the new iso 10723 · 2018-11-27 · iso 10723 ‐performance evaluations of on‐line analytical...
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The New ISO 10723
Advances and new concepts in the performance evaluation and benchmarking of on‐line natural gas analysers.
Dr Paul HollandBD Director, EffecTech Group
Natural gas quality measurementcomposition (content) of natural gas• inert gases
nitrogen, carbon dioxide, helium, (argon & hydrogen)
• hydrocarbons
methane, ethane, propane, iso‐butane, n‐butane, pentanes, hexanes + ......
properties (characteristics) of natural gas• calorific value, Wobbe number, standard density (ISO 6976)
• compression factor, line density (ISO 12213)
• hydrocarbon dew point (ISO 23874)
• emission factors
Energy determination
Risks in energy metering
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
3,000,000
3,500,000
4,000,000
4,500,000
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6
Annual Value / €
U(Energy) / %
Typical gas fired power stationPower output : 500 MWEnergy Price : €60 / MWh
Typical
Gas quality measurement instruments
Legal / commercial requirementslegislation
• customer protection (example in UK law)
Public Gas Transporters (PGTs) shall carry out performance evaluations of gas quality metering instruments in accordance with ISO 10723 following installation or maintenance. Provided that the results of the procedure show that the error on the calculated calorific value of transmission gas will not exceed 0.10 MJ.m‐3 for gas compositions allowed in the system, the PGT may then use that instrument for the determination of calorific values for the purposes of section 12 of the Gas Act 1986.”
• control of GHG emissions (example in EU directive)
commercial gas contracts• sales gas agreements / contracts (end‐users)
• allocation agreements (upstream)
Revision of ISO 10723 : 1995revision to existing standard required for • inclusion of measurement uncertainties
instrument precision, instrumental errors
working calibration gas
• compliance with GUM
• more rigorous assessment of errors and uncertainties of measurement of
composition (gas content amount fraction)
gas properties (calculated from composition)
revision by• ISO/TC193/WG15 (with liaison from ISO/TC158)
• Drafting by G Squire (EffecTech, UK) and D Lander (NGG, UK)
ISO/DIS 10723 : 2011 ‐ ScopeDetermine E(x), E(P) and U(x), U(P) over a pre‐defined range of compositions for each specified component
Determine a range of compositions for each specified component which satisfy pre‐
defined maximums in E(x), E(P) and U(x), U(P)
using a specified calibration gas composition and uncertainty
calibration gas redesigncomposition and uncertainty
Instrument errors
0 1 2 3 4 5 6 7 8 9 10
response / (peak area)
content / (% mol/mol)
y=Fass(x)
xcal
Instrument errors
0 1 2 3 4 5 6 7 8 9 10
response / (peak area)
content / (% mol/mol)
y=Fass(x)
y=Ftrue(x)
xcal
Instrument errors
0 1 2 3 4 5 6 7 8 9 10
response / (peak area)
content / (% mol/mol)
y=Fass(x)
y=Ftrue(x)
xcal
Instrument errors
0 1 2 3 4 5 6 7 8 9 10
response / (peak area)
content / (% mol/mol)
y=Fass(x)
y=Ftrue(x)
xcal
Challengemeasurement of TRUE (actual) response functions for the instrument for all components (i=1..q)• calibration functions
y = Fi,true(x)
• analysis functions
x = Gi,true(y)
function types for F & G• polynomials of order 1, 2 or 3
yi = Fi,true(xi) = a0 + a1xi + a1xi2 + a3xi3
xi= Gi,true(yi) = b0 + b1yi + b2yi2 + b3yi3
Design of reference gasesa series of reference gases is measured by the instrument being calibrated
components included in reference gases• depends on application
range of composition• equal or greater than that expected to be measured by the
instrument (no extrapolation)
number of mixtures • dependent upon expected order of F and G
3 (1st order), 5 (2nd order), 7 (3rd order)
• approximately equally spaced within the range
ISO 10723 ‐ Performance evaluations of on‐line analytical systems
• ISO 17025 accredited calibration gases
• well established reference values & uncertainties
• 7 ‐10 cylinders each containing 10,11 or 12 components
• wide range natural gas compositions
Experimental design
replicate measurements
referencegases
Batch‐wise calibration simplest / manual / most practical (p gas changes) temporal drift has more significance
replicate measurements
referencegases
Drift compensation calibration compensates for temporal drift (due to sample size effects) automation required
Experimental design
Drift correctionSamples are injected at (or with reference to) ambient pressure.response � effective sample size � ambient pressure
Batch‐wise calibration Drift compensation calibration
yijk = y’ijk . Pref / Pijk
measure ambient pressure at time of sample injection (Pijk)
Gas fired power station
Gas fired power station
Witnessed factory evaluation
LNG receiving terminal
Custody transfer border station
Drift compensation calibration (automated)
Offshore allocation / sales gas
Regression analysisparameters F and G are calculated using GLS• maximum liklihood functions relationships (MLFR)
• uncertainties in both variables (amount and response)
• procedure identical to that prescribed in ISO 6143
response functions validated for each component and in each domain F and G using ISO 6143
Calibration results
Errorscontent / amount fraction & properties• assumed
• true
• measured amount following calibration (where functions coincide)
• normalise
• errors
)(, iassii yGx )(, itrueii xFy
))(())((
.,,,
,,,,
*,
calitrueiassi
trueitrueiassicalimeasi xFG
xFGxx
*
,
*,
,measi
measimeasi x
xx
trueimeasimeasi xxx ,,,
truemeasmeas PPP
Uncertainties in errors
contributions from• calibration gas
• instrument precision
properties• any property / characteristic calculated from composition
)( ,calixu
)( & )( ,, measicali yuyu
),...,,,,...,,( 2121 mn wwwxxxfP
)()()( 2
1
22
1
22
i
m
i ii
n
i ic wu
wfxu
xfPu
produce a off‐line model of instrument• errors as a function of amount fraction
• repeatability as a function of amount fraction
• uncertainties as a function of amount fraction
use Monte Carlo simulation• generate 10,000 different gas compositions
• for each composition calculate
errors in physical properties
uncertainties in physical properties
Off‐line model
Errors and uncertainties on errors
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
78 80 82 84 86 88 90 92 94 96 98
E(CVSUP) / MJ.m-3
methane content / (% mol/mol)
Error distribution
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
78 80 82 84 86 88 90 92 94 96 98
E(CVSUP) / MJ.m-3
methane content / (% mol/mol)
Mean error (bias)
-0.16
-0.14
-0.12
-0.10
-0.08
-0.06
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
78 83 88 93 98
E(CVSUP) / MJ.m-3
methane content / (%mol/mol)
Maximum Permissible Bias (MPB)mean error = bias ‐ B(P)
MPBP
Uncertainty on mean error
-0.16
-0.14
-0.12
-0.10
-0.08
-0.06
-0.04
-0.02
0.00
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
78 83 88 93 98
E(CVSUP) / MJ.m-3
methane content / (%mol/mol)
Maximum Permissible Error (MPE)uncertainty on the mean error
≈ uncertainty on bias ‐ U(B(P)) MPEPUP c
Errors and uncertainties ‐ summary
Example – design of calibration gas
Example – design of calibration gas
xC1,cal = 0.88mean E(CV) = 0.001 ± 0.061 MJ.m‐3
Example – design of calibration gas
xC1,cal = 0.88mean E(CV) = 0.001 ± 0.061 MJ.m‐3
xC1,cal = 0.81mean E(CV) = 0.000 ± 0.028 MJ.m‐3
Analysis function correction ‐ superior CV
Instrument errors
0 1 2 3 4 5 6 7 8 9 10
response / (peak area)
content / (% mol/mol)
y=Fass(x)
y=Ftrue(x)
xcal
Dove HouseDove FieldsUttoxeterStaffordshireST14 8HUUnited Kingdom
tel : +44 (0)1889 569229e‐mail : paul.holland@effectech.co.ukweb‐site : www.effectech.co.uk
ISO9001:2008 FS 554539
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