PSSE 240 Bus Case system with Renewables

Originally Contributed by: José Daniel Lara

Introduction

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.

julia> using PowerSimulationsDynamics
julia> using PowerSystemCaseBuilder
julia> using PowerSystems
julia> const PSY = PowerSystemsPowerSystems
julia> using Sundials
julia> using Plots
julia> using OrdinaryDiffEq

Load the system and transform load data

To load the system we use PowerSystemCaseBuilder.jl:

julia> # We remove the checks in this example to avoid large prints
       sys = build_system(PSIDSystems, "WECC 240 Bus"; runchecks = false)
       
       # Transform the system's loadERROR: UndefVarError: `build_system` not defined
julia> for l in get_components(PSY.StandardLoad, sys)
           transform_load_to_constant_impedance(l)
       endERROR: UndefVarError: `sys` not defined

Build the simulation and initialize the problem

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.

julia> using Logging
julia> sim_ida = 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,
       )ERROR: UndefVarError: `sys` not defined

Run the simulation using Sundials

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

julia> execute!(sim_ida, IDA(), dtmax = 0.01)ERROR: UndefVarError: `sim_ida` not defined

Read the results and plot a system variable

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.

julia> res_ida = read_results(sim_ida)ERROR: UndefVarError: `sim_ida` not defined
julia> v1101_ida = get_voltage_magnitude_series(res_ida, 1101);ERROR: UndefVarError: `res_ida` not defined
julia> plot(v1101_ida);ERROR: UndefVarError: `v1101_ida` not defined

Run the simulation using Rodas4()

In this case, we will use a MassMatrixModel formulation, for more details about the formulation checkout the Models Section in PowerSimulationsDynamics.jl documentation

julia> sim_rodas = 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,
       )ERROR: UndefVarError: `sys` not defined

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.

julia> execute!(
           sim_rodas,
           Rodas4(),
           saveat = 0.01,
           atol = 1e-10,
           rtol = 1e-10,
           initializealg = NoInit(),
       )ERROR: UndefVarError: `sim_rodas` not defined

Read the results

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.

julia> res_rodas = read_results(sim_rodas)ERROR: UndefVarError: `sim_rodas` not defined

Compare the results

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.

julia> v1101 = get_voltage_magnitude_series(res_rodas, 1101);ERROR: UndefVarError: `res_rodas` not defined
julia> plot(v1101, label = "RODAS4");ERROR: UndefVarError: `v1101` not defined
julia> plot!(v1101_ida, label = "IDA");ERROR: UndefVarError: `v1101_ida` not defined