Accuracy of CV determination systems for calculation of FWACV Dave Lander

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

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?