def test_MPC_solve_u_opt_2d(self):
'''test of MPC.solve_u_opt() method for 2d system'''
dt = self.dt
dyn2 = self.dyn2
n_sys = 2
assert n_sys == dyn2.nx
n_hor = int(2.5/dt)
assert n_hor == 12
u_max = 1.2 #kW
c2 = dmpc.MPC(dyn2, n_hor, 0, u_max, 1, 100)
# input predictions. needs to be flattened
T_ext_hor = 2+np.zeros((n_hor, n_sys)) # °C
T_ext_hor = T_ext_hor.reshape((n_hor * n_sys, 1))
Ts_hor = 18 + np.zeros((n_hor, n_sys)) # °C
Ts_hor[n_hor//2:] = 22 # °C
Ts_hor = Ts_hor.reshape((n_hor * n_sys, 1))
T0 = np.array([20,10]).reshape((n_sys,1))
c2.set_xyp(T0, Ts_hor, T_ext_hor)
u_opt = c2.solve_u_opt()
assert_equal(u_opt.shape, (n_hor * n_sys, 1))
u_opt = c2.solve_u_opt(reshape_2d=True)
assert_equal(u_opt.shape, (n_hor, n_sys))
u_expected = np.array([
[ 0.39993771, 1.19999994],
[ 0.79998731, 1.19999975],
[ 0.79998749, 1.19994822],
[ 0.7999875 , 0.83837907],
[ 0.79998827, 0.80037647],
[ 1.1215989 , 1.12105229],
[ 1.19999977, 1.19999963],
[ 1.19999867, 1.19999681],
[ 1.0593051 , 1.05942779],
[ 0.99998763, 0.99998742], # steady state at 1 kW
[ 0.99998749, 0.9999875 ],
[ 0.99973719, 0.99973719]])
print(repr(u_opt))
assert_allclose6(u_opt, u_expected)
def test_pred_output(self):
'''test MPC.pred_output method for 2d system'''
dt = self.dt
dyn2 = self.dyn2
n_sys = 2
assert n_sys == dyn2.nx
n_hor = int(2.5/dt)
assert n_hor == 12
u_max = 1.2 #kW
c2 = dmpc.MPC(dyn2, n_hor, 0, u_max, 1, 100)
# input predictions. needs to be flattened
T_ext_hor = 2+np.zeros((n_hor, n_sys)) # °C
T_ext_hor = T_ext_hor.reshape((-1, 1))
u_hor = np.zeros((n_hor, n_sys))
u_hor[n_hor//2:] = 1
u_hor = u_hor.reshape((-1, 1))
T0 = np.array([20,10]).reshape((n_sys,1))
T_pred = c2.pred_output(T0, u_hor, T_ext_hor)
assert_equal(T_pred.shape, (n_sys*n_hor, 1))
T_pred = c2.pred_output(T0, u_hor, T_ext_hor, reshape_2d=True)
assert_equal(T_pred.shape, (n_hor, n_sys))
T_expected = np.array([
[ 16.4 , 8.4 ],
[ 13.52 , 7.12 ],
[ 11.216 , 6.096 ],
[ 9.3728 , 5.2768 ],
[ 7.89824 , 4.62144 ],
[ 6.718592 , 4.097152 ],
[ 9.7748736 , 7.6777216 ],
[ 12.21989888, 10.54217728],
[ 14.1759191 , 12.83374182],
[ 15.74073528, 14.66699346],
[ 16.99258823, 16.13359477],
[ 17.99407058, 17.30687581]])
print(T_pred)
assert_allclose9(T_pred, T_expected)
def test_MPC_solve_u_opt(self):
'''test of MPC.solve_u_opt() method (calls cvxopt)'''
dt = self.dt
dyn = self.dyn1
n_hor = int(2.5/dt)
assert n_hor == 12
u_max = 1.2 #kW
ctrl = dmpc.MPC(dyn, n_hor, 0, u_max, 1, 100)
zn = np.zeros(n_hor)[:,None]
T_ext_hor = 2 + zn # °C
Ts_hor = 18 + zn # °C
Ts_hor[5:] = 22 # °C ()
T0 = 20 # °C
ctrl.set_xyp(T0, Ts_hor, T_ext_hor)
u_opt = ctrl.solve_u_opt()
assert_equal(u_opt.shape, (n_hor,1))
u_expected = np.array([
[ 0.39993755],
[ 0.79998746], # steady state at 0.8 kW
[ 0.7999875 ],
[ 0.79998751],
[ 1.12160221],
[ 1.19999986], # peak at u_max
[ 1.19999099],
[ 1.05931038],
[ 0.9999868 ], # steady state at 1 kW
[ 0.99998794],
[ 0.99998734],
[ 0.99973748]])
print((u_opt - u_expected))
assert_allclose6(u_opt, u_expected)
def test_MPC_closed_loop_sim_2d(self):
'''test MPC.closed_loop_sim() method on a 2d system'''
dt = self.dt
dyn2 = self.dyn2
n_sys = 2
assert n_sys == dyn2.nx
n_hor = int(1.5/dt)
assert n_hor == 7
n_sim = int(3/dt)
assert n_sim == 15
u_max = 1.2 #kW
c2 = dmpc.MPC(dyn2, n_hor, 0, u_max, 1, 100)
Ts_fcast_arr = 18 + np.zeros((n_sim+n_hor, n_sys)) # °C
Ts_fcast_arr[n_sim//2:] = 22 # °C
Ts_fcast = dmpc.Oracle(Ts_fcast_arr)
T_ext_fcast = dmpc.ConstOracle([2, 2]) # °C
T0 = np.array([20,10]).reshape((n_sys,1)) # °C
c2.set_oracles(Ts_fcast, T_ext_fcast)
u_sim, p, x, T_sim, Ts = c2.closed_loop_sim(T0, n_sim)
# check consistency of T set point with Oracle input
assert_equal(Ts.shape, (n_sim, n_sys))
assert_allclose9(Ts, Ts_fcast_arr[0:n_sim, :])
# Check temperature output
assert_equal(T_sim.shape, (n_sim, n_sys))
T_expected = np.array([
[ 20. , 10. ], # Ts is 18°
[ 17.99975046, 13.19999987],
[ 17.99974999, 15.75999979],
[ 17.99974999, 17.80799464],
[ 17.99974966, 17.99974909],
[ 17.99975053, 17.99975053],
[ 19.28619851, 19.28619851],
[ 20.62895623, 20.62895623], # Ts becomes 22°
[ 21.70300215, 21.70300215],
[ 21.99974997, 21.99974997],
[ 21.99974998, 21.99974998],
[ 21.99974998, 21.99974998],
[ 21.99974998, 21.99974998],
[ 21.99974998, 21.99974998],
[ 21.99974998, 21.99974998]])
print((T_sim - T_expected))
print(np.hstack((T_sim, T_expected)))
assert_allclose6(T_sim, T_expected)
# Check MPC control sequence
assert_equal(u_sim.shape, (n_sim, n_sys))
u_expected = np.array([
[ 0.39993761, 1.19999997],
[ 0.7999874 , 1.19999997], # u1 steady state at 0.8 kW, u2=u_max
[ 0.7999875 , 1.1999987 ],
[ 0.79998742, 0.83833834],
[ 0.7999877 , 0.79998781], # steady state at 0.8 kW
[ 1.12159952, 1.12159952],
[ 1.19999936, 1.19999936], # peak at u_max
[ 1.19995929, 1.19995929],
[ 1.05933706, 1.05933706],
[ 0.9999875 , 0.9999875 ], # steady state at 1 kW
[ 0.9999875 , 0.9999875 ],
[ 0.9999875 , 0.9999875 ],
[ 0.9999875 , 0.9999875 ],
[ 0.9999875 , 0.9999875 ],
[ 0.9999875 , 0.9999875 ]])
print((u_sim - u_expected))
assert_allclose6(u_sim, u_expected)
def test_MPC_closed_loop_sim(self):
'''test MPC.closed_loop_sim() method on a short simulation'''
dt = self.dt
dyn = self.dyn1
n_hor = int(1.5/dt)
assert n_hor == 7
n_sim = int(3/dt)
assert n_sim == 15
u_max = 1.2 #kW
ctrl = dmpc.MPC(dyn, n_hor, 0, u_max, 1, 100)
Ts_fcast_arr = 18 + np.zeros(n_sim+n_hor) # °C
Ts_fcast_arr[n_sim//2:] = 22 # °C
Ts_fcast = dmpc.Oracle(Ts_fcast_arr)
T_ext_fcast = dmpc.ConstOracle(2) # °C
T0 = np.atleast_2d(20) # °C
ctrl.set_oracles(Ts_fcast, T_ext_fcast)
u_sim, p, x, T_sim, Ts = ctrl.closed_loop_sim(T0, n_sim)
# check consistency of T set point with Oracle input
assert_equal(Ts.shape, (n_sim,1))
assert_allclose9(Ts, Ts_fcast_arr[0:n_sim, None])
# Check temperature output
assert_equal(T_sim.shape, (n_sim,1))
T_expected = np.array([
[ 20. ], # Ts is 18°
[ 17.99975035],
[ 17.99974999],
[ 17.99974999],
[ 17.99974966],
[ 17.99975053],
[ 19.28619851],
[ 20.62895623], # Ts becomes 22°
[ 21.70300215],
[ 21.99974997],
[ 21.99974998],
[ 21.99974998],
[ 21.99974998],
[ 21.99974998],
[ 21.99974998]])
print((T_sim - T_expected))
print(np.hstack((T_sim, T_expected)))
assert_allclose6(T_sim, T_expected)
# Check MPC control sequence
assert_equal(u_sim.shape, (n_sim,1))
u_expected = np.array([
[ 0.39993759],
[ 0.79998743], # steady state at 0.8 kW
[ 0.7999875 ],
[ 0.79998742],
[ 0.7999877 ],
[ 1.12159952], # peak at u_max
[ 1.19999936],
[ 1.19995929],
[ 1.05933706],
[ 0.9999875 ], # steady state at 1 kW
[ 0.9999875 ],
[ 0.9999875 ],
[ 0.9999875 ],
[ 0.9999875 ],
[ 0.9999875 ]])
print((u_sim - u_expected))
assert_allclose6(u_sim, u_expected)
# Create the dynamics
from therm_data import dt, C, R, P_max
print('Timestep dt: {} h'.format(dt))
print('Capacity C: {} kWh/K'.format(C))
print('Resistance R: {} °C/kW'.format(R))
print('P_max: {} kWh'.format(P_max))
dyn = dmpc.dynamics.from_thermal(R, C, dt, 'single room')
# Create the MPC controller
th = 2 # hours
nh = int(th / dt)
ctrl = dmpc.MPC(dyn, nh, u_min=0, u_max=P_max, u_cost=1, track_weight=100)
# Create the simulation context, e.g. forecast of perturbation and set points
from therm_data import T0, T_out, occupancy, T_abs, T_pres
print('Init temp: {} °C'.format(T0))
print('Outside temp: {} °C'.format(T_out))
print('Temp setpoints: {} °C (absent), {} °C (present)'.format(T_abs, T_pres))
n_sim = int(24 / dt)
t_fcast = np.arange(n_sim + nh) * dt
occ = occupancy(t_fcast)
T_set = np.zeros(n_sim + nh) + T_abs # °C
T_set[occ] = T_pres