# There are some doubts about the results of the experiments in the Powermodels documentation
**URL:** https://discourse.julialang.org/t/there-are-some-doubts-about-the-results-of-the-experiments-in-the-powermodels-documentation/105210
**Category:** Optimization (Mathematical)
**Created:** [October 20, 2023, 1:30am UTC](https://discourse.julialang.org/t/there-are-some-doubts-about-the-results-of-the-experiments-in-the-powermodels-documentation/105210 "2023-10-20T01:30:25Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@lzq-zbc](https://discourse.julialang.org/u/lzq-zbc)
#### Post date: [October 20, 2023, 1:30am UTC](https://discourse.julialang.org/t/there-are-some-doubts-about-the-results-of-the-experiments-in-the-powermodels-documentation/105210/1 "2023-10-20T01:30:25Z")
I would like to consult the following documents about the experimental results, for example, the calculation time of the SoC model of case1354\_pegase is 3 seconds, but I calculate the time on my personal computer is 17 seconds, and I am not sure why there is such a big gap. Here is some of the code I used
`using JuMP, PowerModels, Ipopt
file\_name = “E:/Vscode——data/data/case1354pegase.m”
model = Model(Ipopt.Optimizer)
power\_model = PowerModels.instantiate\_model(
PowerModels.parse\_file(file\_name),
PowerModels.SOCWRPowerModel,
PowerModels.build\_opf;
jump\_model = model,
)
optimize!(model)
println("Optimal objective value: ", JuMP.objective\_value(model))
println("Optimal solve time: ", JuMP.solve\_time(model))
`
---
### Author:  [@ccoffrin](https://discourse.julialang.org/u/ccoffrin)
#### Post date: [October 20, 2023, 2:16am UTC](https://discourse.julialang.org/t/there-are-some-doubts-about-the-results-of-the-experiments-in-the-powermodels-documentation/105210/2 "2023-10-20T02:16:20Z")
The experiment that is put in the PGLib table is run like the following,
```julia
result = solve_opf("data_file.m", SOCWRPowerModel, Ipopt.Optimizer)
result["solve_time"]
```
The key details for timing are,
1. make sure that the run does not include Julia’s JIT compile time. Running the function twice is sufficient
2. For large cases (say \>1000 buses) the linear solver can make a big difference in Ipopt’s performance. In these experiment HSL ma27 is used.