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Added Flh of source and consumers and source capacity and power to th…
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…e parquet files
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@jylambert
jylambert committed Oct 29, 2024
1 parent 2b54cdb commit e2222f6
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Showing 2 changed files with 47 additions and 8 deletions.
1 change: 0 additions & 1 deletion examples/two-producers/run_sts_two_producers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -79,7 +79,6 @@ def main(filepath, outputpath, plots=True, solver='gurobi', mode='forced'):
opt.options['mipgap'] = settings.solver.mip_gap
opt.options['timelimit'] = settings.solver.time_limit
opt.options['logfile'] = os.path.join(outputpath, 'optimization.log')
#opt.options['Seed'] = 56324978

# Solve the optimization problem
result = opt.solve(model, tee=True)
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54 changes: 47 additions & 7 deletions topotherm/postprocessing.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,11 +69,15 @@ def sts(model: pyo.ConcreteModel,
# Get the values from the model
p_ij = np.array(pyo.value(model.P['ij', 'in', :, :]))
p_ji = np.array(pyo.value(model.P['ji', 'in', :, :]))
p_source_inst = np.array(pyo.value(model.P_source_inst[:]))
p_source = np.array(pyo.value(model.P_source[:, :]))

# flow direction, binary
lambda_ij = np.around(np.array(pyo.value(model.lambda_['ij', :])), 0)
lambda_ji = np.around(np.array(pyo.value(model.lambda_['ji', :])), 0)

q_c_opt = np.zeros([matrices['a_c'].shape[1], len(model.set_t)])
flh_c_opt = np.zeros([matrices['a_c'].shape[1], len(model.set_t)])

# Exclude non-connected consumers in Q_c, only affects the economic case
# Check for consumers connected in direction ij
Expand All @@ -87,15 +91,29 @@ def sts(model: pyo.ConcreteModel,
raise ValueError('Error in the incidence matrix!')
# assign the heat demand to the connected consumer if lambda is 1
q_c_opt[a_c_idx[0], :] = lambda_ij[e] * matrices['q_c'][a_c_idx[0], :]
flh_c_opt[a_c_idx[0], :] = lambda_ij[e] * matrices['flh_consumer'][a_c_idx[0], :]
elif d == 'ji':
a_i_idx = np.where(matrices['a_i'][:, e] == 1)
a_c_idx = np.where(matrices['a_c'][a_i_idx[0], :][0] == 1)
if len(a_i_idx) != 1 or len(a_c_idx) != 1:
raise ValueError('Error in the incidence matrix!')
q_c_opt[a_c_idx[0], :] = lambda_ji[e] * matrices['q_c'][a_c_idx[0], :]
flh_c_opt[a_c_idx[0], :] = lambda_ji[e] * matrices['flh_consumer'][a_c_idx[0], :]

# Remove nonzero elements row-wise
q_c_opt = q_c_opt[q_c_opt.any(axis=1)]
flh_c_opt = np.zeros([matrices['a_c'].shape[1], len(model.set_t)])

# Postprocessing producers
if np.shape(matrices['a_p'])[1] == 1:
p_source_inst_opt = p_source_inst
p_source_opt = p_source
flh_s_opt = matrices['flh_source']
else:
valid_sources = p_source_inst.any(axis=1)
p_source_inst_opt = p_source_inst[valid_sources]
p_source_opt = p_source[valid_sources, :]
flh_s_opt = matrices['flh_source'][valid_sources, :]

# Adaption of Incidence Matrix for further postprocessing
for q, _ in enumerate(lambda_ij):
Expand All @@ -107,8 +125,6 @@ def sts(model: pyo.ConcreteModel,
# values lambda_ij for ji. This is necessary for the postprocessing.
elif lambda_ji[q] == 1:
matrices['a_i'][:, q] = matrices['a_i'][:, q] * (-1)
lambda_ij[q] = 1
lambda_ji[q] = 0

p_lin = p_ij + p_ji # Power of the pipes

Expand All @@ -123,9 +139,10 @@ def sts(model: pyo.ConcreteModel,
a_i_opt = matrices['a_i'][valid_rows, :][:, valid_columns]
l_i_opt = matrices['l_i'][valid_columns]

a_i_shape_opt = np.shape(a_i_opt) # (rows 0, columns 1)
a_i_shape_opt = np.shape(a_i_opt) # (rows 0, columns 1)
d_lin = np.zeros(a_i_shape_opt[1]) # Initialize linear diameters
v_lin = np.zeros(a_i_shape_opt[1]) # Initialize velocities

# Assign supply and return temperatures
supply_temp_opt = np.ones(a_i_shape_opt[1]) * settings.temperatures.supply
return_temp_opt = np.ones(a_i_shape_opt[1]) * settings.temperatures.return_
Expand Down Expand Up @@ -153,12 +170,14 @@ def sts(model: pyo.ConcreteModel,
a_c=a_c_opt,
q_c=q_c_opt,
l_i=l_i_opt,
lambda_ij_opt=lambda_ij,
lambda_ji_opt=lambda_ji,
d_i_0=d_lin,
m_i_0=m_lin,
position=pos_opt,
p=p_lin_opt
p=p_lin_opt,
flh_c_opt=flh_c_opt,
flh_s_opt=flh_s_opt,
p_s_inst_opt=p_source_inst_opt,
p_s_opt=p_source_opt
)

return res
Expand All @@ -183,13 +202,16 @@ def mts(model: pyo.ConcreteModel,
p_ij = np.reshape(np.array(pyo.value(model.P['ij', 'in', :, :])), (-1, matrices['q_c'].shape[1]))
p_ji = np.reshape(np.array(pyo.value(model.P['ji', 'in', :, :])), (-1, matrices['q_c'].shape[1]))
p_cap = np.array(pyo.value(model.P_cap[:]))
p_source_inst = np.array(pyo.value(model.P_source_inst[:]))
p_source = np.array(pyo.value(model.P_source[:, :]))

# flow direction, binary
lambda_ij = np.reshape(np.around(np.array(pyo.value(model.lambda_['ij', :, :])), 0), (-1, matrices['q_c'].shape[1]))
lambda_ji = np.reshape(np.around(np.array(pyo.value(model.lambda_['ji', :, :])), 0), (-1, matrices['q_c'].shape[1]))
lambda_b = np.around(np.array(pyo.value(model.lambda_b[:])), 0)

q_c_opt = np.zeros([matrices['a_c'].shape[1], len(model.set_t)])
flh_c_opt = np.zeros([matrices['a_c'].shape[1], len(model.set_t)])

# Exclude non-connected consumers in Q_c, only affects the economic case
# Check for consumers connected in direction ij
Expand All @@ -203,15 +225,29 @@ def mts(model: pyo.ConcreteModel,
raise ValueError('Error in the incidence matrix!')
# assign the heat demand to the connected consumer if lambda is 1
q_c_opt[a_c_idx[0], :] = lambda_b[e] * matrices['q_c'][a_c_idx[0], :]
flh_c_opt[a_c_idx[0], :] = lambda_b[e] * matrices['flh_consumer'][a_c_idx[0], :]
elif d == 'ji':
a_i_idx = np.where(matrices['a_i'][:, e] == 1)
a_c_idx = np.where(matrices['a_c'][a_i_idx[0], :][0] == 1)
if len(a_i_idx) != 1 or len(a_c_idx) != 1:
raise ValueError('Error in the incidence matrix!')
q_c_opt[a_c_idx[0], :] = lambda_b[e] * matrices['q_c'][a_c_idx[0], :]
flh_c_opt[a_c_idx[0], :] = lambda_b[e] * matrices['flh_consumer'][a_c_idx[0], :]

# Remove nonzero elements row-wise
q_c_opt = q_c_opt[q_c_opt.any(axis=1)]
flh_c_opt = flh_c_opt[flh_c_opt.any(axis=1)]

# Postprocessing producers
if np.shape(matrices['a_p'])[1] == 1:
p_source_inst_opt = p_source_inst
p_source_opt = p_source
flh_s_opt = matrices['flh_source']
else:
valid_sources = p_source_inst.any(axis=1)
p_source_inst_opt = p_source_inst[valid_sources]
p_source_opt = p_source[valid_sources, :]
flh_s_opt = matrices['flh_source'][valid_sources, :]

# Adaption of Incidence Matrix for further postprocessing
for q in model.set_n_i:
Expand Down Expand Up @@ -282,7 +318,11 @@ def mts(model: pyo.ConcreteModel,
position=pos_opt,
p=p_lin_opt,
p_ij=p_ij_opt,
p_ji=p_ji_opt
p_ji=p_ji_opt,
flh_c_opt=flh_c_opt,
flh_s_opt=flh_s_opt,
p_s_inst_opt=p_source_inst_opt,
p_s_opt=p_source_opt
)

return res
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