1. Ruel based decision support for the process flow Embedding SIMONE optimisation modules in a Knowledge and rule based process

2. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20082 Rule based decision support for the process flow - Contens -  Introduction Process flow of an optimisation   Knowledge based system   Rule based system   Rules for compressor plant configuration Pressure rules

3. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20083 Introduction Transport optimisation is a highly combinatorial Problem

4. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20084 Introduction - Compressor Plant - First level: Compressor plant second level: Compressor station third level: Compressor unit M M fourth level: Compressor Driver (Cooler)

5. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20085 Introduction - Network description - Compressor plants without crossings and circles (inline). Compressor plants with crossings and without circles (tree) Compressor plant with crossings and circles (mesh)

6. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20086 Rule based decision support for the process flow - Process flow of an optimisation - Introduction  Process flow of an optimisation   Knowledge based system   Rule based system   Rules for compressor plant configuration Pressure rules

7. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20087 Process flow of the optimisation - Overview - SIMONE external data Configuration optimisation Permutation 1. pre-processingLoads 1. post-processing Set-point optimisation of variants 2. post-processing Results 2. pre-processing

8. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20088 Inputs and off takes Valid for all runs Data sources: SCADA System various planning files Process flow of the optimisation - Loads -

9. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.20089 Read process data from SCADA system Create a balanced load scenario Calculate flows at the Compressor plants Set pressure boundaries Set storage pressure Set flow dependant pressure boudaris Process flow of the optimisation - 1. Pre-processing -

10. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200810 The results of the 1 pre-processing are used as input for the rule system The user can further reduce the resulting flow patterns for the compressor plants Maximum of 5 flow patterns per compressor palant Process flow of the optimisation - 2. Pre-processing -

11. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200811 Permutation of the flow patterns for the compressor plants derived by the 2. Pre-processing All derived flow patterns of the compressor plants are independently combinable with each other It is not neglectable to reduce the number of flow patterns as much as possible: ~ 10 plants ~ 5 flow patterns per station  ~ 5 10 different scenarios (N = 9.765.625)  runtime O(15N)  4,64 years (N = 750  3h7m30s)  runtime O(1N)  113 days (N = 750  12m30s) Process flow of the optimisation - Permutation -

12. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200812 Send data via API to Simone Run configuration set point optimisation with all Scenarios of the permutation Standard machine type has to be configured Number of available machines has to be configured Mixed integer and discrete optimisation with SIMONE (CSO) Process flow of the optimisation - configuration set point optimisation -

13. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200813 Read data via API from SIMONE Collect result data of the best results: Resulting configuration of the compressor stations Set point Decision criteria for the selected runs: Fuel gas consumption Necessary line pack shifting Create new variants by manual configuration Pre-selection of machine combinations with the estimated Power Select feasible combinations of aggregates Process flow of the optimisation - 1. Post processing-

14. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200814 Send data via API to SIMONE Set point optimisation with all variants SPO – Module is used Process flow of the optimisation - set point optimisation -

15. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200815 Read data via API from SIMONE Show best results of the scenarios (variants): Configuration of the compressor plants Set points Process flow of the optimisation - 2. Pre-Processing -

16. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200816 Rule based decision support for the process flow - Rule based System - Introduction Process flow of an optimisation    Knowledge based system    Rule based system    Rules for compressor plant configuration  Pressure rules

17. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200817 Knowledge based system - handled data - The knowledge based system contains the database Grid export from Simone Grid topology Static data Scenario parameters and configuration Simulation results

18. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200818 Rule based decision support for the process flow - Rule based System - Introduction Process flow of an optimisation   Knowledge based system    Rule based system    Rules for compressor plant configuration  Pressure rules

19. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200819 Rule based system - overview - Rule configuration to reduce the maximum number of possible flow patterns per Plant Set of rules for each compressor plant Dependency on the flow in the Branches of the compressor plants Declaration of pathes and direct connections Configuration of rules for pressure bounderies Dependency of flow on nodes Normal stations Bidirectional stations Storage pressure Formula for pressure boundary

20. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200820 Rule based system - Condition for flow pattern (1. conditions) -

21. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200821 Rule based system - Condition for flow pattern (2. flowpattern) -

22. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200822 Rule based system - Pressure rules -

23. Simone-Optimierung / WTKG Dirk Lieser, Mike Störmer/ GTD / 21.02.200823 END Thank‘s for your attention