processes impacted: Outage management, Load balancing, transformer overload, customer notification, and theft detection.

 

TECHNOLOGY

 

  1. Identify the PRIMARY TECHNOLOGY COMPONENTS associated with this project including the technologies used (or expected to be used) for: 1) data collection/integration 2) data analysis 3) data presentation and 4) data storage.
    • Notes: Identify the solution providers and products by name if possible

 

AMI Meter, Hadoop, Spark, Python, PowerBI (current), Angular (future)

 

 

  1. Identify the PRIMARY DATA INPUTS/ELEMENTS utilized and their sources.


AMI data (change in voltage, 30 min interval usage

PEOPLE

 

  1. Identify the following individuals by job title (as applicable):

 

  • Business-side Project Leader: AMI Analytics Project Lead and Project Manager___

 

  • Technology-side Project Leader: Sr Data Scientists (3)___

 

  • Executive Sponsor: Analytics Project Lead_____

 

 

  1. Identify and describe the role of external providers (e.g. strategy, consultant, design, development, implementation, ongoing operations).

 

Hortonworks provides expertise on distributed processing and provide guidance on Spark. Two consultants from Hortonworks are onsite and actively involved.

 

  1. Describe the investments required to implement and provide ongoing support for this initiative.

 

  • Internal resources (identify type of internal resources, e.g. job titles and quantities of each (e.g. # of full time/# of part time, total FTEs):

 

  • 2 Data Scientist, 1 Data Architect, 1 GIS Support, 1 Field Analyst, and 2 Hadoop experts

 

  • Technology investments (estimate/provide ranges for one time and recurring costs if possible or indicate that existing technologies were leveraged):

 

  • No additional technology was acquired for this project. The AMI meters and Hadoop are existing technologies that play a critical role in this project.

 


BEST PRACTICIES/LESSONS LEARNED

 

  1. What advice would you share with those either planning or implementing a similar initiative (e.g. best practices, lessons learned, what to do, what not to do)?

 

  • Take risks, be patient, and be systematic.
  • “We will learn from failing” – the fail fast mentality was key
  • Directed to “Go in and try to discover” while being guided by principles.

 

 


 

CONTACT INFORMATION:

Name:

Martin Cardenas

Title:

Lead Data Science Consultant

Company name:

Duke Energy

Email:

Martin.Cardenas@duke-energy.com

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