def test_iceland():
net = pn.iceland()
pp.runpp(net)
assert len(net.bus) == 189
assert len(net.line) + len(net.trafo) == 206
assert len(net.ext_grid) + len(net.gen) + len(net.sgen) == 35
assert net.converged
def test_iceland():
net = pn.iceland()
assert net.converged
pp.runpp(net, trafo_model='pi')
assert len(net.bus) == 189
assert len(net.line) + len(net.trafo) == 206
n_gen = 35
assert len(net.ext_grid) + len(net.gen) + len(net.sgen) == n_gen
assert len(net.polynomial_cost) == n_gen
assert net.converged
def test_iceland():
net = pn.iceland()
assert net.converged
_ppc_element_test(net, 189, 206, 35, True)
if show_sun:
rewards.append(sol[env._current_step - 1])
hues.append('Sun')
t_steps.append(t_step)
hours.append(hour)
if show_demand:
rewards.append(demand[env._current_step - 1])
hues.append('Demand')
t_steps.append(t_step)
hours.append(hour)
if __name__ == '__main__':
flex = 0.3
net = iceland()
env = ActiveEnv(base_net=net, seed=3)
env.set_parameters({'demand_std': 0, 'flexibility': flex})
forecast = env.demand_forecasts[:, 0]
a = -np.ones(env.action_space.shape) # max decrease in consumption
a = env.action_space.sample()
env.step(a)
net = env.powergrid
consumption = net.res_load['p_mw'] / net.load['sn_mva']
load_ratio = consumption / forecast
assert np.linalg.norm(load_ratio - (1 + a * flex)) < 10e-6
print('haha')