Quick Start Guide

Once Gas Models is installed, Pajarito is installed, and a network data file (e.g. "test/data/gaslib-40.json") has been acquired, a Gas Flow with SOC relaxation can be executed with,

using GasModels
using Pajarito

run_soc_gf("../test/data/gaslib-40.json", PajaritoSolver())

Similarly, a full non-convex Gas Flow can be executed with a MINLP solver like

run_nl_gf("../test/data/gaslib-40.json", CouenneNLSolver())

Getting Results

The run commands in GasModels return detailed results data in the form of a dictionary. This dictionary can be saved for further processing as follows,

run_soc_gf("../test/data/gaslib-40.json", PajaritoSolver())

For example, the algorithm's runtime and final objective value can be accessed with,

result["solve_time"]
result["objective"]

The "solution" field contains detailed information about the solution produced by the run method. For example, the following dictionary comprehension can be used to inspect the junction pressures in the solution,

Dict(name => data["p"] for (name, data) in result["solution"]["junction"])

For more information about GasModels result data see the GasModels Result Data Format section.

Accessing Different Formulations

The function "runsocgf" and "runnlgf" are shorthands for a more general formulation-independent gas flow execution, "rungf". For example, `runsoc_gf` is equivalent to,

run_gf("test/data/gaslib-40.json", MISOCPGasModel, PajaritoSolver())

where "MISOCPGasModel" indicates an SOC formulation of the gas flow equations. This more generic run_gf() allows one to solve a gas flow feasability problem with any gas network formulation implemented in GasModels. For example, the full non convex Gas Flow can be run with,

run_gf("test/data/gaslib-40.json", MINLPGasModel, CouenneNLSolver())

Modifying Network Data

The following example demonstrates one way to perform multiple GasModels solves while modify the network data in Julia,

network_data = GasModels.parse_file("test/data/gaslib-40.json")

run_gf(network_data, MISOCPGasModel, PajaritoSolver())

network_data["junction"]["24"]["pmin"] = 30.0

run_gf(network_data, MISOCPGasModel, PajaritoSolver())

For additional details about the network data, see the GasModels Network Data Format section.

Inspecting the Formulation

The following example demonstrates how to break a run_gf call into separate model building and solving steps. This allows inspection of the JuMP model created by GasModels for the gas flow problem,

gm = build_generic_model("test/data/gaslib-40.json", MISOCPGasModel, GasModels.post_gf)

print(gm.model)

solve_generic_model(gm, PajaritoSolver())