def re_visited_2(model, k):
if k == value(model.s) or k == value(model.t):
return Constraint.Skip
found = 0
for (i, j) in model.A:
if k in (i, j):
found = 1
break
if found == 0:
return Constraint.Skip
into_k = sum(model.r[(i, j)] for i, j in model.A if j == k)
return into_k <= 1
def re_visited_1(model, k):
if k == value(model.s) or k == value(model.t):
return Constraint.Skip
found = 0
for (i, j) in model.A:
if k in (i, j):
found = 1
break
if found == 0:
return Constraint.Skip
into_k = sum(model.r[(i, j)] for i, j in model.A if j == k and i != value(model.t))
out_of_k = sum(model.r[(i, j)] for i, j in model.A if i == k and j != value(model.s))
return into_k == out_of_k
def define_path(model):
start = value(model.s)
end = value(model.t)
all_steps = []
path = [start]
for v in model.component_objects(Var, active=True):
for index in v:
if v[index].value == 1:
all_steps.append(index)
start_step = find_next_step(all_steps, start)
next = start_step[1]
path.append(next)
end_not_found = True
while end_not_found:
next_step = find_next_step(all_steps, next)
next = next_step[1]
path.append(next)
if next == end:
end_not_found = False
return path
def costs_(model):
return sum(model.r[(i, j)] * model.c[(i, j)] for i, j in model.A) <= value(model.b)
def ends_2(model):
sum = 0
for i in model.N:
if (value(model.t), i) in model.A.value:
sum += model.r[(model.t, i)]
return sum == 0
def ends_1(model):
sum = 0
for i in model.N:
if (i, value(model.t)) in model.A.value:
sum += model.r[(i, model.t)]
return sum == 1
def starts_2(model):
sum = 0
for j in model.N:
if (j, value(model.s)) in model.A.value:
sum += model.r[(j, model.s)]
return sum == 0
def starts_1(model):
sum = 0
for j in model.N:
if (value(model.s), j) in model.A.value:
sum += model.r[(model.s, j)]
return sum == 1
def total_rule(model):
sum = 0
for i, j in model.A:
sum += model.r[(i, j)] * (value(model.eta) * model.g_i[i] + (1 - value(model.eta)) * model.p[i])
return sum
def _build_solution(self, results=None):
"""
Store the solution of the day-ahead market in the order book.
"""
model = self.model
book = self.orders
complexOrders = self.complexOrders
book.volumes = {
s: {l: {t: 0.0
for t in book.periods}
for l in model.L}
for s in ['SUPPLY', 'DEMAND']
}
book.prices = {
l: {t: model.pi[l, t].value
for t in book.periods}
for l in model.L
}
self.welfare = value(model.obj)
logging.info("welfare: %.2f" % value(self.welfare))
for i in model.sBids:
bid = book.bids[i]
# Obtain and save the volume
xs = model.xs[i].value
bid.acceptance = xs
# Update volumes and prices
if xs > options.EPS:
# Compute the total volumes exchanged
supplydemand = "SUPPLY" if bid.volume > 0 else "DEMAND"
t = bid.period
book.volumes[supplydemand][bid.location][t] += bid.volume * xs
for c in model.C:
flow_up = []
flow_down = []
congestion_up = []
congestion_down = []
for p in model.periods:
flow_up.append(model.f[c, 1, p].value)
flow_down.append(model.f[c, 2, p].value)
congestion_up.append(model.u[c, 1, p].value)
congestion_down.append(model.u[c, 2, p].value)
self.connections[c - 1].flow_up = flow_up
self.connections[c - 1].flow_down = flow_down
self.connections[c - 1].congestion_up = congestion_up
self.connections[c - 1].congestion_down = congestion_down
for i in model.bBids:
bid = book.bids[i]
# Obtain and save the volume
xb = model.xb[i].value
bid.acceptance = model.xb[i].value
if xb > options.EPS:
supplydemand = "SUPPLY" if bid.volumes[0] > 0 else "DEMAND"
for t, v in bid.volumes.items():
book.volumes[bid.location][t] += v
for i in model.cBids:
# logging.info('building solution for complex %d' % i)
bid = complexOrders[i - 1]
# Obtain and save the volume
bid.acceptance = model.xc[i].value
bid.surplus = model.sc[i].value
bid.volumes = [
model.complexVolume[i, p].value for p in model.periods
]
bid.pi_lg = [
model.pi[bid.location, p].value for p in model.periods
] # FIXME could be removed
if bid.acceptance < options.EPS: # Bid is rejected, is it paradoxically ?
bid.tentativeVolumes = dict(
zip(model.periods, [0.0] * len(model.periods)))
for p in model.periods:
for i in bid.ids:
if book.bids[i].price <= bid.pi_lg[
p - 1]: # FIXME assuming supply
bid.tentativeVolumes[p] += book.bids[i].volume
bid.tentativeIncome = sum(bid.tentativeVolumes[p] *
bid.pi_lg[p - 1]
for p in model.periods)
bid.isPR = (bid.tentativeIncome >=
bid.FT + bid.VT * sum(bid.tentativeVolumes[p]
for p in model.periods))
else:
bid.tentativeVolumes = {}
bid.tentativeIncome = 0
bid.isPR = False
