#[PSSE 240 Bus Case system with Renewables](https://www.nrel.gov/grid/test-case-repository.html)
Originally Contributed by: José Daniel Lara
This tutorial will introduce the industry models of Renewable Energy the comparisons between DiffEq Integration techniques for comparison. We show the uses of Sundials and OrdinaryDiffEq to obtain the transient response of a system to a perturbation.
using PowerSimulationsDynamics
using PowerSystemCaseBuilder
using PowerSystems
using Sundials
using Plots
using OrdinaryDiffEq
PSD = PowerSimulationsDynamics
The system data is provided through PowerSystemCaseBuilder.
sys = build_system(PSSETestSystems, "psse_240_case_renewable_sys")
The next step is to create the simulation structure. This will create the indexing
of our system that will be used to formulate the differential-algebraic system of
equations. To do so, it is required to specify the perturbation that will occur in
the system. In this case, we will use a ResidualModel formulation, for more details
about the formulation checkout the Models Section
in PowerSimulationsDynamics.jl documentation
using Logging
sim_ida = PSD.Simulation(
ResidualModel,
sys, #system
pwd(),
(0.0, 20.0), #time span
BranchTrip(1.0, Line, "CORONADO -1101-PALOVRDE -1401-i_10");
console_level = Logging.Info,
)
We will now run the simulation using Sundials.jl solver IDA() by specifying the maximum dt we want for the simulation. In our experience with this solver, solution times are faster when supplying information about the maximum time step than the tolerances as we can see in the example
PSD.execute!(sim_ida, IDA(), dtmax = 0.01)
After the simulation is completed, we can extract the results and make plots as desired. In this case, we will plot the voltage magnitude at the bus at which the line was connected.
res_ida = read_results(sim_ida)
v1101_ida = get_voltage_magnitude_series(res_ida, 1101);
plot(v1101_ida)
In this case, we will use a MassMatrixModel formulation, for more details
about the formulation checkout the Models Section
in PowerSimulationsDynamics.jl documentation
sim_rodas = PSD.Simulation(
MassMatrixModel,
sys, #system
pwd(),
(0.0, 20.0), #time span
BranchTrip(1.0, Line, "CORONADO -1101-PALOVRDE -1401-i_10");
console_level = Logging.Info,
)
We will now run the simulation using OrdinaryDiffEq.jl solver Rodas4() by specifying the
tolerance we want for the simulation. In our experience with this solver, solution times are faster
when supplying information about the atol and rtol values as we can see in the example. The solver will also
work with a specified dtmax but take a significantly longer time to solve.
When using OrdinaryDiffEq.jl solvers always pass the option initializealg = NoInit() to avoid
unnecessary re-initialization of the algebraic equations.
PSD.execute!(
sim_rodas,
Rodas4(),
saveat = 0.01,
atol = 1e-10,
rtol = 1e-10,
initializealg = NoInit(),
)
After the simulation is completed, we can extract the results and make plots as desired. In this case, we will plot the voltage magnitude at the bus at which the line was connected.
res_rodas = read_results(sim_rodas)
After the simulation is completed, we can extract the results and make plots as desired. In this case, we will plot the voltage magnitude at the bus at which the line was connected. For both of the solution techniques.
v1101 = get_voltage_magnitude_series(res_rodas, 1101);
plot(v1101, label = "RODAS4")
plot!(v1101_ida, label = "IDA")
This notebook was generated using Literate.jl.