def test_control_curve_interpolated(model): m = model m.scenarios.setup() si = ScenarioIndex(0, np.array([0], dtype=np.int32)) s = Storage(m, 'Storage', max_volume=100.0) cc = ConstantParameter(0.8) values = [20.0, 5.0, 0.0] s.cost = ControlCurveInterpolatedParameter(s, cc, values) s.setup(m) for v in (0.0, 10.0, 50.0, 80.0, 90.0, 100.0): s.initial_volume = v s.reset() assert_allclose(s.get_cost(m.timestepper.current, si), np.interp(v/100.0, [0.0, 0.8, 1.0], values[::-1])) # special case when control curve is 100% cc.update(np.array([1.0,])) s.initial_volume == 100.0 s.reset() assert_allclose(s.get_cost(m.timestepper.current, si), values[1]) # special case when control curve is 0% cc.update(np.array([0.0,])) s.initial_volume == 0.0 s.reset() assert_allclose(s.get_cost(m.timestepper.current, si), values[0])
def test_single_cc_load(self, model): """ Test load from dict with 'control_curve' key This is different to the above test by using singular 'control_curve' key in the dict """ m = model m.scenarios.setup() s = Storage(m, 'Storage', max_volume=100.0) data = { "type": "controlcurve", "storage_node": "Storage", "control_curve": 0.8, } s.cost = p = load_parameter(model, data) assert isinstance(p, ControlCurveParameter) s.setup(m) # Init memory view on storage (bypasses usual `Model.setup`) si = ScenarioIndex(0, np.array([0], dtype=np.int32)) s.initial_volume = 90.0 m.reset() assert_allclose(s.get_cost(m.timestepper.current, si), 0) s.initial_volume = 70.0 m.reset() assert_allclose(s.get_cost(m.timestepper.current, si), 1)