texas smart grid consortium november 8 th 2010

Texas Smart Grid ConsortiumNovember 8th 2010

• Transition Probability• Chaos Theory attractors• Signal to Noise ratio• MultiColinearity

Remove the Complexity

Egg

Hatchling

Pond Scum

Juvenile

20%20%

80%80%

5%5%

Transition ProbabilityGolden Shiner

Child Star “Adult” Star

Super Star

Pond Scum

Rehab

Politician

10%10%

70%70%

20%20%

40%40%

40%40%

100%100%

Late Night Infomercial

SecurityGuard

20%20%

Transition Probability

Interval Read Poor Signal Quality

Pond Scum

92%92%

2%2%

6%6%

MeterSenseMeterSenseRepositoryVersioningAuditing

Aggregation

EstimateOverride

EditGuide Edits

MetersenseCertified10 rulesBased

Validation routines Service

Orders

98%98%

2%2%1%1%

99%99%

QualityReads

100%100%

Transition ProbabilityAMI Data Cleansing

NoiseNoise

Signal

Signal

Can’t Hear

Hear

Hear Clearly

RatiosRatiosSignal to Noise

Disgust

Desperat

ion

Won’t Use

Can’t Refuse

Locked InsideTaking a Snooze

RatiosRatiosPort-a-Potty

Behavior

Alcohol

Complexity of Integration

Data Qualit

y

Won’t Use

Use

DrivesInnovation

RatiosRatiosMultiCollinearity

Amount of Data

Chaos TheoryChaos TheoryAttractorsAttractors

AttractorAttractor

Chaos TheoryChaos TheoryAttractorsAttractors

Chaos TheoryChaos TheoryAttractorsAttractors

Chaos TheoryChaos TheoryAttractorsAttractors

Savings$645.00Total Cost

$3.58Daily Cost

1145Total Kwh

610On Peak

Flat Rate$534.00Total Cost

$2.96Daily Cost

1037Total Kwh

558On Peak

Time of Use Rate Savings $111.00

Time based rates comparison

Avg. Temp 25 F

Identify high line losses Loss revenue loss protection Blink momentary interruption analysis Secondary line theft Identification Balance Primary loads Phase Balancing and circuit utilization Equipment trouble shooting Transformer optimization incorporated with weather conditions Scheduled Preventative Maintenance Improve Voltage regulation and capacitor placement Customer load profiles Customer class load profiles Network location load profiles Top contributors to system peaks Water non-compliance usage Water leak detection Water main leak detection Water pressure analysis

MDM Iphone / Android structure

Reporting Structure

Application sharingEngineering Firms

ConsultantsUser Community

Web Based sharing engine

BPO Decision Automation

Wholesale Energy Purchases – Retail Member energy sales = Lost revenue

Electric Distribution Line Loss

Peak Load Contribution by Rate Class

Load Analytics

Loss 4-8%

Diagnostic System Losses

Causes; Theft, Meter issues, Voltage variance, equipment sizing placement, disturbances

Select System

Top Circuit line loss by percentage of revenue

System Line Loss Report

Total Losses for this period

Same Period last year

Loss 4-8%

Diagnostic System Losses

Secondary Power Theft

Municipal Utility Energy Demand 30 to 40 percent of the electricity is used by water utilities

Reduce Peak demand charges by 20%

Identify Lift Station

Malfunctions

Run Pumps Off Peak

Conservation Monitoring Conservation and threshold monitoring of specific energy classes allowing performance comparison and Device monitoring and Energy Resource Management

Charleston SC. expects to save $18.5 million over 15yrs through performance contracts that include saving water and energy.

Galveston TX. Through more accurate water meters expects to save $1.3 million per year

Glendale WI. Water Efficiency contributes to LEED certification