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Overview
Based on work previously carried out October 2006
Examines how consumers gas bills are estimated
Examines how the accuracy of all of the inputs into the calculation affects the overall accuracy of the gas bill
Poses questions about:
• fairness
• the appropriate level of acuracy
Accuracy of CV determination systems - Page 2
Introductory concepts: error, uncertainty, bias...
Uncertainty
• "Parameter that characterises the spread of values that could reasonably be attributed to the measurand."
• Range and an associated probability
Error
• Measured result minus a “true” value
Bias
• Mean value of a distribution of errors.
• Associated with an agreed set of conditions (each showing an error)
Accuracy of CV determination systems - Page 3
The Charging Area CV
Charging area CV is calculated as the Flow weighted average CV
Subject to a 1 MJ/m3 cap
Uncertainty in FWACV arises from:
• Uncertainty in measurement of CVs and flows
• Variation in the CV of the sources of gas
Accuracy of CV determination systems - Page 4
The Charging Area CV
Consumer A receives high CV gas “all the time”
• For him the FWACV is biased
Consumer B receives low CV gas “all the time”
• For him the FWACV is biased
FWACV delivers zero bias in charging area energy
CV cap limits the exposure of consumer B
Accuracy of CV determination systems - Page 5
A
B
The Consumers’ Energy Bill
Energy = quantity of gas x representative calorific value
Quantity is expressed as volume at reference conditions
• Consumer:
• actual metered volume x conversion factor
• conversion factor is provided in the Regulations
Representative calorific value represents the CV of the gas seen by the consumer
• Consumer:
• average of charging area CVs over the billing period
• determined through use of approved CVDDs
Accuracy of CV determination systems - Page 6
Sources of Error, bias and Uncertainty
FWACV
• Daily volumes at Network Offtakes
• Error, bias in daily volumes
• CVs at Network Offtakes
• Error, bias in CVs
Actual gas quality received
• Variation in gas quality
• “Location” uncertainty
Quantity of gas
• Error, bias in domestic meter
• Error, bias in conversion factor
Accuracy of CV determination systems - Page 7
A
B
Estimating error, bias and uncertainty
Principles suggested by Marcogaz Energy Measurement Working Group
• Provides guidance on implementation of OIML Recommendation “Gas Metering”
• Estimates errors and bias in each component of measurement, which are then combined arithmetically to provide and overall bias in energy measurement
• Estimates uncertainties in bias for each source, which are then combined in quadrature to provide an overall uncertainty in bias.
• Sources: measurement instrumentation; fixed factors; representative CV calculation
Accuracy of CV determination systems - Page 8
Estimating error, bias and uncertainty
Domestic meter bias and uncertainty
Fixed factor bias and uncertainty
• Compare with average and variance in pressure, temperature, altitude
Matrix of FWACV scenarios:
• Uncertainty in CV determination at NTS Offtakes
• 0.125%, 0.25%, 0.5% (i.e. 0.05, 0.10, 0.20 MJ/m3)
• Uncertainty in NTS offtake metering
• 1%, 4%
Accuracy of CV determination systems - Page 9
Results: Consumers’ energy bills
Current situation
• MPE in CV determination is 0.25%
• MPE in Offtake volume metering is 1%
Overall bias is close to zero (-0.081%), because:
• Daily CVs and volumes, and hence FWACV, assumed to be unbiased
• Small bias arises from assumptions in fixed factor in the Regulations
Expanded uncertainty in bias is 5.8%
• 61% of variance arises from temperature variation
• 25% of variance arises from CV variation (i.e. 1 MJ/m3 cap)
• 9% of variance arises from domestic meter
• 0.06% of variance arises from FWACV uncertainty
Accuracy of CV determination systems - Page 10
Results: Consumers’ energy bills
Current situation
• MPE in CV determination is 0.25% [0.5%]
• MPE in Offtake volume metering is 1%
Overall bias is close to zero (-0.081%), because:
• Daily CVs and volumes, and hence FWACV, assumed to be unbiased
• Small bias arises from assumptions in fixed factor in the Regulations
Expanded uncertainty in bias is 5.817% [5.822%]
• 61% of variance arises from temperature variation
• 25% of variance arises from CV variation (i.e. 1 MJ/m3 cap)
• 9% of variance arises from domestic meter
• 0.06% of variance arises from FWACV uncertainty [0.22%]
Accuracy of CV determination systems - Page 11
Results: Consumers’ energy bills (impact of biomethane)
Current situation
• MPE in CV determination is 0.25% [biomethane 10 MJ/m3, or 25%]
• MPE in Offtake volume metering is 1% [biomethane 3%]
Overall bias is close to zero (-0.081%), because:
• Daily CVs and volumes, and hence FWACV, assumed to be unbiased
• Small bias arises from assumptions in fixed factor in the Regulations
Expanded uncertainty in bias is 5.817% [5.818%]
• 61% of variance arises from temperature variation
• 25% of variance arises from CV variation (i.e. 1 MJ/m3 cap)
• 9% of variance arises from domestic meter
• 0.06% of variance arises from FWACV uncertainty [0.08%]
Accuracy of CV determination systems - Page 12
Accuracy of CV determination systems - Page 13
Points for discussion
Overall, consumer billing is largely unbiased, provided assumptions about CV measurement and domestic and offtake metering are appropriate. (This can be part of a specification.)
Some consumers experience bias and are under- or over-billed, largely because of temperature CV variation.
This is as fair as the current system can get; suppliers and gas transporters don’t gain. The cap limits the exposure of the worst affected (although arguably at the expense of bias in LDZ energy).
Doubling the uncertainty in CV determination at NTS Offtakes has little impact.
Uncertainty in CV determination at small entry points is unlikely to have significant impact (although yet to be modelled).
Cheap and cheerful CV measurement in Smart meters?