def onerun(data, loads, forecasts, errors=True):
status = []
times = []
mo, c_, v_ = init_problem(data)
for i in range(0, H - T):
start = time.perf_counter()
price = P[i: i + T, :]
# load = L[i : i + T]
if errors:
load = forecasts[i: i + T].copy()
load[0] = loads[i]
else:
load = loads[i: i + T].copy()
data['price'] = price
data['load'] = load
mo = update_problem(mo, c_, v_, data)
_ = mo.solve()
sol = cleanup_solution(mo, c_, v_, data)
bat = sol['var'][SLICE] - sol['var'][2 * SLICE]
net = sol['net'][0]
data['history_bat'][i] = bat
data['history_cost'][i] = sol['var'][0]
data['history_post_net'][i] = sol['net'][0]
data['charge'] += bat
end = time.perf_counter() - start
times.append(end)
if i % 50 == 0:
print('ITER', i)
return data
def init_players(players):
P = len(players)
L = players[0]['L']
for i in range(P):
data = players[i]
mo, c_, v_ = init_problem(data)
players[i]['model'] = mo
players[i]['con'] = c_
players[i]['var'] = v_
players[i]['history_bat'] = np.zeros(L)
players[i]['history_cost'] = np.zeros(L)
players[i]['history_pre_net'] = np.zeros(L)
players[i]['history_post_net'] = np.zeros(L)
def test_simple_opt_2(opt_problem_2):
data = opt_problem_2
data['T'] = 1
data['price'] = np.array([[1, 1, 3, 3, 0, 0, 0]])
data['load'] = np.array([-2])
data['commitment'] = -1
mo, c_, v_ = init_problem(data)
_ = mo.solve()
res = cleanup_solution(mo, c_, v_, data)
np.testing.assert_allclose(res['obj'], -2, atol=1e-5)
np.testing.assert_allclose(res['var'], np.array([-2, 0, 0]), atol=1e-5)
np.testing.assert_allclose(res['net'], np.array([-2]), atol=1e-5)
def test_simple_opt_1(opt_problem_2):
data = opt_problem_2
mo, c_, v_ = init_problem(data)
_ = mo.solve()
res = cleanup_solution(mo, c_, v_, data)
np.testing.assert_allclose(res['obj'], 21.3, atol=1e-5)
np.testing.assert_allclose(res['var'], np.array([13.8, 7.5, 0, 0, 0, 0]), atol=1e-5)
np.testing.assert_allclose(res['net'], np.array([2.0, 2.0]), atol=1e-5)
data['charge'] = 0.5
data['bmax'] = 0.5
mo = update_problem(mo, c_, v_, data)
_ = mo.solve()
res = cleanup_solution(mo, c_, v_, data)
np.testing.assert_allclose(res['obj'], 17.7, atol=1e-5)
np.testing.assert_allclose(res['var'], np.array([10.2, 7.5, 0, 0, 0.5, 0]), atol=1e-5)
np.testing.assert_allclose(res['net'], np.array([1.55, 2.0]), atol=1e-5)
data['price'][1] = np.array([2, 2, 3, 3, -1, 0 , 1])
mo = update_problem(mo, c_, v_, data)
_ = mo.solve()
res = cleanup_solution(mo, c_, v_, data)
np.testing.assert_allclose(res['obj'], 16.2, atol=1e-5)
np.testing.assert_allclose(res['var'], np.array([10.2, 6, 0, 0, 0.5, 0]), atol=1e-5)
np.testing.assert_allclose(res['net'], np.array([1.55, 2]), atol=1e-5)
data['commitment'] = 1.7
mo = update_problem(mo, c_, v_, data)
_ = mo.solve()
res = cleanup_solution(mo, c_, v_, data)
np.testing.assert_allclose(res['obj'], 16.95, atol=1e-4)
np.testing.assert_allclose(res['var'], np.array([11.4, 5.55, 0, 0, 1/3, 1/6]), atol=1e-4)
np.testing.assert_allclose(res['net'], np.array([1.7, 1.85]), atol=1e-4)
del data['commitment']
mo = update_problem(mo, c_, v_, data)
_ = mo.solve()
res = cleanup_solution(mo, c_, v_, data)
np.testing.assert_allclose(res['obj'], 16.2, atol=1e-5)
np.testing.assert_allclose(res['var'], np.array([10.2, 6, 0, 0, 0.5, 0]), atol=1e-5)
np.testing.assert_allclose(res['net'], np.array([1.55, 2]), atol=1e-5)
def simulate():
status = []
times = []
mo, c_, v_ = init_problem(D)
for i in range(0, H - T):
start = time.perf_counter()
price = P[i:i + T, :]
load = L[i:i + T]
D['price'] = price
D['load'] = load
mo = update_problem(mo, c_, v_, D)
sol = mo.solve()
end = time.perf_counter() - start
status.append(sol.solve_status)
times.append(end)
if i % 50 == 0:
print('ITER', i)
return status, times