def test_price_duality(test_mp):
years = [2020, 2025, 2030, 2040, 2050]
for c in [0.25, 0.5, 0.75]:
# set up a scenario for cumulative constraints
scen = Scenario(test_mp, MODEL, "cum_many_tecs", version="new")
model_setup(scen, years, simple_tecs=False)
scen.add_cat("year", "cumulative", years)
scen.add_par("bound_emission", ["World", "ghg", "all", "cumulative"],
0.5, "tCO2")
scen.commit("initialize test scenario")
scen.solve()
# set up a new scenario with emissions taxes
tax_scen = Scenario(test_mp, MODEL, "tax_many_tecs", version="new")
model_setup(tax_scen, years, simple_tecs=False)
for y in years:
tax_scen.add_cat("year", y, y)
# use emission prices from cumulative-constraint scenario as taxes
taxes = scen.var("PRICE_EMISSION").rename(columns={
"year": "type_year",
"lvl": "value"
})
taxes["unit"] = "USD/tCO2"
tax_scen.add_par("tax_emission", taxes)
tax_scen.commit("initialize test scenario for taxes")
tax_scen.solve()
# check that emissions are close between cumulative and tax scenario
filters = {"node": "World"}
emiss = scen.var("EMISS", filters).set_index("year").lvl
emiss_tax = tax_scen.var("EMISS", filters).set_index("year").lvl
npt.assert_allclose(emiss, emiss_tax, rtol=0.20)
def base_scen_mp(test_mp):
scen = Scenario(test_mp, 'model', 'standard', version='new')
data = {2020: 1, 2030: 2, 2040: 3}
years = sorted(list(set(data.keys())))
scen.add_set('node', 'node')
scen.add_set('commodity', 'comm')
scen.add_set('level', 'level')
scen.add_set('year', years)
scen.add_set('technology', 'tec')
scen.add_set('mode', 'mode')
output_specs = ['node', 'comm', 'level', 'year', 'year']
for (yr, value) in data.items():
scen.add_par('demand', ['node', 'comm', 'level', yr, 'year'], 1, 'GWa')
scen.add_par('technical_lifetime', ['node', 'tec', yr], 10, 'y')
tec_specs = ['node', 'tec', yr, yr, 'mode']
scen.add_par('output', tec_specs + output_specs, 1, '-')
scen.add_par('var_cost', tec_specs + ['year'], value, 'USD/GWa')
scen.commit('initialize test model')
scen.solve(case='original_years')
yield scen, test_mp
def test_new_timeseries_long_name64plus(message_test_mp):
scen = Scenario(message_test_mp, **SCENARIO["dantzig multi-year"])
scen = scen.clone(keep_solution=False)
scen.check_out(timeseries_only=True)
df = pd.DataFrame(
{
"region": [
"India",
],
"variable": [
(
"Emissions|CO2|Energy|Demand|Transportation|Aviation|"
"Domestic|Freight|Oil"
),
],
"unit": [
"Mt CO2/yr",
],
"2012": [
0.257009,
],
}
)
scen.add_timeseries(df)
scen.commit("importing a testing timeseries")
def base_scen_mp(test_mp):
scen = Scenario(test_mp, "model", "standard", version="new")
data = {2020: 1, 2030: 2, 2040: 3}
years = sorted(list(set(data.keys())))
scen.add_set("node", "node")
scen.add_set("commodity", "comm")
scen.add_set("level", "level")
scen.add_set("year", years)
scen.add_set("technology", "tec")
scen.add_set("mode", "mode")
output_specs = ["node", "comm", "level", "year", "year"]
for (yr, value) in data.items():
scen.add_par("demand", ["node", "comm", "level", yr, "year"], 1, "GWa")
scen.add_par("technical_lifetime", ["node", "tec", yr], 10, "y")
tec_specs = ["node", "tec", yr, yr, "mode"]
scen.add_par("output", tec_specs + output_specs, 1, "-")
scen.add_par("var_cost", tec_specs + ["year"], value, "USD/GWa")
scen.commit("initialize test model")
scen.solve(case="original_years", quiet=True)
yield scen, test_mp
def test_bound_emission_year(test_mp):
scen = Scenario(test_mp, "test_bound_emission", "standard", version="new")
model_setup(scen, [2020, 2030])
scen.commit("initialize test model")
add_bound_emission(scen, bound=1.250, year=2020)
scen.solve(case="bound_emission_year")
assert_function(scen, year=2020)
def test_price_duality(test_mp):
years = [2020, 2025, 2030, 2040, 2050]
for c in [0.25, 0.5, 0.75]:
# set up a scenario for cumulative constraints
scen = Scenario(test_mp, MODEL, 'cum_many_tecs', version='new')
model_setup(scen, years, simple_tecs=False)
scen.add_cat('year', 'cumulative', years)
scen.add_par('bound_emission', ['World', 'ghg', 'all', 'cumulative'],
0.5, 'tCO2')
scen.commit('initialize test scenario')
scen.solve()
# set up a new scenario with emissions taxes
tax_scen = Scenario(test_mp, MODEL, 'tax_many_tecs', version='new')
model_setup(tax_scen, years, simple_tecs=False)
for y in years:
tax_scen.add_cat('year', y, y)
# use emission prices from cumulative-constraint scenario as taxes
taxes = scen.var('PRICE_EMISSION')\
.rename(columns={'year': 'type_year', 'lvl': 'value'})
taxes['unit'] = 'USD/tCO2'
tax_scen.add_par('tax_emission', taxes)
tax_scen.commit('initialize test scenario for taxes')
tax_scen.solve()
# check that emissions are close between cumulative and tax scenario
filters = {'node': 'World'}
emiss = scen.var('EMISS', filters).set_index('year').lvl
emiss_tax = tax_scen.var('EMISS', filters).set_index('year').lvl
npt.assert_allclose(emiss, emiss_tax, rtol=0.20)
def test_bound_emission_5y(test_mp):
scen = Scenario(test_mp, "test_bound_emission", "standard", version="new")
model_setup(scen, [2020, 2025, 2030, 2040])
scen.commit("initialize test model")
add_bound_emission(scen, bound=1.250)
scen.solve(case="bound_emission_5y", quiet=True)
assert_function(scen, year="cumulative")
def test_bound_emission_5y(test_mp):
scen = Scenario(test_mp, 'test_bound_emission', 'standard', version='new')
model_setup(scen, [2020, 2025, 2030, 2040])
scen.commit('initialize test model')
add_bound_emission(scen, bound=1.250)
scen.solve(case='bound_emission_5y')
assert_function(scen, year='cumulative')
def test_commodity_price(test_mp):
scen = Scenario(test_mp, 'test_commodity_price', 'standard', version='new')
model_setup(scen)
scen.commit('initialize test model')
scen.solve(case='price_commodity_standard')
assert scen.var('OBJ')['lvl'] == 1
assert scen.var('PRICE_COMMODITY')['lvl'][0] == 1
def test_commodity_price(test_mp):
scen = Scenario(test_mp, "test_commodity_price", "standard", version="new")
model_setup(scen)
scen.commit("initialize test model")
scen.solve(case="price_commodity_standard")
assert scen.var("OBJ")["lvl"] == 1
assert scen.var("PRICE_COMMODITY")["lvl"][0] == 1
def test_init(test_mp):
scen = Scenario(test_mp, *msg_args)
scen = scen.clone('foo', 'bar')
scen.check_out()
macro.init(scen)
scen.commit('foo')
scen.solve()
assert np.isclose(scen.var('OBJ')['lvl'], 153.675)
def test_no_constraint(test_mp):
scen = Scenario(test_mp, MODEL, 'no_constraint', version='new')
model_setup(scen, [2020, 2030])
scen.commit('initialize test scenario')
scen.solve()
# without emissions constraint, the zero-cost technology satisfies demand
assert scen.var('OBJ')['lvl'] == 0
# without emissions constraint, there are no emission prices
assert scen.var('PRICE_EMISSION').empty
def test_no_constraint(test_mp):
scen = Scenario(test_mp, MODEL, "no_constraint", version="new")
model_setup(scen, [2020, 2030])
scen.commit("initialize test scenario")
scen.solve(quiet=True)
# without emissions constraint, the zero-cost technology satisfies demand
assert scen.var("OBJ")["lvl"] == 0
# without emissions constraint, there are no emission prices
assert scen.var("PRICE_EMISSION").empty
def test_init(test_mp):
scen = Scenario(test_mp, *msg_args)
obs = scen.var('OBJ')['lvl']
scen = scen.clone('foo', 'bar', keep_solution=False)
scen.check_out()
macro.init(scen)
scen.commit('foo')
scen.solve()
exp = scen.var('OBJ')['lvl']
assert np.isclose(obs, exp)
def test_new_timeseries_long_name64plus(test_mp):
scen = Scenario(test_mp, *msg_multiyear_args)
scen = scen.clone(keep_solution=False)
scen.check_out(timeseries_only=True)
df = pd.DataFrame({
'region': ['India', ],
'variable': [('Emissions|CO2|Energy|Demand|Transportation|Aviation|'
'Domestic|Freight|Oil'), ],
'unit': ['Mt CO2/yr', ],
'2012': [0.257009, ]
})
scen.add_timeseries(df)
scen.commit('importing a testing timeseries')
def test_add_year(test_mp):
scen_ref = Scenario(test_mp, 'model', 'standard', version='new')
model_setup(scen_ref, {2020: 1, 2030: 2, 2040: 3})
scen_ref.commit('initialize test model')
scen_ref.solve(case='original_years')
# Adding new years
years_new = [2025, 2035]
scen_new = adding_years(test_mp, scen_ref, years_new)
scen_new.solve(case='new_years')
# Running the tests
assert_function(scen_ref, scen_new, years_new, yr_test=2025)
def test_addon_up(test_mp):
scen = Scenario(test_mp, *msg_args).clone(scenario='addon_up',
keep_solution=False)
add_addon(scen, costs=-1, zero_output=True)
scen.check_out()
scen.add_par('addon_up', addon_share)
scen.commit('adding upper bound on addon technology')
scen.solve()
exp = scen.var('ACT', f)['lvl'] * 0.5
obs = scen.var('ACT', g)['lvl']
assert np.isclose(exp, obs)
def test_init(message_test_mp):
scen = Scenario(message_test_mp, **SCENARIO["dantzig"])
scen = scen.clone("foo", "bar")
scen.check_out()
MACRO.initialize(scen)
scen.commit("foo")
scen.solve(quiet=True)
assert np.isclose(scen.var("OBJ")["lvl"], 153.675)
assert "mapping_macro_sector" in scen.set_list()
assert "aeei" in scen.par_list()
assert "DEMAND" in scen.var_list()
assert "COST_ACCOUNTING_NODAL" in scen.equ_list()
def test_init(message_test_mp):
scen = Scenario(message_test_mp, **SCENARIO['dantzig'])
scen = scen.clone('foo', 'bar')
scen.check_out()
MACRO.initialize(scen)
scen.commit('foo')
scen.solve()
assert np.isclose(scen.var('OBJ')['lvl'], 153.675)
assert 'mapping_macro_sector' in scen.set_list()
assert 'aeei' in scen.par_list()
assert 'DEMAND' in scen.var_list()
assert 'COST_ACCOUNTING_NODAL' in scen.equ_list()
def test_addon_lo(message_test_mp):
scen = Scenario(message_test_mp, **SCENARIO['dantzig']) \
.clone(scenario='addon_lo', keep_solution=False)
add_addon(scen, costs=1, zero_output=True)
scen.check_out()
scen.add_par('addon_lo', addon_share)
scen.commit('adding lower bound on addon technology')
scen.solve()
exp = scen.var('ACT', f)['lvl'] * 0.5
obs = scen.var('ACT', g)['lvl']
assert np.isclose(exp, obs)
def test_addon_up(message_test_mp):
scen = Scenario(message_test_mp,
**SCENARIO["dantzig"]).clone(scenario="addon_up",
keep_solution=False)
add_addon(scen, costs=-1, zero_output=True)
scen.check_out()
scen.add_par("addon_up", addon_share)
scen.commit("adding upper bound on addon technology")
scen.solve()
exp = scen.var("ACT", f)["lvl"] * 0.5
obs = scen.var("ACT", g)["lvl"]
assert np.isclose(exp, obs)
def test_per_period_equidistant(test_mp):
scen = Scenario(test_mp, MODEL, 'per_period_equidistant', version='new')
years = [2020, 2030, 2040]
model_setup(scen, years)
for y in years:
scen.add_cat('year', y, y)
scen.add_par('bound_emission', ['World', 'ghg', 'all', y], 0, 'tCO2')
scen.commit('initialize test scenario')
scen.solve()
# with emissions constraint, the technology with costs satisfies demand
assert scen.var('OBJ')['lvl'] > 0
# under per-year emissions constraints, the emission price must be equal to
# the marginal relaxation, ie. the difference in costs between technologies
npt.assert_allclose(scen.var('PRICE_EMISSION')['lvl'], [1] * 3)
def test_per_period_equidistant(test_mp):
scen = Scenario(test_mp, MODEL, "per_period_equidistant", version="new")
years = [2020, 2030, 2040]
model_setup(scen, years)
for y in years:
scen.add_cat("year", y, y)
scen.add_par("bound_emission", ["World", "ghg", "all", y], 0, "tCO2")
scen.commit("initialize test scenario")
scen.solve()
# with emissions constraint, the technology with costs satisfies demand
assert scen.var("OBJ")["lvl"] > 0
# under per-year emissions constraints, the emission price must be equal to
# the marginal relaxation, ie. the difference in costs between technologies
npt.assert_allclose(scen.var("PRICE_EMISSION")["lvl"], [1] * 3)
def test_commodity_price_equality(test_mp):
scen = Scenario(test_mp, "test_commodity_price", "equality", version="new")
model_setup(scen, var_cost=-1)
scen.commit("initialize test model with negative variable costs")
# negative variable costs and supply >= demand causes an unbounded ray
pytest.raises(CalledProcessError, scen.solve)
# use the commodity-balance equality feature
scen.check_out()
scen.add_set("balance_equality", ["comm", "level"])
scen.commit("set commodity-balance for `[comm, level]` as equality")
scen.solve(case="price_commodity_equality")
assert scen.var("OBJ")["lvl"] == -1
assert scen.var("PRICE_COMMODITY")["lvl"][0] == -1
def test_commodity_price_equality(test_mp):
scen = Scenario(test_mp, 'test_commodity_price', 'equality', version='new')
model_setup(scen, var_cost=-1)
scen.commit('initialize test model with negative variable costs')
# negative variable costs and supply >= demand causes an unbounded ray
pytest.raises(CalledProcessError, scen.solve)
# use the commodity-balance equality feature
scen.check_out()
scen.add_set('balance_equality', ['comm', 'level'])
scen.commit('set commodity-balance for `[comm, level]` as equality')
scen.solve(case='price_commodity_equality')
assert scen.var('OBJ')['lvl'] == -1
assert scen.var('PRICE_COMMODITY')['lvl'][0] == -1
def test_cumulative_equidistant(test_mp):
scen = Scenario(test_mp, MODEL, "cum_equidistant", version="new")
years = [2020, 2030, 2040]
model_setup(scen, years)
scen.add_cat("year", "cumulative", years)
scen.add_par("bound_emission", ["World", "ghg", "all", "cumulative"], 0, "tCO2")
scen.commit("initialize test scenario")
scen.solve(quiet=True)
# with emissions constraint, the technology with costs satisfies demand
assert scen.var("OBJ")["lvl"] > 0
# under a cumulative constraint, the price must increase with the discount
# rate starting from the marginal relaxation in the first year
obs = scen.var("PRICE_EMISSION")["lvl"].values
npt.assert_allclose(obs, [1.05 ** (y - years[0]) for y in years])
def test_cumulative_equidistant(test_mp):
scen = Scenario(test_mp, MODEL, 'cum_equidistant', version='new')
years = [2020, 2030, 2040]
model_setup(scen, years)
scen.add_cat('year', 'cumulative', years)
scen.add_par('bound_emission', ['World', 'ghg', 'all', 'cumulative'], 0,
'tCO2')
scen.commit('initialize test scenario')
scen.solve()
# with emissions constraint, the technology with costs satisfies demand
assert scen.var('OBJ')['lvl'] > 0
# under a cumulative constraint, the price must increase with the discount
# rate starting from the marginal relaxation in the first year
obs = scen.var('PRICE_EMISSION')['lvl'].values
npt.assert_allclose(obs, [1.05**(y - years[0]) for y in years])
def test_addon_tec(test_mp):
scen = Scenario(test_mp, *msg_args).clone(scenario='addon',
keep_solution=False)
add_addon(scen, costs=-1)
scen.check_out()
bda = scen.par('bound_activity_up', f)
bda['value'] = bda['value'] / 2
scen.add_par('bound_activity_up', bda)
scen.commit('changing output and bounds')
scen.solve()
exp = scen.var('ACT', f)['lvl']
obs = scen.var('ACT', g)['lvl']
assert np.isclose(exp, obs)
def test_excel_read_write(test_mp):
fname = 'test_excel_read_write.xlsx'
scen1 = Scenario(test_mp, *msg_args)
scen1.to_excel(fname)
scen2 = Scenario(test_mp, model='foo', scenario='bar', version='new')
scen2.read_excel(fname)
exp = scen1.par('input')
obs = scen2.par('input')
pdt.assert_frame_equal(exp, obs)
scen2.commit('foo') # must be checked in
scen2.solve()
assert np.isclose(scen2.var('OBJ')['lvl'], 153.675)
os.remove(fname)
def test_addon_tec(message_test_mp):
scen = Scenario(message_test_mp,
**SCENARIO["dantzig"]).clone(scenario="addon",
keep_solution=False)
add_addon(scen, costs=-1)
scen.check_out()
bda = scen.par("bound_activity_up", f)
bda["value"] = bda["value"] / 2
scen.add_par("bound_activity_up", bda)
scen.commit("changing output and bounds")
scen.solve()
exp = scen.var("ACT", f)["lvl"]
obs = scen.var("ACT", g)["lvl"]
assert np.isclose(exp, obs)
