Gdmp model workshop 5 - structure of tim
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This document provides an overview of the Transportation Infrastructure Model (TIM), which identifies least cost infrastructure options to balance regional gas supply and demand in Indonesia until 2040. The model minimizes transportation costs across pipeline and LNG connections between regions based on inputs from the Detailed Assessment of Supply Scenarios model. Key outputs include optimized interregional flows, infrastructure capacity requirements, unmet demand volumes, and delivered gas costs by region. The document outlines the model assumptions, scenarios, limitations, and how to operate the model by running optimizations and adjusting inputs and connection concepts. It also provides an example of comparing results from base and high demand cases and adjusting connection concepts to find a more optimal infrastructure combination.
Gdmp model workshop 5 - structure of tim
- 1. Indo GDMP TIM Model Pilot Transportation Infrastructure Model (TIM) Demo version (GDMP Workshop June 2013)
- 2. 2 Presentation outline • Objective, approach and key outputs of TIM • Detailed presentation of TIM, covering – Assumptions – Scenarios – Limitations • User manual of model, covering – Running the model and selecting different scenarios – Changing inputs – Retrieving key output information • Practical application
- 3. 3 Presentation outline • Objective, approach and key outputs of TIM • Detailed presentation of TIM, covering – Assumptions – Scenarios – Limitations • User manual of model, covering – Running the model and selecting different scenarios – Changing inputs – Retrieving key output information • Practical application
- 4. 4 Objective of TIM and key questions Key issue for Gas Infrastructure Policy: supply centres removed from major demand centres Objective of TIM: identify set of least cost infrastructure options to balance supply and demand across regions until 2040 Key questions • What is the last cost infrastructure portfolio to balance regional supply and demand? • What are optimized interregional LNG and pipeline flows? • What are the liquefaction, regasification and interregional pipeline capacity requirements in each region? • What is the volume of unmet demand/imports in each region? • What is volume of excess supply, i.e. gas not consumed domestically or exported? • What is the cost of delivered gas in each region?
- 5. 5 Map illustrating S/D imbalances across regions Excess Production Unmet Demand Based on DASS Base Case scenario
- 6. 6 Approach and overview of methodology Approach followed in TIM is a minimization across transportation costs of pipeline and LNG connections This is done for each year with given export, demand and production volumes (inputs from DASS) in each region Approach ensures a balancing of supply and demand volumes across all regions at lowest transport cost Illustrative example C. Java E. Kalimantan W. Java • If E. Kalimantan has excess supply and if W. Java has unmet demand • TIM will prioritize connection via C. Java, because least cost: 2.1 $/mcf < 3.2 $/mcf 1.2 $/mcf 0.9 $/mcf 3.2 $/mcf
- 7. 7 Key outputs Infrastructure planning • Liquefaction, regasification and pipeline capacity needed to supply gas into each region • Optimized pipeline and LNG flows across regions • Earliest year gas transport infrastructure in each region is needed Export and production policy • Level of unmet demand, i.e. demand that cannot be covered by domestic production • Volume of excess production, i.e. scheduled production that is neither exported nor domestically consumed Investment requirements • Total cost of infrastructure requirements to balance supply and demand
- 8. 8 Output: Regional S/D balances, unmet demand, exports and interregional flows Excess Production Unmet DemandExports Domestic Transfers Click to go back to summary results slide
- 9. 9 Output: Interregional flows by connection concept Click to go back to summary results slide
- 10. 10 Output: Infrastructure Plan Click to go back to summary results slide
- 11. 11 Output: Costs, capacity requirements and throughputs Click to go back to summary results slide
- 12. 12 Presentation outline • Objective, approach and key outputs of TIM • Detailed presentation of TIM, covering – Assumptions – Scenarios – Limitations • User manual of model, covering – Running the model and selecting different scenarios – Changing inputs – Retrieving key output information • Practical application
- 13. 13 Model overview Infrastructure plan Infrastructure cost summary DASS inputs INPUT DATA Demand data Transport costs used in minimisation CONTROL PANEL RESULTSSCENARIOS Supply data Export data Connection Concepts Run minimisation Interregional LNG and pipeline flows S/D balances, exports, and unmet demand by region
- 14. 14 Inputs (1/2): demand, production, export Demand, export and production volumes over the period 2013-2040 will be imported from DASS. This means that the results are dependent on policy scenarios simulated and constructed in DASS. The transfer of DASS outputs to TIM Inputs is done via a transfer file.
- 15. 15 Inputs (2/2): Cost Parameters Input cost parameters are used for two purposes in model: 1. To calculate ‘typical unit transport cost’ used in minimization – input into minimization 2. To calculate ‘total infrastructure costs’ needed for optimized interregional flows and LNG exports – output of minimization The cost input parameters in TIM include: 2013 Pipeline Cost assumptions Offshore Pipeline CAPEX 70,000 US$/inch/km Onshore Pipeline CAPEX 35,000 US$/inch/km Compressor station costs 2,000 US$/horsepower One compressor station every 120km Capacity of compressor station 50 horsepower/Bcf/y Load factor of PL 80% Annual OPEX 3%of CAPEX 2013 LNG Cost assumptions Liquefaction CAPEX 1,200 US$/t of cap/y Liquefaction OPEX 6% of CAPEX Shipping costs 114,000 US$/day/ship Typical cargo ship capacity 150,000 Tonnes of LNG Traveling speed of LNG cargoes 30 km/h Regasification CAPEX 130 US$/t of cap/y Regas Annual OPEX 4% of CAPEX Boil-off rate in process 10% of gas transported
- 16. 16 Scenarios: Connection concepts approach Scenarios in TIM are defined by the selection of a combination of different ‘connection concept’ A connection concept consists of a transport link between two regions, i.e. an LNG or pipeline connection no specific infrastructure options are selected but connections between regions The selection of the connection concepts over which TIM optimizes is done manually and has to be determined by the user Example selection Included?
- 17. 17 Scenarios: Optimization methodology TIM projects gas flow profiles for each included connection concept until 2040 The flow projection is the result of minimizing the combination of transportation cost + volumes of unmet demand in every year The optimization therefore seeks the least cost combination of (selected) connection concepts while avoiding as best possible unmet demand. Cost used in optimization TIM uses levelised per unit costs determined prior to optimization. These are calculated on the basis of: • a typical flow profile for each connection concept • PV of CAPEX, OPEX and other costs (shipping costs for LNG, losses,….) • Where existing capacity exists only future OPEX are considered • Distance of connection concept
- 18. 18 Infrastructure cost and utilisation summaryInfrastructure plan Results: Maps, Tables and key figures Interregional LNG and pipeline flowsS/D balances, exports, and unmet demand by region
- 19. 19 Key assumptions in optimization and result generation • Costs minimization is based on pre-determined typical flows and are not based on optimized flow profiles • Costs over which are optimized are based on 2013 levels and are not assumed to change over time • Connection concepts utilizing existing capacity are costed at OPEX up until additional capacity is required •The minimium annual volumes of flows along a connection concepts warranting an expansion or construction of infrastructure is: • 13 Bcf/y for pipelines • 50 Bcf/y for Liquefaction • 25 Bcf/y for regasification • Unmet demand is costed at DES LNG prices
- 20. 20 Limitations of TIM • Production costs are not included in optimization- only transportation cost are considered • Due to the circularity of costs, i.e. costs depend on flows, which are the output of the optimization, TIM relies on a hypothetical cost number for each connection concept • Excel not the best optimization tool, hence solutions might not necessarily be the global minimum solution but might be local minimum • One iteration is not sufficient to provide insightful policy recommendations, need to adjust and change the list of connection concepts on the basis of the results from previous iteration
- 21. 21 Presentation outline • Objective, approach and key outputs of TIM • Detailed presentation of TIM, covering – Assumptions – Scenarios – Limitations • User manual of model, covering – Running the model and selecting different scenarios – Changing inputs – Retrieving key output information • Practical application
- 22. 22 Overview of model sheets Screenshot of worksheet directory
- 23. 23 Running model and selecting different scenarios The sheet where the user can select different scenarios is the control panel, where different connection options can be selected
- 24. 24 Changing input data (1/2) – Demand/Exports/Production To change demand, export and production scenarios, need to select the INPUT|S_D Balance sheet and copy/paste scenarios simulated in DASS from the ‘DASS Transfer tab’
- 25. 25 Changing input data (2/2) – Cost data To change cost data and thereby change the unit transport costs used in the iteration, change turquoise cells in ‘INPUT|Cost’ sheet
- 26. 26 Running optimization TIM allows for two iterations - we focus on 1.iteration initially. Optimization can be run from two sheets (‘Control Panel’ and Results|Infr. Plan’) The minimization is run by clicking on the ‘Run optimization’ button at the top of each of the two sheets. Keep button of ‘1.iteration’ selected for now
- 27. 27 Awaiting results Optimization can take up to 10 minutes and during optimization, user will be directed to RESULTS| Summary sheet. The progress of the optimization can be tracked via the graphs on the sheet, which will update every 2-3 minutes.
- 28. 28 Retrieving key output data and information All key outputs are summarized in the ‘RESULTS|….’ tabs, which are marked in green The four key outputs have been presented in previous slides and include: • Infrastructure plan of additional infrastructure required • Two maps of flows and S/D balances showing the flows implied by the optimization • Summary cost and throughput data
- 29. 29 Potential problems with results and adjusting scenarios (1/3) Results form an initial optimization might have the following problems: • low utilization of infrastructure resulting in excessively high per unit costs • Excess supply in some region and unmet demand in other regions • Regions have high unmet demand as well as large outflows – suggesting they are importing gas to send it to other regions
- 30. 30 Potential problems with results and adjusting scenarios (2/3) These problems can be reduced by adjusting the list of connection concepts selected in further scenarios • low utilization of connection concepts Proposed Solution: exclude in next run of model • Excess supply in some region and unmet demand in other regions Possible solution: include connection concept between these two regions by selecting the respective option in ‘Control Panel’ or overwriting options • Regions have high unmet demand as well as large outflows This results from the model finding a local minimum, possible solution: generally reduce the number of connection concepts
- 31. 31 Potential problems with results and adjusting scenarios (3/3) When adjusting and comparing the results of different runs, the key criteria is the change in ‘Volume of unmet demand’. If unmet demand increases from one run to the next, the changes in connection concepts selected are not improving the interregional supply demand balance.
- 32. 32 Presentation outline • Objective, approach and key outputs of TIM • Detailed presentation of TIM, covering – Assumptions – Scenarios – Limitations • User manual of model, covering – Running the model and selecting different scenarios – Changing inputs – Retrieving key output information • Practical application
- 33. 33 Enabling Excel on your computer to allow for the model to run (1/2) Excel needs to be updated in order to allow ‘Solver’ to be run on your computer. Follow these steps: 1. Enable Solver on your version of Excel: • Click on the Microsoft button and click on Excel Options • Click the Add-ins category • In the Manage box, click Excel Add-ins, and the click Go • In the Add-ins available box, select the check box next to Solver Add-in and the click Ok • Click Yes to install it 2. If you are using Excel 2007, you can now run the model. If you are using Excel 2010, continue these steps 3. Run the optimization by clicking on ‘Run optimisation’ button in Control panel (should not take much time) 4. Once finished, select the ‘Output|Calculation’ sheet, click on ‘Data’ and select Solver
- 34. 34 Enabling Excel on your computer to allow for the model to run (2/2) 5. In the window that appears, select the GRG nonlinear option in the dropdown menu and click on Solve 6. You can now run the optimization by clicking on ‘Run optimisation’ button in Control panel and this will give you the desired results. 7. Save the file after you’ve completed all above steps
- 35. 35 Practical application – Comparing results of base case and high case scenarios Questions to be addressed: 1. By how much does volume of unmet demand (in PV terms) increase between base case and high case scenario? 2. How do the infrastructure recommendations change between high case and base case? Approach: split attendees into two groups: one ‘base case’ group and one ‘high case’ group
- 36. 36 Practical application – adjusting connection concepts to find optimal combination – Step 1 Step 1: Ensure Solver is installed on all participating laptops Step 2: Copy production, export and demand numbers from DASS: Group 1: Base Case numbers Group 2: High case numbers Step 3: select connection concepts listed in next slide Step 4: run optimization
- 37. 37 Practical application – adjusting connection concepts to find optimal combination – Step 1
- 38. 38 Practical application – Answer to question 1 Base Case: 20,018 Bcf High Case: 40,706 Bcf
- 39. 39 Practical application – Answer to question 2 Base Case: High case:
- 40. 40 Back up Advanced Practical application: How to adjust the list of connection concepts to obtain an optimised set of infrastructure options?
- 41. 41 Advanced – adjusting connection concepts to find optimal combination – Step 1 Under base case demand, export and production assumptions, select following options and run optimization:
- 42. 42 Advanced – adjusting connection concepts to find optimal combination – Results Results of 1. scenario are sensible (PV of unmet demand is 20,018), however two problems persist: • high unit costs for some options (see next slide) • Unmet demand and domestic outflows in S. Moluccas, Central Java, East Kalimantan and C. & S Sumatra
- 43. 43 Advanced – adjusting connection concepts to find optimal combination - Step 2 On ‘Control Panel’, select button with 2. iteration to compare costs associated with optimized profile. Exclude those concepts with excessive unit costs
- 44. 44 Advanced – adjusting connection concepts to find optimal combination - Step 3 After excluding the above options, on ‘Control Panel’, select button with 1. iteration again and run optimization. Key results: • Unmet demand stays the same • Total infrastructure cost reduced from 53 billion US$ to 41 billion US$ • Region’s unmet demand and outflows behave in a good manner