def shed(self, time, scenario=None, evaluate=False):
Pused = self.power(time, scenario=scenario)
Pavail = self.power_available(time, scenario=scenario)
if evaluate:
Pused = value(Pused)
Pavail = value(Pavail)
return Pavail - Pused
def shed(self, time, scenario=None, evaluate=False):
Pused = self.power(time, scenario=scenario)
Pavail = self.power_available(time, scenario=scenario)
if evaluate:
Pused = value(Pused)
Pavail = value(Pavail)
return Pavail - Pused
def visualization(self, filename=None):
'''power flow visualization'''
if not do_plotting:
return
try:
import networkx as nx
except ImportError:
logging.warning("Could'nt import networkx -- skipping plotting.")
return
buses, lines, t = self.buses, self.lines, self.times[0]
G = nx.DiGraph()
for bus in buses:
Pinj = value(bus.Pgen(t)) - value(bus.Pload(t))
G.add_node(bus.name, Pinj=Pinj)
for line in lines:
P = value(line.power(t))
if P >= 0:
G.add_edge(line.frombus, line.tobus, P=P, Plim=line.pmax)
else:
G.add_edge(line.tobus, line.frombus, P=-P, Plim=-line.pmin)
pos = nx.spectral_layout(G)
Pinj = [
ndata['Pinj'] for bus, ndata in G.nodes(data=True)
if 'Pinj' in ndata
]
nx.draw(G,
node_color=Pinj,
pos=pos,
node_size=1500,
alpha=.7,
cmap=plot.cm.get_cmap('RdYlBu'),
fontsize=30)
# TODO: get colorbar label working again
# ax = plot.gca()
# cb = plot.colorbar(ax=ax, shrink=.8)
# cb.set_label('injected power [MW]', fontsize=15)
Plines = [
edata['P'] for _, t, edata in G.edges(data=True) if 'P' in edata
]
atLimLines = [(f, t) for f, t, edata in G.edges(data=True)
if within(edata['P'], val=edata['Plim'], eps=1e-3)]
nx.draw_networkx_edges(G,
edge_color='0.6',
pos=pos,
width=Plines,
alpha=0.5)
nx.draw_networkx_edges(G,
edgelist=atLimLines,
edge_color='r',
pos=pos,
width=Plines,
alpha=0.5)
self.savevisualization(full_filename('powerflow.png'))
def output_incremental(self, input_var):
input_val = value(input_var)
if self.is_pwl:
for A, B in pairwise(self.bid_points):
if A[0] <= input_val <= B[0]:
return get_line_slope(A, B)
else:
return polynomial_incremental_value(self.polynomial, value(input_var))
def get_values(self, items, method='power', time=None, evaluate=False):
'''Get the attributes of all objects of a certain kind at a given time.'''
if time:
if evaluate:
out = [value(getattr(
obj, method)(time, evaluate=True)) for obj in items]
else:
out = [value(getattr(obj, method)(time)) for obj in items]
else:
out = [value(getattr(obj, method)) for obj in items]
return out
def gen_time_df(self, method, scenario, non_overlap=True, evaluate=False,
generators=None):
if generators is None:
generators = self.generators
if evaluate:
getval = lambda gen, t: value(
getattr(gen, method)(t, scenario, evaluate=True))
else:
getval = lambda gen, t: value(getattr(gen, method)(t, scenario))
times = self.times_non_overlap if non_overlap else self.times
return gen_time_dataframe(generators, times,
[[getval(gen, t) for t in times] for gen in generators])
def cost_shutdown(self, time, scenario=None, evaluate=False):
if self.shutdowncost == 0 or not self.commitment_problem:
return 0
else:
c = self.get_variable(
'shutdowncost', time, scenario=scenario, indexed=True)
return c if not evaluate else value(c)
def cost_shutdown(self, time, scenario=None, evaluate=False):
if self.shutdowncost == 0 or not self.commitment_problem:
return 0
else:
c = self.get_variable(
'shutdowncost', time, scenario=scenario, indexed=True)
return c if not evaluate else value(c)
def _get_problem_info(self):
self.solve_time = self.power_system.solution_time
self.objective = float(value(self.power_system.objective))
try:
self.mipgap = self.power_system.mipgap
except AttributeError:
self.mipgap = None
def power(self, time, scenario=None, evaluate=False):
if self.shedding_mode:
power = self.get_variable("power", time, scenario=scenario, indexed=True)
if evaluate:
power = value(power)
return power
else:
return self.get_scheduled_output(time)
def power(self, time, scenario=None, evaluate=False):
if self.shedding_mode:
power = self.get_variable('power', time,
scenario=scenario, indexed=True)
if evaluate:
power = value(power)
return power
else:
return self.get_scheduled_output(time)
def get_line_value(A, B, x):
'''
take a pair of points and make a linear function
get the value of the function at x
see http://bit.ly/Pd4z4l
'''
xA, yA = A
slope = get_line_slope(A, B)
return slope * (value(x) - xA) + yA
def visualization(self, filename=None):
'''power flow visualization'''
if not do_plotting:
return
try:
import networkx as nx
except ImportError:
logging.warning("Could'nt import networkx -- skipping plotting.")
return
buses, lines, t = self.buses, self.lines, self.times[0]
G = nx.DiGraph()
for bus in buses:
Pinj = value(bus.Pgen(t)) - value(bus.Pload(t))
G.add_node(bus.name, Pinj=Pinj)
for line in lines:
P = value(line.power(t))
if P >= 0:
G.add_edge(line.frombus, line.tobus, P=P, Plim=line.pmax)
else:
G.add_edge(line.tobus, line.frombus, P=-P, Plim=-line.pmin)
pos = nx.spectral_layout(G)
Pinj = [ndata['Pinj'] for bus, ndata in G.nodes(data=True)
if 'Pinj' in ndata]
nx.draw(G, node_color=Pinj, pos=pos, node_size=1500,
alpha=.7, cmap=plot.cm.get_cmap('RdYlBu'), fontsize=30)
# TODO: get colorbar label working again
# ax = plot.gca()
# cb = plot.colorbar(ax=ax, shrink=.8)
# cb.set_label('injected power [MW]', fontsize=15)
Plines = [edata['P'] for _, t, edata in G.edges(data=True)
if 'P' in edata]
atLimLines = [(f, t) for f, t, edata in G.edges(
data=True) if within(edata['P'], val=edata['Plim'], eps=1e-3)]
nx.draw_networkx_edges(
G, edge_color='0.6', pos=pos, width=Plines, alpha=0.5)
nx.draw_networkx_edges(G, edgelist=atLimLines, edge_color='r',
pos=pos, width=Plines, alpha=0.5)
self.savevisualization(full_filename('powerflow.png'))
def output(self, time=None, scenario=None, evaluate=False):
status = self.status_variable(time, scenario)
power = self.input_variable(time, scenario)
if evaluate:
status = value(status)
power = value(power)
if self.is_linear:
out = self.polynomial[1] * power
else:
out = self.get_variable('cost',
time=time, scenario=scenario, indexed=True)
if evaluate:
out = value(out)
if self.constant_term != 0:
out += status * self.constant_term
return out
def stg_panel(self, method,
generators=None,
no_overlap=True,
evaluate=False):
if generators is None:
generators = self.generators
times = self.times_non_overlap if no_overlap else self.times
if evaluate:
getval = lambda s, gen, t: value(
getattr(gen, method)(t, s, evaluate=True))
else:
getval = lambda s, gen, t: value(getattr(gen, method)(t, s))
return pd.Panel(
[[[getval(s, gen, t) for gen in generators]
for t in times] for s in self.scenarios],
items=[s for s in self.scenarios],
major_axis=times.strings.index,
minor_axis=[str(g) for g in generators])
def output_true(self, input_var, force_linear=False):
'''true output value of bid'''
input_val = value(input_var)
if (self.is_pwl or force_linear) and not self.is_linear:
if not self.is_pwl and self.bid_points is None:
# construct the bid points
bid_pt_outputs = map(lambda pt: polynomial_value(
self.polynomial, pt), self.discrete_input_points)
self.bid_points = zip(
self.discrete_input_points, bid_pt_outputs)
for A, B in pairwise(self.bid_points.values.tolist()):
if A[0] <= input_val <= B[0]:
return get_line_value(A, B, input_val) + self.constant_term
else:
return polynomial_value(self.polynomial, input_val)
def visualization(self, show_cost_also=False):
''' economic dispatch visualization of linearized incremental cost'''
if not do_plotting:
return
t = self.times[0]
price = self.lmps[str(t)][0]
generators = self.generators
loads = self.loads
plotted_gens, names_gens, plotted_loads, names_loads = [], [], [], []
minGen = min(getattrL(generators, 'pmin'))
maxGen = max(getattrL(generators, 'pmax'))
# save a plot of the price space - illustrating equal IC
ax = plot.axes()
for gen in generators:
if gen.status(t):
in_range, out_range = gen.bids.output_incremental_range()
if gen.bids.is_pwl:
line, = plot.step(
in_range, out_range, where='pre', linestyle='-')
else:
line, = plot.plot(in_range, out_range, linestyle='-', )
plotted_gens.append(line)
P = value(gen.power(t))
IC = gen.incrementalcost(t)
plot.plot(P, IC, '.', c=line.get_color(
), markersize=8, linewidth=2, alpha=0.7)
names_gens.append(gen.name)
if price is not None:
grayColor = '.75'
plot.plot([minGen, maxGen], [price, price], '--k', color=grayColor)
plot.text(maxGen, price, '{p:0.2f} $/MWh'.format(
p=price), color=grayColor, horizontalalignment='right')
plot.xlabel('P [MWh]')
if plotted_loads:
plot.ylabel('Marginal Cost-Benifit [$/MWh]')
else:
plot.ylabel('Marginal Cost [$/MWh]')
prettify_axes(ax)
# plot.xlim(xmin=0,xmax=)
ymin, _ = plot.ylim()
if ymin < 0:
plot.ylim(ymin=0)
legendGens = plot.legend(plotted_gens, names_gens, fancybox=True,
title='Generators:', loc='best')
if plotted_loads:
plot.legend(plotted_loads, names_loads,
fancybox=True, title='Loads:', loc='best')
# add first legend to the axes manually bcs multiple legends get overwritten
plot.gca().add_artist(legendGens)
self.savevisualization(filename=full_filename('dispatch.png'))
if show_cost_also:
# show a plot of the cost space, illustrating the linearization
plot.figure()
gensPlotted_price = plotted_gens
plotted_gens, names_gens, plotted_loads, names_loads = [
], [], [], []
for g, gen in enumerate(generators):
if gen.status(t):
plotted_gens.append(gen.cost_model.plot(
P=value(gen.power(t)),
linestyle='-',
color=gensPlotted_price[g].get_color()
))
names_gens.append(gen.name)
for load in loads:
if load.kind == 'bidding':
plotted_loads.append(load.bid(
t).plot(P=value(load.power(t)), linestyle=':'))
names_loads.append(load.name)
plot.xlabel('P [MWh]')
if plotted_loads:
plot.ylabel('Cost-Benifit [$/h]')
else:
plot.ylabel('Cost [$/h]')
legendGens = plot.legend(plotted_gens, names_gens, fancybox=True,
title='Generators:', loc='best')
if plotted_loads:
plot.legend(plotted_loads, names_loads,
fancybox=True, title='Loads:', loc='best')
plot.gca().add_artist(legendGens) # add first legend to the axes manually bcs multiple legends get overwritten
self.savevisualization(filename=full_filename('dispatch-cost.png'))
def getstatus(self, tend, times, status):
return dict(
status=value(self.status(tend)),
power=value(self.power(tend)),
hoursinstatus=self.gethrsinstatus(times, status))
def incrementalcost(self, time, scenario=None):
'''change in cost with change in power at time (based on exact bid polynomial).'''
return self.bids.output_incremental(self.power(time, scenario)) if value(self.status(time, scenario)) else None
def getstatus(self, tend, times, status):
return dict(status=value(self.status(tend)),
power=value(self.power(tend)),
hoursinstatus=self.gethrsinstatus(times, status))
def truecost(self, time, scenario=None):
'''exact cost of real power production at time (based on exact bid polynomial).'''
return value(self.status(time, scenario)) * self.bids.output_true(
self.power(time, scenario))
def Pload(self, t, evaluate=False):
if evaluate:
return sum(value(ld.power(t)) for ld in self.loads)
else:
return sum(ld.power(t) for ld in self.loads)
def truecost(self, time, scenario=None):
'''exact cost of real power production at time (based on exact bid polynomial).'''
return value(self.status(time, scenario)) * self.bids.output_true(self.power(time, scenario))
def Pgen(self, t, evaluate=False):
if evaluate:
return sum(value(gen.power(t)) for gen in self.generators)
else:
return sum(gen.power(t) for gen in self.generators)
def incrementalcost(self, time, scenario=None):
'''change in cost with change in power at time (based on exact bid polynomial).'''
return self.bids.output_incremental(self.power(
time, scenario)) if value(self.status(time, scenario)) else None
