gis integrated analytics for preventive maintenance and storm response   

GIS Integrated Analytics for Preventive Maintenance and Storm Response

Presenter:John Lauletta, CEO/CTO

Sr. Member, IEEE

Preventive Maintenance Decision Process

Budget

Circuit Performance

Non Storm-Related Outages on the Electric Distribution System

Trees / Vegetation32%

Animal Contact18%

Miscellaneous19%

Equipment Failure 31%

Source: U.S. DOE

Preventive Maintenance Decision Process

Grid Design Asset Health Connectivity

Budget

Circuit Performance Optimized Maintenance

PREDICTIVE (PdM)

Vegetation Mgmt.

Predictive Maintenance (PdM)Predictive Maintenance is based upon knowing the condition of equipment in a system.

Predictive Maintenance means using technologies that tell us what will fail in the future, not what is failing right now. Predictions come from monitoring the condition of equipment as it is operating.

Visual Detection

Infrared Detection

Ultrasonic Emission Detection

RF Emission Detection

There are many benefits to conditions-based maintenance including lowering cost, improving system performance and enhancing worker safety. But, how can the condition of all the equipment on the grid be measured?

Measuring the Condition of the Grid

Here are some ways to measure equipment condition.

Based in Columbus, OH US Strategic Partners: Int’l Alliance Partners

– Australia, Mexico, Canada 2 US Patents, 7 Int’l Patents 2 million+ Poles Surveyed 3rd Party Validation

– U.S. Dept. of Energy (DOE)

– Nat’l Elec. Testing Lab (NETL)

– The Ohio State University

Exacter, Inc. Provides: Grid Condition Assessment for Improved System Resiliency and Reliability

Initial Research 2004 to 2006Advanced Research Coninues

Research FacilitiesThe Ohio State University High Voltage Laboratory

Test Fixtures

Two views of the test setup

Surge Arrester Being Studied

Lab Workstation

EXACTER® Sensor

Research Analytics

Faraday Cage

Exacter Acquisition and Analysis ProcessData Acquisition &

Discrimination Data Analysis Actionable Information

RF emissions from arcing (deteriorated) electrical components

Exacter sensor in vehicle/aircraft collects the signals and then discriminates and

GPS locates arcing, tracking and leaking electrical components

Data analyzed for severity, persistence and prevalence, enabling: • Exact locating of failing

component• Replacement prioritization

Precise GPS coordinates and relevant condition-

data transmittedto servers for final

statistical geospatial analysis Reports and GIS compatible

information provided to customer

The Need: DOE Smart Grid Project Example

http://www.smartgrid.gov/reports

Condition Assessment:Select Circuits and Design Survey

Following the selection of circuits to be included in the

assessment, Exacter Data Specialists design specific survey routes

using public access roadways. The

EXACTER Sensor is sensitive in a 200

meter radius from the vehicle.

Survey Quality ControlCondition Assessment:Monitor Survey Progress

While the survey is underway, the path of the survey vehicle, the

WHITE trace, is monitored to insure

that the circuits being assessed are

completely studied.

Accuracy of results is improved by multiple

passes of the same route over a four week

period.

Condition Assessment:Real-time Failure Signature Analysis

Whenever the EXACTER Sensor

locates a line emission that correlates to a Failure Signature a real-time study is

completed. The 986 RED markers show all

of the studies from the four-week survey

process.

Condition Assessment:EXACTER Condition Assessment Results

The 986 RED Failure Signature Events are studied by EXACTER

Servers to create this result: 25 BLUE

Maintenance Groups where a structure

includes at least one weakened component.

Analytical Process to Locate Deteriorated Equipment

• Calculates coordinates of a circle which is centered about a point on the globe

• Difficult cone-sphere intersection problem

• Adopted a method described in The Journal of Applied Meteorology by I. Ruff in 1971

Internal Algorithms: Geographic Circle Calculation

Transmission Equipment DeteriorationAerial Surveys

Prioritized Maintenance Action:Select Equipment to Replace

Specific component(s) that are arcing, leaking

or tracking on those structures that have been prioritized for

repair are identified.

Photographs, Maps, Reports, and GIS Files

are provided.

GIS.SHP File

Example: Project Design• Projects are designed with utility data to create an optimized price/benefit

result• Utilities:

– Set Goals– Perform Maintenance– Measure Results

Vegetation, 32%

Animals and Other, 37%

Selected Prior-ity Feeders to

Assess and Improve Af -

fecting 20% of Out-

ages

Deferred, Less Critical , Low SAIDI Impact Feeders 11% Outage Causes

PredictiveBased

Maintenance

30%

26%

17%

9%8%

5%

2% 2%1% 0%0.0%

5.0%

10.0%

15.0%

20.0%

25.0%

30.0%

35.0%

-

5,000,000.00

10,000,000.00

15,000,000.00

20,000,000.00

25,000,000.00

1 11 21 31 41 51 61 71 81 91 101 111 121 131 141 151 161 171 181 191 201 211 221 231 241 251

Eastern DivisionCMI Impact Analysis

Circuit CMI Contribution 5,950 OVHD Miles

Example: Prioritized Worst Performing Circuit (WPC) Improvement Program

73% of Total CMI – 1,904 miles (32%)

CMI Result ofCurrent Programs

Sum of All Customer Interruption DurationsTotal Number of Customers ServedSAIDI

71.1861.33 63.92

23.38

Aggregate Customer Experience

IEEE 1366

Total # of Customer InterruptionsTotal Number of Customers ServedSAIFI

1.52 1.48 1.53

1.03

Aggregate Customer Experience

Sum of All Customer Interruptions Total Number of Customer Interruptions CAIDI

Aggregate Customer Experience

46.73 41.32 41.90

22.78

Relatively No Change in the Customer Experience

Non Storm-Related Outages on the Electric Distribution System

Trees / Vegetation32%

Animal Contact18%

Miscellaneous19%

Equipment Failure 31%

Source: U.S. DOE

Flat Response = Challenges & Opportunities

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I

Flat Response = Challenges & Opportunities

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I

Target Performance

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I

Top Decile20 Years of Design Excellence

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I

SAIDI FocusO&M – Workforce Deployment

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I

SAIFI FocusCapital Intensive Programs

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I

Typical Strategies

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I Tree Trimming

Automat ion

60% – 70%Out of ROW

Replace Deteriorated Equipment

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

I Tree Trimming

Automat ion

Predictive Equipment Maintenance

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 50

50

100

150

200

250

300

350

400

450

500

SAIFI

CAID

IWhat is The Strategy to Improve?

How Good Is Good Enough?

• SAIDI (CMI)

• SAIFI (Number of outages)

• CAIDI (CMI)

• CEMI (Number of outages)

• Targeted Performance: 1st Quartile or Decile

• Stay Ahead of the Bear

What is Urgent and Important?

Informed Maintenance Decisions

Circuit A Circuit B Circuit C Circuit D0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

CMICMI (

100,

000)

Optimized Selection

Circuit A Circuit B Circuit C Circuit D0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

CMICMI / Mile

CMI (

100,

000)

Circuit Connectivity

1,000 Customers

CMI1 = CMI2

120 Customers

Circuit 1

Circuit 2

Circuit Physical Design

9 miles of OH 1 mile of UG

9 miles of UG1 mile of OH

CMI1 = CMI2

Circuit 1

Circuit 2

Circuit Critical Connectivity

100 Customers

100 Customers

CMI1 = CMI2

Circuit 1

Circuit 2

Grid Operation Importance

Smart Grid Control element

Residential Distribution

CMI1 = CMI2

Circuit 1

Circuit 2

CMI Reduction Project

Preventive Maintenance Decision Process

Budget

Circuit Performance

Preventive Maintenance

Customer Complaints

Improved Measurements Effective Results

00.5

11.5

22.5

33.5

44.5

Cost per Outcome

Cost of Program

Desi

red

Out

com

e

0

1

2

3

4

5

Cost per Outcome

Cost of Program

Desi

red

Out

com

e

Lift

OpportunityTo Lower

O&M Expense

Preventive Maintenance Decision Process

Grid Design Asset Health Critical Load Connectivity

Budget

Circuit Performance Optimized Maintenance

PREDICTIVE (PdM)

Optimized Maintenance

Deteriorated Equipment Impact on Grid Resiliency

1. THE GRID IS OLD—AND IT'S ONLY MAKING MATTERS WORSEAccording to the DOE report: "70% of the grid’s transmission lines and power transformers are now over 25 years old and the average age of power plants is over 30 years."As a result, "the age of the grid’s components has contributed to an increased incidence of weather-related power outages.“. . . Utility Dive

http://nca2009.globalchange.gov/significant-weather-related-us-electric-grid-disturbances

Storm Influence on Transmission

Storm Impact on Reliability

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 -

200,000

400,000

600,000

800,000

1,000,000

1,200,000

Correlation: OH EQ CMI against MEDs

System MEDs Total OH EQ CMI

Cus

tom

er M

inut

es o

f Int

erru

ptio

n (C

MI)

Predictive Analytics Effective Conditions-based Maintenance

• Long Term Improvement in Reliability– Measurable– Documented– Repeatable

• Additional Value– GIS Data– OMS Systems– Software

• Complete Solution– Vegetation– Asset Data Collection– Condition Assessment– Predictive Maintenance

CONFIDENTIAL

Questions?

JLauletta@exacterinc.com

@EXACTERINC