Grain LNG: A Collaborative Approach To LNG Terminal Business Performance Improvement · 2012. 11. 15. · CHP Scheme – Business Drivers •LNG vaporisation requires a large quantity

2012 Business Optimization Conference Kuala Lumpur, Malaysia

Grain LNG: A Collaborative Approach To LNG Terminal Business Performance Improvement Nick Blair, Grain LNG, Commercial Operations Marco Fahl, Honeywell, Senior Consultant

2 2012 Business Optimization Conference

Agenda

• Background on Grain LNG

• CDP @ Grain LNG

• Collaboration aspects in Planning & Scheduling Models at

Grain LNG

– LNG Terminal & CHP Interaction

– Annual Unloading Plan

– Cargo Unloading Scheduling

• Summary & Conclusions

3 2012 Business Optimization Conference 3

National Grid Grain LNG: Background


National Grid Grain LNG Vision

• In considering the way forward with their business processes, Grain LNG

considered it to be important to align these to the company vision of;

– Innovation and Efficiency

• Continual improvement of processes to add value to staff and customers

– Operational Excellence

• Build on our existing knowledge to provide consistently excellent

performance

• Around this vision, Grain LNG engaged Honeywell to scope potential

improvements around a large variety of workflows


CDP @ Grain LNG - Project Timeline

• June 2010: CDP Scoping Study

– Identify areas of improvement

• Dec 2010: Project Kick-Off "CDP Stage-1", incl. Staged

– Heat Nominations Forecasting (Heatpipe) Implementation

– Annual Unloading Plan (AUP)

• Jan 2011: Project Kick-Off "CDP Stage-2", incl.

– Marine Scheduling etc

• June 2011: SAT Stage-1 Scope

• July/Aug 2011: Scoping Study "Commercial Operations Business Processes"

• Sept 2011: SAT Stage-2 Scope

• July 2012: Project Kick-Off Stage-3 (Cost Allocation)

• Nov 2012 (Plan): SAT Stage-3 Scope


Introducing Capacity Distribution Planner (CDP)

• Provides interactive, structured and collaborative environment for decision support – Create model of production and distribution – Provides daily prediction of key values such as production and inventories – Enable view of plan and historical values – Manage plan revisions and workflow

• Easy to Use – Familiar Microsoft Office UI concepts – Conditional formatting to flag deviations – Supports what if capabilities

• Highly Configurable and Extensible – Calculations configured similar to Excel – Create views for specific users – Easy to add plug in capabilities

• Foundation for Supply Chain Solution – Integrates easily with other systems


Capacity and Distribution Planner (CDP)

• Excel-like, but without the inherent limitations and consistency problems

• Flexible models

• Easy to use, navigate

• Manages approved plan and tracks actuals against this plan

• Foundation for broader supply chain solutions

• Highly extensible and customizable


CDP within the Grain LNG system Landscape


Commercial Ops

Environmental

Marine Ops

Shift Teams

Gas Quality

CDP @ Grain LNG - Solution Overview

months ago days ago hours ago now hours ahead days ahead months ahead

Annual Unloading

Plan

2-Yrs Heatpipe

Forecast

Heat Nominations

Plant Configuration

Vessel Unloading

Scheduling & Tracking

Utilities Tracking

Environmental

Reporting

Cost Allocation


External Collaboration: Grain LNG - E.ON


CHP Scheme – Business Drivers

• LNG vaporisation requires a large quantity of energy, typically around

1.4% of the LNG vaporised

• E.ON built a 1.2 GW CCGT power station 3km from Grain LNG. Using

excess heat (up to 227MW) from their condensing units to heat hot water

for use in the vaporisation process

• Business Drivers

– Up to 300,000 tonnes of carbon dioxide saved

– E.ON benefit from levy exemption certificates for cleaner power generation

– Grain LNG save up to 170 mcm of customer's gas


Combined Heat and Power Scheme

Natural Gas In

Gas Turbine

Steam Turbine

Vaporiser

LNG Storage Tank

LNG Carrier at Jetty

Send-Out Gas

Condenser


Importance Of Collaboration

• The CHP project brings together two separate companies and processes with a combined goal

• Success is dependant on a wide variety of factors and data, some of which spans over the course of a year

• The scheduling of requirements needs to consider all relevant information and meet the demands of both teams

• Daily processes (heat nominations / renominations) to agree on heat requirements and delivery


Heat Nominations

Grain LNG / E.ON heat nomination process

• Day-Ahead Nominations (indicative-firm-final)

• In-Day Re-Nominations (up to every hr)

• Decisions incl

– Use heatpipe or fuel gas

– Heat amount

– Water temperature

– No of SCVs in CHP mode

1 3

4

2

5

Gas sendout

No

. o

f S

CV

s

Figure 1: finding the temperature


Internal Collaboration: Annual Unloading Plan and Cargo Unloading Scheduling


Commercial Ops

AUP Model

Cargo Unloading

PCAR

PCAN

Marine Ops

Gas Quality

Confirmation Coordination

Vessel Details / Confirmation

PCAR: Provisional Cargo Acceptance Request PCAN: Provisional Cargo Acceptance Notification

Berthing Slots

Shipper/Agent

Utilities Tracking

Collaboration is Key - An Example

Ship Captain


Annual Unloading Plan

• The Annual Unloading Plan (AUP) is a calendar showing when shippers are allowed to bring in a cargo

• The allocation of berthing slots is based on a number of heuristic rules including; – Number of slots (per contract) – Spacing between slots (per contract) – Specific shipper-shipper

relationships

• This was a manually intensive task to work out slot spacing in a way to minimise excursion from the rules


Original Workflow for AUP Creation ...

A

B

C

D

E

F

Q1 Jan

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

A D B A C A B C D A B C A D

Feb

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28

Year day 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59

B A C A B C D A B A C D B

Mar

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90

A A C B D C A B A D B A C

Q2 April C

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Year day 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120

A D B A C B D A C A B D C A

May

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151

B A C D A B C A B D C A B A

Jun

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Year day 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181

D C A B C A D B A C A B D

Q3 Jul

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212

C A B A C D A B C A D B C A

Aug

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243

B D C A B A C D A B C A D B

Sep

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Year day 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273

A C B A D C A B C A D B A C

Q4 Oct

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304

B A D C A B C A D B A C B

Nov

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

Year day 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334

A D C A B A C D B A C B A D

Dec

Date 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Year day 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365

E C A B C A D F C B A C D B E C A C B F

Publishing Results

Copy & Paste

Copy & Paste

Maintain alternative versions ...

AUTOSHEET XXX XXX XXX XXX Comments Ships Count 3,4,3,6 4,4,3,6 4,1,3,6 4,3,3,6 4,3,3,2 4,3,3,7 4,3,3,9

Shipper A 55 0.00 55 0 0 100 181 178 173 173 173 176 173

Shipper B 41 0.00 41 0 1 100 140 143 155 152 152 145 152

Shipper C 70 0.00 70 0 2 100 37 40 31 37 37 42 37

Shipper D 29 0.00 29 0 3 100 7 4 6 3 3 2 3

Shipper E 15 0.00 15 0 4 50 0 0 0 0 0 0 0

Shipper F 26 0.00 26 0 5 50 0 0 0 0 0 0 0

6 50 0 0 0 0 0 0 0

22/11/2011 14:06 236 236 0 Total 550 365 365 365 365 365 365 365

Scheduled 450 184 187 192 192 192 189 192

Pattern E F F Repeats E F

A 0 0 8 0 0

B 0 0 0 8 0 0

50 50 100

Q1 1 0 0

Q2 1 0 0

Q3 0

Q4 1

5 2 4 11

Day A B C D E F # Arrivals Groups A B C D E F E ship

6.64 8.90 5.21 12.59 24.33 14.04 31/12/2010 5 2 4 11 2 Int.

1 1 1 1 3 3 01/01/2011 6 3 5 12 A 3 3

2 0 02/01/2011 0.3636364 4 0.7857143 0.4137931 4 4

3 0 03/01/2011 1.3636364 5 1.7857143 1.4137931 5 5

4 0 04/01/2011 2.3636364 6 2.7857143 2.4137931 6 6

5 0 05/01/2011 3.3636364 7 3.7857143 3.4137931 7 7

6 1 1 2 2 06/01/2011 4.3636364 8 4.7857143 4.4137931 8 8

7 0 07/01/2011 5.3636364 0.097561 0.5714286 5.4137931 9 9

8 1 1 2 2 08/01/2011 6.3636364 1.097561 1.5714286 6.4137931 10 10

9 0 09/01/2011 0.7272727 2.097561 2.5714286 7.4137931 11 11

10 0 10/01/2011 1.7272727 3.097561 3.5714286 8.4137931 12 12

11 1 1 11/01/2011 2.7272727 4.097561 4.5714286 9.4137931 13 13

12 0 12/01/2011 3.7272727 5.097561 0.3571429 10.413793 A 14 14

13 0 13/01/2011 4.7272727 6.097561 1.3571429 11.413793 15 15

14 1 1 2 3 14/01/2011 5.7272727 7.097561 2.3571429 12.413793 16 16

15 1 1 15/01/2011 0.0909091 8.097561 3.3571429 0.8275862 17 17

16 1 1 16/01/2011 1.0909091 0.195122 4.3571429 1.8275862 18 18

17 0 17/01/2011 2.0909091 1.195122 0.1428571 2.8275862 19 19

18 0 18/01/2011 3.0909091 2.195122 1.1428571 3.8275862 20 20

19 1 1 19/01/2011 4.0909091 3.195122 2.1428571 4.8275862 21 21

20 0 20/01/2011 5.0909091 4.195122 3.1428571 5.8275862 B 22 22

21 1 1 21/01/2011 6.0909091 5.195122 4.1428571 6.8275862 23 23

22 1 1 22/01/2011 0.4545455 6.195122 5.1428571 7.8275862 24 24

23 0 23/01/2011 1.4545455 7.195122 0.9285714 8.8275862 25 25

A,B schedules

Comments

EXCEL-based calculations

1

ADJUSTERXXX XXX XXX XXX XXX

Sendo

ut 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

A 55 6.64 55 0 140 Capacity days 6.64 929.1 146,360 192780 5 55 A 0 1 0 0 0 0 21 32 1 0 0 0 0 0 0

B 41 8.90 41 0 102 E 168 8.90 908 143,045 190000 8 41 B 0 0 0 0 1 0 0 0 12 20 8 0 0 0 0

C 70 5.21 70 0 170 F 197 5.21 886.4 139,639 212500 4 70 C 0 0 1 0 6 43 20 0 0 0 0 0 0 0 0

D 29 12.59 29 0 73 12.59 918.8 144,737 145000 11 29 D 0 0 0 0 0 1 0 0 0 0 0 4 10 9 3

E 15 24.33 #VALUE! 160 10 1600 252,048 212500 9 14 E 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0

F 26 14.04 #VALUE! 160 6 960 151,229 212500 6 25 F 0 0 0 0 0 0 0 4 5 2 0 0 0 0 0

Schedule based 236 195 #VALUE! 1.186108 40 E&F 0 0 0 0 0 0 3 7 10 6 5 7 2 0 0

on 3-4-3-6-(2) 189.8

15 16 17 18 19 20 21 22 23 24 25 26 27 28

Shipping Schedule (across the two jetties) ShipE first in sequence 1 A 0 0 0 0 0 0 0 0 0 0 0 0 0 0

12 instances of 5 ships in 5 days 60 ShipE last in sequence 3 B 0 0 0 0 0 0 0 0 0 0 0 0 0 0

20 instances of 4 ships in 4 days 80 ShipE single seq 0 C 0 0 0 0 0 0 0 0 0 0 0 0 0 0

14 instances of 3 ships in 3 days 42 ShipE in seq 11 D 2 0 0 0 0 0 0 0 0 0 0 0 0 0

12 instances of 2 ships in 2 days 24 E 0 0 0 0 3 0 0 0 0 1 3 1 5 0

29 instances of 1 ships in 1 days 29 F 0 0 3 4 5 2 0 0 0 0 0 0 0 0

43 instances of 0 ships in 0 days 0 E&F 0 0 0 0 0 0 0 0 0 0 0 0 0 0

235

Shifted forward one day 7 7 3 5 0 6

Deleted

Shifted back one day 6 2 8 3 1 2

Day A B C D E F Ships E first Series Single last A B C D E F A B C D E F E&F E&F E/F SHIP6.64 8.90 5.21 12.59 14.04 0 0 0 0 0 0 6.64 8.90 5.21 12.59 0.00 14.04 MANUAL FILL

1 0 0 1 1 1 1 1 1 0 1 0 E

2 1 1 0 1 2 2 2 2 2 1 0 2 1 E

3 1 1 0 2 3 1 3 3 3 2 0 3 2 2 E

4 0 0 3 4 2 4 4 4 0 4 0 E

5 1 1 0 4 1 3 5 5 5 4 0 5 1 E

6 1 1 0 5 2 4 1 6 6 5 0 6 2 E

7 1 1 1 Series 6 3 5 2 1 7 6 6 1 1 3 E

8 1 1 2 7 4 1 3 2 8 5 0 2 4 E

9 1 1 3 1 5 2 4 3 9 7 0 3 5 5 E

10 0 4 2 6 3 5 4 10 0 4 0 0 E

11 0 5 3 7 4 6 5 11 0 5 0 E

12 1 1 6 4 8 1 7 6 12 4 0 6 1 1 E

13 0 7 5 9 2 8 7 13 0 7 0 E

14 1 1 8 6 1 3 9 8 14 9 0 8 1 E

15 1 1 9 1 2 4 10 9 15 6 0 9 2 2 E

16 0 10 2 3 5 11 10 16 0 10 0 E

Sequences

ShipE Count days between slots Max days between slots

Manual tuning & what-if analysis

2

3


... has been replaced by CDP-based Workflow for AUP Creation

• EXCEL-based logic has been encapsulated in CDP calculations

• Initial AUP available on button-click

• AUP updates and What-If analysis handled by CDP planning scenarios

• Data readily available for

• Users across the organization

• Integration with other CDP models / external applications


Cargo Unloading Scheduling

• Following the Phase 3 expansion Grain LNG has two jetties, both with different limitations to the vessel sizes they can accept

• Historical storage of information mainly paper based and held in individual files per vessel visit

• Expected offload times based on generic formulae over known vessel performance

• Recognised requirement for auditable planning and recording of vessel activities


Cargo Unloading CDP Model

• Inputs – AUP & Tide information

– Vessel Selection from Vessel Database

– Actual cargo unloading information

• Outputs/Functionality – Detailed timing of cargo

unloading based on vessel performance information

– Constraint evaluation with respect to

– Back-to-back unloadings

– Jetty assignments

– Ship Offloading Reports

– Forecast / Actual


Summary & Conclusions

• National Grid Grain LNG looked to build on operational excellence at the terminal with a drive for efficient processes

• CDP was seen as the ideal platform for managing the CHP scheme and other planning / reporting aspects in operations support

• The Heat Nomination and AUP models have delivered significant time savings and added clarity to both our customers and CHP partners

• The collaborative aspects ensure that all parties have the latest view of information; for the CHP scheme this delivers a large cost saving

• CDP is now seen as an area for growth and integration at Grain LNG

Documents

Grain LNG: A Collaborative Approach To LNG Terminal Business Performance Improvement · 2012. 11. 15. · CHP Scheme – Business Drivers •LNG vaporisation requires a large quantity