from __future__ import print_function, division
from __future__ import absolute_import

import pypsa

import numpy as np


def test_sclopf():


    csv_folder_name = "../examples/scigrid-de/scigrid-with-load-gen-trafos/"

    network = pypsa.Network(csv_folder_name=csv_folder_name)

    #test results were generated with GLPK and other solvers may differ
    solver_name = "glpk"

    #There are some infeasibilities without line extensions
    for line_name in ["316","527","602"]:
        network.lines.loc[line_name,"s_nom"] = 1200

    network.now = network.snapshots[0]

    #choose the contingencies
    branch_outages = network.lines.index[:3]

    print("Performing security-constrained linear OPF:")

    network.sclopf(branch_outages=branch_outages)



    #For the PF, set the P to the optimised P
    network.generators_t.p_set.loc[network.now] = network.generators_t.p.loc[network.now]
    network.storage_units_t.p_set.loc[network.now] = network.storage_units_t.p.loc[network.now]

    #Check no lines are overloaded with the linear contingency analysis

    p0_test = network.lpf_contingency(branch_outages=branch_outages)

    #check loading as per unit of s_nom in each contingency

    max_loading = abs(p0_test.divide(network.passive_branches().s_nom,axis=0)).describe().loc["max"]


    np.testing.assert_array_almost_equal(max_loading,np.ones((len(max_loading))))


if __name__ == "__main__":
    test_sclopf()

Include unit test of Security-Constrained LOPF
Include unit test of Security-Constrained LOPF
