Grain LNG: A Collaborative Approach To LNG Terminal Business Performance Improvement

Transcription

1 Grain LNG: A Collaborative Approach To LNG Terminal Business Performance Improvement Nick Blair, Grain LNG, Commercial Operations Marco Fahl, Honeywell, Senior Consultant 2012 Business Optimization Conference Kuala Lumpur, Malaysia

2 Agenda Background on Grain LNG Grain LNG Collaboration aspects in Planning & Scheduling Models at Grain LNG LNG Terminal & CHP Interaction Annual Unloading Plan Cargo Unloading Scheduling Summary & Conclusions Business Optimization Conference

3 National Grid Grain LNG: Background Business 3 Optimization Conference

4 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 Business Optimization Conference

5 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 Business Optimization Conference

6 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 Business Optimization Conference

7 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 Business Optimization Conference

8 CDP within the Grain LNG system Landscape Business Optimization Conference

9 Grain LNG - Solution Overview Cost Allocation Environmental Reporting Commercial Ops Environmental 2-Yrs Heatpipe Forecast Annual Unloading Plan Utilities Tracking Gas Quality Plant Configuration Marine Ops Shift Teams Vessel Unloading Scheduling & Tracking Heat Nominations months ago days ago hours ago now hours ahead days ahead months ahead Business Optimization Conference

10 External Collaboration: Grain LNG - E.ON 2012 Business Optimization Conference Kuala Lumpur, Malaysia

11 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 Business Optimization Conference

12 Combined Heat and Power Scheme Vaporiser Send-Out Gas LNG Storage Tank Steam Turbine Condenser Gas Turbine LNG Carrier at Jetty Natural Gas In Business Optimization Conference

13 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 Business Optimization Conference

14 No. of SCVs 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 Gas sendout Figure 1: finding the temperature Business Optimization Conference

15 Internal Collaboration: Annual Unloading Plan and Cargo Unloading Scheduling 2012 Business Optimization Conference Kuala Lumpur, Malaysia

16 Collaboration is Key - An Example Shipper/Agent Commercial Ops AUP Model Berthing Slots PCAR PCAN Marine Ops Vessel Details / Confirmation Cargo Unloading Gas Quality Confirmation Coordination Ship Captain Utilities Tracking PCAR: Provisional Cargo Acceptance Request PCAN: Provisional Cargo Acceptance Notification Business Optimization Conference

17 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 Business Optimization Conference

18 Original Workflow for AUP Creation... 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 Shipper B Shipper C Shipper D Shipper E Shipper F /11/ : Total Copy & Paste Scheduled Comments Pattern E F F Repeats E F A B Q Q Q3 0 Q Sendo ADJUSTER Day A B C D E F # Arrivals Groups A B C D E 2 F XXX E shipxxx XXX XXX XXX ut /12/ A A,B schedules Int Capacity days , A /01/ B A E , B /01/ C F , C /01/ D , D EXCEL-based 0 04/01/ E #VALUE! , E /01/ F #VALUE! , F /01/ Schedule based #VALUE! E&F /01/ on (2) /01/ /01/ /01/ Shipping Schedule (across the two 12 jetties) 12 ShipE first in sequence 1 A calculations /01/ instances 13 of 135 ships in 5 days 60 ShipE last in sequence 3 B /01/ A 20 instances 14 of 144 ships in 4 days 80 ShipE single seq 0 C /01/ instances 15 of 153 ships in 3 days 42 ShipE in seq 11 D /01/ instances 16 of 162 ships in 2 days 24 E /01/ instances 17 of 171 ships in 1 days 29 F /01/ instances 18 of 180 ships in 0 days 0 E&F /01/ /01/ Shifted forward one day /01/ A Deleted Manual tuning & what-if /01/ B B Shifted back one day ShipE Count days between slots Max days between slots /01/ C /01/ Day A 24 B C 24 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 Sequences E/F SHIP MANUAL FILL D /01/ E E E F E 4 analysis E E Q1 Jan E Date Series E Year day E A D B A C A B C D A B C A D E Feb E Date E Year day E B A C A B C D A B A C D B E Mar E Date E E Year day A A C B D C A B A D B A C Q2 April C Date Year day A D B A C B D A C A B D C A May Date Year day B A C D A B C A B D C A B A Jun Date Year day D C A B C A D B A C A B D Q3 Jul Date Publishing Results Year day C A B A C D A B C A D B C A Aug Date Year day B D C A B A C D A B C A D B Sep Date Year day A C B A D C A B C A D B A C Q4 Oct Date Year day B A D C A B C A D B A C B Business Optimization Conference Nov Date Year day A D C A B A C D B A C B A D Maintain alternative versions... Copy & Paste

19 ... 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 Business Optimization Conference

20 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 Business Optimization Conference

21 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 Business Optimization Conference

22 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 Business Optimization Conference