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Gas Distribution Network Optimization with Genetic Algorithm

This study focuses on optimizing gas distribution networks, which are crucial for providing clean energy. Given the high costs associated with establishing new pipeline networks, we utilize a genetic algorithm to minimize investment, operational, and installation costs by optimizing the inner pipe diameter. We consider constraints like fixed pressure at inlet and outlet nodes, flow rates, and available pipe dimensions. Our methodology includes pressure distribution validation using both genetic algorithm and Newton methods, ensuring efficient and cost-effective pipeline design.

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Gas Distribution Network Optimization with Genetic Algorithm

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  1. Gas Distribution Network Optimization with Genetic Algorithm Kuntjoro Adji S. Lala Septem Riza Kusuma Chasanah Widita Febi Haryadi

  2. Introduction • Natural gas plays an important role in providing clean energy for the community. • Gas companies have planned to design and build a new gas pipeline network in many places. • To build pipeline network needs expensive cost in pipeline cost, investment cost, operasional cost, etc. • So, pipe diameter optimization process must be done to minimize the investment cost with considering to the pressure and flow rates that have been agreed in the contract

  3. Methodology • INPUT DATA: • Fix pressure on inlet and outlet node • Schematic of pipeline network • Geometries of pipe • Flow rate on each outlet • OUTPUT DATA: • ID, OD, t • Pressure Distribution • Cost (investment, coating, installation) • GENETIC ALGORITHM • To optimize inside diameter with minimize total cost • To determine pressure distribution on junction • With constrains: • Fix pressure on outlet node • Available pipe on market • Output: • Optimal inside diameter • Cost calculation • Pressure on each node • VALIDATION OF PRESSURE DISTRIBUTION • (Using Genetic Algorithm and Newton Method for checking/calculating of pressure distribution) • Input: • Optimal inside diameter • Pressure on inlet node • Output: • Pressure distribution on each node

  4. The problem formulation Minimize subject to is balancing equation at node i.

  5. The Genetic Optimization Minimize subject to • Pressure on each inlet is given. • Inside diameter which available on market, 64 kind of ID (3 inch – 16 inch). • flow rate on each outlet.

  6. The model of gas flow in pipe • The panhandle A: • The equation system is constructed based on kirchoff’s law: “ at any node, the sum of mass flow into that node is equal to the sum of mass flow out of that node”

  7. Continuity equations at the system:

  8. Continuity equation at node m: • QNmis the node flow (supply / demand rate) at node m

  9. Continuity equation at node 6: • Obtained: • N continuity equations

  10. The economic model • Investment cost: • Coating cost: • Installation cost: • Operational cost(rule of thumb): 4% * investment cost.

  11. Flow Chart of Genetic Algorithm

  12. The Computation Method:The Genetic Algorithm • To search the suitable pressure and index of inside diameter available on the market which give the best fitness. • The representation of population:

  13. The Computation Method:The Genetic Algorithm (con’t) • Fitness function: • We use usual the Selection, crossover and mutation operator.

  14. Case Study Input Data: 1). The schematic network, 2). There are 18 nodes: 1 inlet, 7 junctions, 10 outlet. And there are 17 pipe segments. 3). Pressure on inlet and on each outlet. To find: • Pressure on each junction • ID on each segments. • Cost calculation

  15. The software“OptDistNet”

  16. 1st simulation • To calculate the optimum diameter using GA • Input: pressure on inlet “S1” and pressure on each outlet, length of pipe. • Output: ID on 17 segment pipe and pressure on each junction.

  17. Result: Pressure Distribution on junction

  18. Result: Optimum Pipe Diameter

  19. Result: Cost Calculation

  20. 2nd Simulation • To validate pressure on each node using optimum inside diameter. • Input: • Inside diameter • Pressure on inlet • Flow rate on each outlet • Output: • Pressure on each node.

  21. Result: Pressure Distribution

  22. Conclusions • The simple Genetic Algorithm can be helpful in finding an optimal inside diameter.

  23. Thank You

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