Texas Smart Grid Consortium November 8 th 2010
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Texas Smart Grid Consortium November 8 th 2010
description
Texas Smart Grid Consortium November 8 th 2010. Remove the Complexity. Transition Probability Chaos Theory attractors Signal to Noise ratio MultiColinearity. Transition Probability Golden Shiner. Hatchling. 5%. 20%. Juvenile. Egg. 80%. Pond Scum. Transition Probability. - PowerPoint PPT Presentation
Transcript of 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
