kieran laxen - assessing the impacts of short-term power generation - dmug17

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Assessing the impacts of short-term power generation Kieran Laxen

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Page 1: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Assessing the impacts of short-term power generation

Kieran Laxen

Page 2: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Short-term operating plant:• Presentation topics

1. Assessment approach2. Model inputs and assumptions3. Consideration of impacts

• Applies to any limited operation plant• STORs• Backup generators• Emergency generators• CHP plant

• Discussing NOx emissions and NO2 impacts

Page 3: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

STOR Short Term Operating Reserve

• Banks / array of generators • Used for peak demand or for periods of no wind / sola

energy production • Possibly 250 to 2500 hours per year (or up to 8760?)• Operate on Diesel or Gas (to be economic gas needs to operate for

longer hours)

• Currently no permit required – no control on operating hours

• Urban and rural locations (including within AQMAs)

Page 4: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

STOR AssessmentsSome poor assessments being carried out• Crucial for a proper assessment to add generator impacts

to local baseline not just local background Background is averaged across a 1x1km grid square Baseline is the concentration at a receptor – for a receptor near a

road this will be higher than the background

• Annual mean impacts can be significant even with short-term operation

• Need to address short-term impacts using a probability approach

Page 5: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Problems faced - assessingThere is no official guidance in the UK in relation to development control on how to describe air quality impacts. Use IAQM/EPUK guidance.

Page 6: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Problems faced - Modelling• Constant operation or scheduled operation – typically

constant modelled. • Meteorological data – maximum of 5 years of modelled data• Constant emissions or variable emissions

• Be sceptical of any emissions data you’re given• Model at emission limits where nothing else is available.

• Chemistry?• Modelling road traffic?

Condition Specific Emissions Value Condition

NOx Emission rate (mg/Nm3) 903Standardised to 0degC, 101.325 kPa, measured oxygen (assumed to be 9% O2 content), wet (assumed to be 8%

moisture content).NOx Emission rate (mg/Nm3) 506 Normalised to 0 degC, 101.325 kPa, 15% O2, dry.NOx Emission rate (mg/Nm3) 1,793 Normalised to 0 degC, 101.325 kPa, 0% O2, dry.NOx Emission rate (g/kWhoutput) 3.7 -NOx Emission rate (g/s) 2.28 -

Page 7: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Example emissions• There are no requirements for stationary generators to meet EU Stage emission

limits (NRMM limits)! • Diesel generators / gas generators / dual fuel generators / abatement (SCR systems)• Emissions presented in the same units: dry flow, 0 degC, 101.325 kPa, 0% oxygen.• Based on typical generator combustion (~35-40% efficiency, 77% excess air, 9% O2,

8% moisture). Plant Emission Limit

(mg/Nm3)Comment

Diesel Generator (EU Stage 1) 4400 <9.2 g/kWhoutput

Diesel Generator (EU Stage 2) 2780 <6 g/kWhoutput

Diesel Generator (EU Stage 3) - For Plant <560 kWDiesel Generator (EU Stage 4) - For Plant <560 kW

Diesel Generator (Proposed EU Stage 5) 322 <0.67 g/kWhoutput

Gas Generator (500 mg/Nm3) 657 500 mg/Nm3 @ 5% O2 dryGas Generator (250 mg/Nm3) 329 250 mg/Nm3 @ 5% O2 dryGas Generator (25 mg/Nm3) 33 25 mg/Nm3 @ 5% O2 dry

MCPD Diesel 673 190 mg/Nm3 @ 15% O2 dryMCPD Gas (pre-31Dec17 operation) 673 190 mg/Nm3 @ 15% O2 dryMCPD Gas (post-31Dec17 operation) 337 95 mg/Nm3 @ 15% O2 dry

Page 8: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Warning – wrong emissionsEmission rates are provided at 5% O2, dry, 0 °C and 101.325 kPa.

Parameter Provided Calculated (15% O2) Calculated (0% O2)NOx mg/Nm3 1782 661.2 2342.2O2 (%) 5 15 0

H2O vapour (%) 0 0 0Absolute Exhaust Pressure (Pa) 101325 101325 101325Temp (°C) 0.0 0.0 0.0

Parameter Actual Normalised (incorrectly)Temp (°C) 470.0 0.0O2 (%) 15.0% (assumed) 15.0% (assumed)H2O vapour (%) Unknown UnknownMass Flow Rate (kg/h) Unknown UnknownVolume (m3/min) 460.0 169.0Volume (m+/h) 27267.7 10141.0 (calculated)

Parameter Actual Normalised (correctly)Temp (°C) 470.0 0.0Proportion Air Above Stoichiometric (%) 95.0% 0.0%

O2 (%) 9.8% 0.0%H2O vapour (%) 7.3% 0.0%Mass Flow Rate (kg/h) 12971.2 6308.8Volume (m3/h) 27541.0 4620.3

Lambda settings above about 1.9 start to result in misfires. Lambda 1.9 is 90% excess air.Supplier assumes 15% O2 in actual flow because that is the reference condition used to compare plant. 15% O2 = >280% excess air. This would lead to misfires. So is not realistic.

Emission rate calculated by supplier: 1.86 g/s

Emission rate calculated correctly: 3.00 g/s

Assuming correct flow conditions:

Supplied Calculations:

Page 9: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

NO2/NOx In-Stack Ratio (ISR) Database

Alpha databasehttps://www3.epa.gov/scram001/no2_isr_database.htm

<5% <10% <20% <30% <40% <50% <100%0

10

20

30

40

50

60

Diesel - Dataset size: 124Looking at the power of the generators, generators with >1000KW output are unlikely to be greater than 20% but there are some that are as high as 16%.

• If modelling chemistry…primary NO2?

Page 10: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Typical scenario

• Defra ‘mapped’ background NO2: 18-24 g/m3

• Significant local emission sources (e.g. road traffic)

Page 11: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Annual Mean – Impact descriptors Annual Mean Concentration At Receptor In Assessment Year

(g/m3)

Change in Concentration – NO2 (g/m3)

<0.2 0.2-0.6 0.6-2.2 2.2-4.0 >4.0

<30.2 Negligible Negligible Negligible Slight Moderate

30.2-37.8 Negligible Negligible Slight Moderate Moderate

37.8-41.0 Negligible Slight Moderate Moderate Substantial

41.0-43.8 Negligible Moderate Moderate Substantial Substantial

>43.8 Negligible Moderate Substantial Substantial Substantial

* Baseline will depend on the actual concentration and will need to be investigated

Process Contribution Band: 0.2 – 0.6 0.6 – 2.2 2.2 – 4.0 >4.0

Negligible <37.2 <28.0 - -

Slight adverse 37.2 - 40.4 28.0 - 35.6 <26.2  Moderate adverse >40.4 35.6 - 41.6 26.2 - 37.0 <33.8 *

Substantial adverse - >41.6 >37.0 >33.8 *

Baseline concentrations for defining impact descriptor:

Page 12: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Annual mean

0.6 to 2.2 g/m3 PC band – ‘moderate adverse’ if baseline is 35.6 to 41.6 g/m3

Typical emissions MCP emissions

Baseline:• Defra ‘mapped’ backgrounds (~24 g/m3) – all below 40 g/m3

• Monitoring? ~36 g/m3 – impact ‘moderate adverse’• Judgement? How many people are affected?

Page 13: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Approach for short-term impacts: ‘a lot of randomness’

• From the full 8760 value dataset, randomly select 250 values.

• Each time an hourly concentration is selected it is excluded from the dataset.

• Select the 19th highest value from the 250 independent values. This is a representative value for 19th highest concentration in the year.

Repeat this process 10,000 times or more!

Evaluate the 10,000 ‘years’ of calculated process contributions from randomly selected hours

Model a full year (accounting for worst-case modelling): output hour-by-hour data.

Page 14: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

What to do with 10,000 short-term PCs!

Minimum (g/m3) 8Maximum (g/m3) 33095%ile (g/m3) 201

PC (g/m3) Count Percentage0-100 4288 42.9%

100-120 1294 12.9%120-160 2675 26.8%160-200 1211 12.1%

>200 532 5.3%

0 50 100 150 200 250 300 350 4000

100

200

300

400

500

600

700

800

900

Process contribution

Coun

t

Annual Mean Baseline (g/m3) ~36-37Short-term baseline (g/m3) ~72-74Headroom (g/m3) (200 – baseline) 128Total (g/m3) (95%ile to max) 326-458

Chance of PC >120 (g/m3) 44.2%

Consider the whole dataset of predicted short-term concentrations:• All below the headroom?

>> no risk• A small number greater than the headroom?

>> some risk• Lots greater than the headroom?

>> high risk

Page 15: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Environment Agency Modelling

https://consult.defra.gov.uk/airquality/medium-combustion-plant-and-controls-on-generators/https://en.wikipedia.org/wiki/Hypergeometric_distribution

Page 16: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Probability and Risk Environment Agency has used hypergeometric distribution Probability of 200 µg/m3 being exceeded more than 18 times a year,

depending on the number of operational hours Acceptable risk:

the EA is saying that a 5% chance is acceptable AQC screens on a 1% chance

Model the percentile that would lead to chance

Page 17: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Mutually exclusive selections

• Dataset size – 24 values. 7 Ys and 13 Ns.

• You randomly select four of the values, and after each value is selected that value is not available to select again.

• What is the probability that two of the selected four are Y?

• Hypergeometric distribution!

Dataset - 1

Dataset - 2

Dataset - 3

Dataset - 4

Dataset - 5

Dataset -Selected

Y Y << randomly selected 1st N N N N NY Y Y Y YN N N N NN N N N NN N N N N << randomly selected 4th N N N N NY Y Y Y YN N N N NY Y Y Y YY Y Y Y YN N N N NN N N N NN N N << randomly selected 2nd Y Y Y Y YN N N N NY Y Y Y YN N N N NN N N N << randomly selected 3rd N N N N NY Y Y Y YN N N N NY Y Y Y Y

Page 18: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Hypergeometric distribution

drawn not drawn totalExceedenc

e k = 19 K − k = 353 K = 372

Not exceedenc

en − k = 231 N + k − n − K = 8157 N − K = 8388 (m)

Total n = 250 N − n = 8510 N = 8760

 Contingency table, 250 hours of operation:

How to calculate. Excel? ’R’ commands:

372 exceendence hours in full dataset before the is a 1% chance of 19 being selected

Page 19: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

The 95.75 %ile

No chemistry PC – 35% conversion Chemistry PC – 16% primary NO2

For 250 hours operation the 1% chance of an exceedence is associated with 372 hours in a full year above 200 µg/m3 (a 95.75th percentile = 372 / 8760)

In other words, we model for a full year and if the 95.75th percentile (including baseline) is less than 200 µg/m3 then there is less than a 1% chance of the objective being exceeded and the impact is ‘not significant’.

Page 20: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Assessed percentile

There are different percentiles for different operational hours and for difference associated probabilities

Hours of operation Number of hourly exceedences in full dataset for <1% probability of exceedence Percentile

250 372 95.75%500 186 97.88%1000 94 98.93%1500 64 99.27%2000 49 99.44%

Hours of operation Number of hourly exceedences in full dataset for <5% probability of exceedence Percentile

250 443 94.94%500 222 97.47%

1000 112 98.72%1500 75 99.14%2000 57 99.35%

Page 21: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Probability distribution vs calculated random selection

Minimum (g/m3) 7.5Maximum (g/m3) 329.595%ile (g/m3) 20198%ile (g/m3) 222

94.94%ile 95.75%ileChemistry - 16% primary NO2 186 g/m3 221 g/m3

Hypergeometric distribution is clearly more optimistic than the random selection approach

PC (g/m3) Count Percentage0-100 4288 42.9%

100-120 1294 12.9%120-180 3476 34.8%180-200 410 4.1%

>200 532 5.3%

<5% probability which the EA use is too optimistic The 94.94th %ile is not in the top 5% of concentrations

AQC use <1% probability criterion which is in the top 5%

vs

Page 22: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Final noteMedium Combustion Plan Directive

1 to 50 MWth plant

Transposed into UK law by December 2017 Emission limits from Dec 2018 for new plant and 2025 or 2030 for

existing plant Unclear who will Permit the plant – EA or LA

Siting Near or in AQMAs In suburban / residential areas Low level: 3-7 m release – near receptors Hospitals Horizontal exhaust

Page 23: Kieran Laxen - Assessing the impacts of short-term power generation - DMUG17

Head Office 23 Coldharbour Road, Bristol BS6 7JTTel: 0117 974 1086

London Office1 Burwood Place, London W2 2UTTel: 020 3873 4780