Accuracy of CV determination
systems for calculation of FWACV
Dave Lander
Update 12th October 2011
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”
B
• 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
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
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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
B
• Variation in gas quality
• “Location” uncertainty
 Quantity of gas
• Error, bias in domestic meter
• Error, bias in conversion factor
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A
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
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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%
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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
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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%]
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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
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?
Accuracy of CV determination systems - Page 13
Typical Inferential-type CVDDs uncertainty in GCV
 GasPT2 – 0.2-0.75%, depending on CO2 content
 EMC 500 – 0.2-0.5%
 Gas-lab Q1 – 0.4%
Title of Presentation - Page 14