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Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 1
Meter Verification Research Approach
– Identify client issues, resources, and needs– List common meter verification problems– Examine the data to identify problems/issues
• Plot and summarize data• Compare with billing loads
– Develop data flow chart– Develop software solution
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 2
Issue, Resources, and Needs
– Issue: New purchase procedures in the wholesale power market in Virginia would soon place increased value in having accurate real time delivery point load data via SCADA.
– Resources: Near real time Load data from 225 delivery points, along with monthly hourly billing histories.
– Need: SCADA delivery point load data, which was incomplete and often inaccurate, needed to be verified, adjusted, and/or estimated.
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 3
Common Meter Verification Problems
– Missing data– Meter constant errors– Partial intervals (low usage)– Multiple combined intervals (high usage)– Data “glitches” (very high or very low usage)
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 4
Other Problems/Issues Identified in Data
Most data was good, but there were:
– Zero and negative values (faulty, but not missing)– Repeated values (default inputs, stuck meters)– No metering (not just missing values)
– Variable length intervals (20 second – 5 minute)– Limited billing histories (less than 2 years) in some
cases– Differing treatment of line and transformer losses
• SCADA and billing meters sometimes on opposite sides of transformer
– Some delivery point combined into billing meters
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 5
MVES Data Flows
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 6
Approach
– Problem: Variable Interval Lengths• Solution: Combine into 5 minute intervals.
– Problem: Meter Constant and Loss Accounting Errors• Solution: Allow user to specify delivery point scale
factors.– Problem: Missing Values or Bad Values
• Solution: Estimate through delivery point regression models of hourly billing data, with weather, day-type, and time-of day, explanatory variables.
– Problem: Combined SCADA Meters• Solution: Allocation factors available to divide
model estimates among related SCADA meters.
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 7
Approach
– Problem: Out-of-Range Values
• Solution 1: Check for data hi/lo spikes compared to adjoining intervals
• Solution 2: Allow user specified high and low limits by delivery point.
• Solution 3: Estimate where user-specified numbers, by delivery point, of standard deviation of model estimate exceeded.
– Problem: Repeated Values (including repeated zeros)
• Solution: Include a user-specified repeated value check by delivery point.
– Problem: Faulty zero and negative values
• Solution: Include user-specified checks by delivery point.
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 8
Reporting
– Quality flags allow user to identify treatment of 5 minute data.• Actual used• Missing – estimate used• Repeated too many times – estimate used• Etc.
– Historic hourly comparisons available through user interface for billing, SCADA metering, and model estimates
Electric / Gas / WaterInformation collection, analysis and application
Knowledge to Shape Your Future 9
Questions?
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