effectech emib presentation

8/17/2019 EffecTech EMIB Presentation

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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 Holland

BD 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 station

Power output : 500 MW

Energy 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 ‐ Scope

Determine 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 redesign

composition

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



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 + b3yi

3



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

r e f e r e

n c e

g a s e s

Batch‐wise calibration

simplest / manual / most practical ( p gas changes)

temporal drift has more significance



replicate measurements

r e f e r e

n c e

g a s e s

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



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



Errors content / amount fraction & properties

• assumed

• true

• measured amount following calibration

(where functions coincide)

• normalise

• errors

)(, i assi i y G x

)(, i truei i x F y

))((

))((.

,,,

,,,

,

*

,

calitrueiassi

trueitrueiassi

calimeasi

xFG

xFGxx

*

,

*

,

,

measi

measi

measix

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 wwwxxxf P

)()()( 2

1

2

2

1

2

2

i

m

i i

i

n

i i

c wuw

f xu

x

f Pu



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))

MPE PUPc

d i i



Errors and uncertainties ‐ summary

E l d i f lib i



Example – design of calibration gas

E l d i f lib ti




xC1,cal = 0.88

mean E(CV) = 0.001 ± 0.061 MJ.m‐3

E l d i f lib ti




xC1,cal = 0.88

mean E(CV) = 0.001 ± 0.061 MJ.m‐3

xC1,cal = 0.81

mean E(CV) = 0.000 ± 0.028 MJ.m‐3



Analysis function correction ‐ superior CV



Dove House

Dove Fields

Uttoxeter

Staffordshire

ST14 8HU

United

Kingdom

tel : +44 (0)1889 569229

e‐mail : [email protected]

web‐site : www.effectech.co.uk

ISO9001:2008 FS 554539

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