def on_closing(self):
if messagebox.askokcancel('Quit', 'Do you want to close this window? This is likely to stop all simulations.'):
self.root.quit()
self.root.destroy()
if self.bFNCSactive:
fncs.finalize()
self.bFNCSactive = False
def Quit(self):
"""Shuts down this monitor, and also shuts down FNCS if active
"""
self.root.quit()
self.root.destroy()
if self.bFNCSactive:
fncs.finalize()
self.bFNCSactive = False
def kill_all(self):
for proc in self.pids:
print('trying to kill', proc.pid)
proc.terminate()
self.root.update()
print('trying to finalize FNCS')
fncs.finalize()
print('FNCS finalized')
def kill_all(self):
"""Shut down all FNCS federates in TESP, except for this monitor
"""
for proc in self.pids:
print('trying to kill', proc.pid)
proc.terminate()
self.root.update()
print('trying to finalize FNCS')
if self.bFNCSactive:
fncs.finalize()
self.bFNCSactive = False
print('FNCS finalized')
def on_closing(self):
"""Verify whether the user wants to stop TESP simulations before exiting the monitor
This monitor is itself a FNCS federate, so it can not be shut down without shutting
down all other FNCS federates in the TESP simulation.
"""
if messagebox.askokcancel(
'Quit',
'Do you want to close this window? This is likely to stop all simulations.'
):
self.root.quit()
self.root.destroy()
if self.bFNCSactive:
fncs.finalize()
self.bFNCSactive = False
def pypower_loop (casefile, rootname):
""" Public function to start PYPOWER solutions under control of FNCS
The time step, maximum time, and other data must be set up in a JSON file.
This function will run the case under FNCS, manage the FNCS message traffic,
and shutdown FNCS upon completion. Five files are written:
- *rootname.csv*; intermediate solution results during simulation
- *rootname_m_dict.json*; metadata for post-processing
- *bus_rootname_metrics.json*; bus metrics for GridLAB-D connections, upon completion
- *gen_rootname_metrics.json*; bulk system generator metrics, upon completion
- *sys_rootname_metrics.json*; bulk system-level metrics, upon completion
Args:
casefile (str): the configuring JSON file name, without extension
rootname (str): the root filename for metrics output, without extension
"""
# if len(sys.argv) == 3:
# rootname = sys.argv[1]
# casefile = sys.argv[2]
# else:
# print ('usage: python fncsPYPOWER.py metrics_rootname casedata.json')
# sys.exit()
ppc = load_json_case (casefile)
StartTime = ppc['StartTime']
tmax = int(ppc['Tmax'])
period = int(ppc['Period'])
dt = int(ppc['dt'])
make_dictionary (ppc, rootname)
bus_mp = open ("bus_" + rootname + "_metrics.json", "w")
gen_mp = open ("gen_" + rootname + "_metrics.json", "w")
sys_mp = open ("sys_" + rootname + "_metrics.json", "w")
bus_meta = {'LMP_P':{'units':'USD/kwh','index':0},'LMP_Q':{'units':'USD/kvarh','index':1},
'PD':{'units':'MW','index':2},'QD':{'units':'MVAR','index':3},'Vang':{'units':'deg','index':4},
'Vmag':{'units':'pu','index':5},'Vmax':{'units':'pu','index':6},'Vmin':{'units':'pu','index':7}}
gen_meta = {'Pgen':{'units':'MW','index':0},'Qgen':{'units':'MVAR','index':1},'LMP_P':{'units':'USD/kwh','index':2}}
sys_meta = {'Ploss':{'units':'MW','index':0},'Converged':{'units':'true/false','index':1}}
bus_metrics = {'Metadata':bus_meta,'StartTime':StartTime}
gen_metrics = {'Metadata':gen_meta,'StartTime':StartTime}
sys_metrics = {'Metadata':sys_meta,'StartTime':StartTime}
gencost = ppc['gencost']
fncsBus = ppc['FNCS']
gen = ppc['gen']
ppopt_market = pp.ppoption(VERBOSE=0, OUT_ALL=0, PF_DC=ppc['opf_dc'])
ppopt_regular = pp.ppoption(VERBOSE=0, OUT_ALL=0, PF_DC=ppc['pf_dc'])
loads = np.loadtxt(ppc['CSVFile'], delimiter=',')
for row in ppc['UnitsOut']:
print ('unit ', row[0], 'off from', row[1], 'to', row[2], flush=True)
for row in ppc['BranchesOut']:
print ('branch', row[0], 'out from', row[1], 'to', row[2], flush=True)
nloads = loads.shape[0]
ts = 0
tnext_opf = -dt
# initializing for metrics collection
tnext_metrics = 0
loss_accum = 0
conv_accum = True
n_accum = 0
bus_accum = {}
gen_accum = {}
for i in range (fncsBus.shape[0]):
busnum = int(fncsBus[i,0])
bus_accum[str(busnum)] = [0,0,0,0,0,0,0,99999.0]
for i in range (gen.shape[0]):
gen_accum[str(i+1)] = [0,0,0]
op = open (rootname + '.csv', 'w')
print ('t[s],Converged,Pload,P7 (csv),Unresp (opf),P7 (rpf),Resp (opf),GLD Pub,BID?,P7 Min,V7,LMP_P7,LMP_Q7,Pgen1,Pgen2,Pgen3,Pgen4,Pdisp,Deg,c2,c1', file=op, flush=True)
fncs.initialize()
# transactive load components
csv_load = 0 # from the file
unresp = 0 # unresponsive load estimate from the auction agent
resp = 0 # will be the responsive load as dispatched by OPF
resp_deg = 0 # RESPONSIVE_DEG from FNCS
resp_c1 = 0 # RESPONSIVE_C1 from FNCS
resp_c2 = 0 # RESPONSIVE_C2 from FNCS
resp_max = 0 # RESPONSIVE_MAX_MW from FNCS
feeder_load = 0 # amplified feeder MW
while ts <= tmax:
# start by getting the latest inputs from GridLAB-D and the auction
events = fncs.get_events()
new_bid = False
load_scale = float (fncsBus[0][2])
for topic in events:
value = fncs.get_value(topic)
if topic == 'UNRESPONSIVE_MW':
unresp = load_scale * float(value)
fncsBus[0][3] = unresp # to poke unresponsive estimate into the bus load slot
new_bid = True
elif topic == 'RESPONSIVE_MAX_MW':
resp_max = load_scale * float(value)
new_bid = True
elif topic == 'RESPONSIVE_C2':
resp_c2 = float(value) / load_scale
new_bid = True
elif topic == 'RESPONSIVE_C1':
resp_c1 = float(value)
new_bid = True
elif topic == 'RESPONSIVE_DEG':
resp_deg = int(value)
new_bid = True
else:
gld_load = parse_mva (value) # actual value, may not match unresp + resp load
feeder_load = float(gld_load[0]) * load_scale
if new_bid == True:
dummy = 2
# print('**Bid', ts, unresp, resp_max, resp_deg, resp_c2, resp_c1)
# update the case for bids, outages and CSV loads
idx = int ((ts + dt) / period) % nloads
bus = ppc['bus']
gen = ppc['gen']
branch = ppc['branch']
gencost = ppc['gencost']
csv_load = loads[idx,0]
bus[4,2] = loads[idx,1]
bus[8,2] = loads[idx,2]
# process the generator and branch outages
for row in ppc['UnitsOut']:
if ts >= row[1] and ts <= row[2]:
gen[row[0],7] = 0
else:
gen[row[0],7] = 1
for row in ppc['BranchesOut']:
if ts >= row[1] and ts <= row[2]:
branch[row[0],10] = 0
else:
branch[row[0],10] = 1
if resp_deg == 2:
gencost[4][3] = 3
gencost[4][4] = -resp_c2
gencost[4][5] = resp_c1
elif resp_deg == 1:
gencost[4][3] = 2
gencost[4][4] = resp_c1
gencost[4][5] = 0.0
else:
gencost[4][3] = 1
gencost[4][4] = 999.0
gencost[4][5] = 0.0
gencost[4][6] = 0.0
if ts >= tnext_opf: # expecting to solve opf one dt before the market clearing period ends, so GridLAB-D has time to use it
# for OPF, the FNCS bus load is CSV + Unresponsive estimate, with Responsive separately dispatchable
bus = ppc['bus']
gen = ppc['gen']
bus[6,2] = csv_load
for row in ppc['FNCS']:
unresp = float(row[3])
newidx = int(row[0]) - 1
if unresp >= feeder_load:
bus[newidx,2] += unresp
else:
bus[newidx,2] += feeder_load
gen[4][9] = -resp_max
res = pp.runopf(ppc, ppopt_market)
if res['success'] == False:
conv_accum = False
opf_bus = deepcopy (res['bus'])
opf_gen = deepcopy (res['gen'])
lmp = opf_bus[6,13]
resp = -1.0 * opf_gen[4,1]
fncs.publish('LMP_B7', 0.001 * lmp) # publishing $/kwh
# print (' OPF', ts, csv_load, '{:.3f}'.format(unresp), '{:.3f}'.format(resp),
# '{:.3f}'.format(feeder_load), '{:.3f}'.format(opf_bus[6,2]),
# '{:.3f}'.format(opf_gen[0,1]), '{:.3f}'.format(opf_gen[1,1]), '{:.3f}'.format(opf_gen[2,1]),
# '{:.3f}'.format(opf_gen[3,1]), '{:.3f}'.format(opf_gen[4,1]), '{:.3f}'.format(lmp))
# if unit 2 (the normal swing bus) is dispatched at max, change the swing bus to 9
if opf_gen[1,1] >= 191.0:
ppc['bus'][1,1] = 2
ppc['bus'][8,1] = 3
print (' SWING Bus 9')
else:
ppc['bus'][1,1] = 3
ppc['bus'][8,1] = 1
print (' SWING Bus 2')
tnext_opf += period
# always update the electrical quantities with a regular power flow
bus = ppc['bus']
gen = ppc['gen']
bus[6,13] = lmp
gen[0,1] = opf_gen[0, 1]
gen[1,1] = opf_gen[1, 1]
gen[2,1] = opf_gen[2, 1]
gen[3,1] = opf_gen[3, 1]
# during regular power flow, we use the actual CSV + feeder load, ignore dispatchable load and use actual
bus[6,2] = csv_load + feeder_load
gen[4,1] = 0 # opf_gen[4, 1]
gen[4,9] = 0
rpf = pp.runpf(ppc, ppopt_regular)
if rpf[0]['success'] == False:
conv_accum = False
bus = rpf[0]['bus']
gen = rpf[0]['gen']
Pload = bus[:,2].sum()
Pgen = gen[:,1].sum()
Ploss = Pgen - Pload
# update the metrics
n_accum += 1
loss_accum += Ploss
for i in range (fncsBus.shape[0]):
busnum = int(fncsBus[i,0])
busidx = busnum - 1
row = bus[busidx].tolist()
# LMP_P, LMP_Q, PD, QD, Vang, Vmag, Vmax, Vmin: row[11] and row[12] are Vmax and Vmin constraints
PD = row[2] + resp # the ERCOT version shows how to track scaled_resp separately for each FNCS bus
Vpu = row[7]
bus_accum[str(busnum)][0] += row[13]*0.001
bus_accum[str(busnum)][1] += row[14]*0.001
bus_accum[str(busnum)][2] += PD
bus_accum[str(busnum)][3] += row[3]
bus_accum[str(busnum)][4] += row[8]
bus_accum[str(busnum)][5] += Vpu
if Vpu > bus_accum[str(busnum)][6]:
bus_accum[str(busnum)][6] = Vpu
if Vpu < bus_accum[str(busnum)][7]:
bus_accum[str(busnum)][7] = Vpu
for i in range (gen.shape[0]):
row = gen[i].tolist()
busidx = int(row[0] - 1)
# Pgen, Qgen, LMP_P (includes the responsive load as dispatched by OPF)
gen_accum[str(i+1)][0] += row[1]
gen_accum[str(i+1)][1] += row[2]
gen_accum[str(i+1)][2] += float(opf_bus[busidx,13])*0.001
# write the metrics
if ts >= tnext_metrics:
sys_metrics[str(ts)] = {rootname:[loss_accum / n_accum,conv_accum]}
bus_metrics[str(ts)] = {}
for i in range (fncsBus.shape[0]):
busnum = int(fncsBus[i,0])
busidx = busnum - 1
row = bus[busidx].tolist()
met = bus_accum[str(busnum)]
bus_metrics[str(ts)][str(busnum)] = [met[0]/n_accum, met[1]/n_accum, met[2]/n_accum, met[3]/n_accum,
met[4]/n_accum, met[5]/n_accum, met[6], met[7]]
bus_accum[str(busnum)] = [0,0,0,0,0,0,0,99999.0]
gen_metrics[str(ts)] = {}
for i in range (gen.shape[0]):
met = gen_accum[str(i+1)]
gen_metrics[str(ts)][str(i+1)] = [met[0]/n_accum, met[1]/n_accum, met[2]/n_accum]
gen_accum[str(i+1)] = [0,0,0]
tnext_metrics += period
n_accum = 0
loss_accum = 0
conv_accum = True
volts = 1000.0 * bus[6,7] * bus[6,9] / sqrt(3.0) # VLN for GridLAB-D
fncs.publish('three_phase_voltage_B7', volts)
# CSV file output
print (ts, res['success'],
'{:.3f}'.format(Pload), # Pload
'{:.3f}'.format(csv_load), # P7 (csv)
'{:.3f}'.format(unresp), # GLD Unresp
'{:.3f}'.format(bus[6,2]), # P7 (rpf)
'{:.3f}'.format(resp), # Resp (opf)
'{:.3f}'.format(feeder_load), # GLD Pub
new_bid,
'{:.3f}'.format(gen[4,9]), # P7 Min
'{:.3f}'.format(bus[6,7]), # V7
'{:.3f}'.format(bus[6,13]), # LMP_P7
'{:.3f}'.format(bus[6,14]), # LMP_Q7
'{:.2f}'.format(gen[0,1]), # Pgen1
'{:.2f}'.format(gen[1,1]), # Pgen2
'{:.2f}'.format(gen[2,1]), # Pgen3
'{:.2f}'.format(gen[3,1]), # Pgen4
'{:.2f}'.format(res['gen'][4, 1]), # Pdisp
'{:.4f}'.format(resp_deg), # degree
'{:.8f}'.format(ppc['gencost'][4, 4]), # c2
'{:.8f}'.format(ppc['gencost'][4, 5]), # c1
sep=',', file=op, flush=True)
# request the next time step, if necessary
if ts >= tmax:
print ('breaking out at',ts,flush=True)
break
ts = fncs.time_request(min(ts + dt, tmax))
# ===================================
print ('writing metrics', flush=True)
print (json.dumps(sys_metrics), file=sys_mp, flush=True)
print (json.dumps(bus_metrics), file=bus_mp, flush=True)
print (json.dumps(gen_metrics), file=gen_mp, flush=True)
print ('closing files', flush=True)
bus_mp.close()
gen_mp.close()
sys_mp.close()
op.close()
print ('finalizing FNCS', flush=True)
fncs.finalize()
if sys.platform != 'win32':
usage = resource.getrusage(resource.RUSAGE_SELF)
RESOURCES = [
('ru_utime', 'User time'),
('ru_stime', 'System time'),
('ru_maxrss', 'Max. Resident Set Size'),
('ru_ixrss', 'Shared Memory Size'),
('ru_idrss', 'Unshared Memory Size'),
('ru_isrss', 'Stack Size'),
('ru_inblock', 'Block inputs'),
('ru_oublock', 'Block outputs')]
print('Resource usage:')
for name, desc in RESOURCES:
print(' {:<25} ({:<10}) = {}'.format(desc, name, getattr(usage, name)))
def update_plots(self, i):
"""This function is called by Matplotlib for each animation frame
Each time called, collect FNCS messages until the next time to plot
has been reached. Then update the plot quantities and return the
Line2D objects that have been updated for plotting. Check for new
data outside the plotted vertical range, which triggers a full
re-draw of the axes. On the last frame, finalize FNCS.
Args:
i (int): the animation frame number
"""
# print ('.', end='')
# print ('frame', i, 'of', self.nsteps)
bRedraw = False
while self.time_granted < self.time_stop: # time in seconds
# find the time value and index into the time (X) array
self.time_granted = fncs.time_request(self.time_stop)
events = fncs.get_events()
self.root.update()
idx = int(self.time_granted / self.yaml_delta)
if idx <= self.idxlast:
continue
self.idxlast = idx
h = float(self.time_granted / 3600.0)
self.hrs.append(h)
# find the newest Y values
v0 = 0.0
v1 = 0.0
v2auc = 0.0
v2lmp = 0.0
v3 = 0.0
for topic in events:
value = fncs.get_value(topic)
if topic == 'power_A':
v1 = 3.0 * float(value.strip('+ degFkW')) / 1000.0
elif topic == 'distribution_load':
v3 = helpers.parse_kw(value)
self.gld_load = v3
elif topic == 'vpos7':
v0 = float(value.strip('+ degFkW')) / 133000.0
elif topic == 'clear_price':
v2auc = float(value.strip('+ degFkW'))
elif topic == 'LMP7':
v2lmp = float(value.strip('+ degFkW'))
elif topic == 'SUBSTATION7':
v1 = float(value.strip('+ degFkW')) # already in kW
# expand the Y axis limits if necessary, keeping a 10% padding around the range
if v0 < self.y0min or v0 > self.y0max:
self.y0min, self.y0max = self.expand_limits(
v0, self.y0min, self.y0max)
self.ax[0].set_ylim(self.y0min, self.y0max)
bRedraw = True
if v1 < self.y1min or v1 > self.y1max:
self.y1min, self.y1max = self.expand_limits(
v1, self.y1min, self.y1max)
self.ax[1].set_ylim(self.y1min, self.y1max)
bRedraw = True
if v2auc > v2lmp:
v2max = v2auc
v2min = v2lmp
else:
v2max = v2lmp
v2min = v2auc
if v2min < self.y2min or v2max > self.y2max:
self.y2min, self.y2max = self.expand_limits(
v2min, self.y2min, self.y2max)
self.y2min, self.y2max = self.expand_limits(
v2max, self.y2min, self.y2max)
self.ax[2].set_ylim(self.y2min, self.y2max)
bRedraw = True
if v3 < self.y3min or v3 > self.y3max:
self.y3min, self.y3max = self.expand_limits(
v3, self.y3min, self.y3max)
self.ax[3].set_ylim(self.y3min, self.y3max)
bRedraw = True
# update the Y axis data to draw
self.y0.append(v0) # Vpu
self.y1.append(v1) # school kW
self.y2auc.append(v2auc) # price
self.y2lmp.append(v2lmp) # LMP
self.y3fncs.append(
v3) # this feeder load from FNCS (could be zero if no update)
self.y3gld.append(
self.gld_load) # most recent feeder load from FNCS
self.ln0.set_data(self.hrs, self.y0)
self.ln1.set_data(self.hrs, self.y1)
self.ln2auc.set_data(self.hrs, self.y2auc)
self.ln2lmp.set_data(self.hrs, self.y2lmp)
self.ln3fncs.set_data(self.hrs, self.y3fncs)
self.ln3gld.set_data(self.hrs, self.y3gld)
if bRedraw:
# print ('redrawing axes')
self.fig.canvas.draw()
if i >= (self.nsteps - 1):
print('finalizing FNCS')
fncs.finalize()
print('FNCS active to False')
self.bFNCSactive = False
return self.ln0, self.ln1, self.ln2auc, self.ln2lmp, self.ln3fncs, self.ln3gld,
print('not finalizing FNCS')
return self.ln0, self.ln1, self.ln2auc, self.ln2lmp, self.ln3fncs, self.ln3gld, # in case we miss the last point
met = gen_accum[str(i + 1)]
gen_metrics[str(ts)][str(i + 1)] = [
met[0] / n_accum, met[1] / n_accum, met[2] / n_accum
]
gen_accum[str(i + 1)] = [0, 0, 0]
tnext_metrics += period
n_accum = 0
loss_accum = 0
conv_accum = True
# request the next time step, if necessary
if ts >= tmax:
print('breaking out at', ts, flush=True)
break
ts = fncs.time_request(min(ts + dt, tmax))
# ======================================================
print('writing metrics', flush=True)
print(json.dumps(sys_metrics), file=sys_mp, flush=True)
print(json.dumps(bus_metrics), file=bus_mp, flush=True)
print(json.dumps(gen_metrics), file=gen_mp, flush=True)
print('closing files', flush=True)
bus_mp.close()
gen_mp.close()
sys_mp.close()
op.close()
vp.close()
print('finalizing FNCS', flush=True)
fncs.finalize()
def update_plots(self, i):
print ('.', end='')
# print ('frame', i, 'of', self.nsteps)
bRedraw = False
while self.time_granted < self.time_stop: # time in minutes
self.time_granted = fncs.time_request(self.time_stop)
events = fncs.get_events()
self.root.update()
idx = int (self.time_granted / self.yaml_delta)
if idx <= self.idxlast:
continue
self.idxlast = idx
v0 = 0.0
v1 = 0.0
v2 = 0.0
v3 = 0.0
for topic in events:
value = fncs.get_value(topic)
if topic == 'power_A':
v1 = 3.0 * float (value.strip('+ degFkW')) / 1000.0
elif topic == 'distribution_load':
v3 = simple_auction.parse_kw (value)
elif topic == 'vpos7':
v0 = float (value.strip('+ degFkW')) / 133000.0
elif topic == 'clear_price':
v2 = float (value.strip('+ degFkW'))
elif topic == 'LMP7':
v2 = float (value.strip('+ degFkW'))
elif topic == 'SUBSTATION7':
v1 = float (value.strip('+ degFkW')) # already in kW
retval = [self.ln0, self.ln1, self.ln2, self.ln3]
h = float (self.time_granted / 60.0)
self.hrs.append (h)
if v0 < self.y0min or v0 > self.y0max:
if v0 < self.y0min:
self.y0min = v0
if v0 > self.y0max:
self.y0max = v0
self.ax[0].set_ylim (self.y0min, self.y0max)
bRedraw = True
if v1 < self.y1min or v1 > self.y1max:
if v1 < self.y1min:
self.y1min = v1
if v1 > self.y1max:
self.y1max = v1
self.ax[1].set_ylim (self.y1min, self.y1max)
bRedraw = True
if v2 < self.y2min or v2 > self.y2max:
if v2 < self.y2min:
self.y2min = v2
if v2 > self.y2max:
self.y2max = v2
self.ax[2].set_ylim (self.y2min, self.y2max)
bRedraw = True
if v3 < self.y3min or v3 > self.y3max:
if v3 < self.y3min:
self.y3min = v3
if v3 > self.y3max:
self.y3max = v3
self.ax[3].set_ylim (self.y3min, self.y3max)
bRedraw = True
self.y0.append (v0) # Vpu
self.y1.append (v1) # school kW
self.y2.append (v2) # price
self.y3.append (v3) # feeder load
self.ln0.set_data (self.hrs, self.y0)
self.ln1.set_data (self.hrs, self.y1)
self.ln2.set_data (self.hrs, self.y2)
self.ln3.set_data (self.hrs, self.y3)
if bRedraw:
self.fig.canvas.draw()
if i >= (self.nsteps - 1):
fncs.finalize()
self.bFNCSactive = False
return retval
def Quit(self):
self.root.quit()
self.root.destroy()
if self.bFNCSactive:
fncs.finalize()
self.bFNCSactive = False
def precool_loop(nhours, metrics_root):
time_stop = int(3600 * nhours)
lp = open(metrics_root + "_agent_dict.json").read()
dict = json.loads(lp)
precool_meta = {
'temperature_deviation_min': {
'units': 'degF',
'index': 0
},
'temperature_deviation_max': {
'units': 'degF',
'index': 1
},
'temperature_deviation_avg': {
'units': 'degF',
'index': 2
}
}
StartTime = "2013-07-01 00:00:00 PST"
precool_metrics = {'Metadata': precool_meta, 'StartTime': StartTime}
dt = dict['dt']
mean = dict['mean']
stddev = dict['stddev']
period = dict['period']
k = dict['k_slope']
print('run till', time_stop, 'period', period, 'step', dt, 'mean', mean,
'stddev', stddev, 'k_slope', k)
fncs.initialize()
time_granted = 0
price = 0.11 # mean
# time_next = dt
voltages = {}
temperatures = {}
setpoints = {} # publish a new one only if changed
lastchange = {}
precooling_quiet = 4 * 3600
precooling_off = 25 * 3600 # never turns off
precooling_status = {}
lockout_period = 360
bSetDeadbands = True
nPrecoolers = 0
while time_granted < time_stop:
time_granted = fncs.time_request(time_stop) # time_next
hour_of_day = 24.0 * ((float(time_granted) / 86400.0) % 1.0)
events = fncs.get_events()
for topic in events:
value = fncs.get_value(topic)
if topic == 'price':
price = float(value)
else:
pair = topic.split('#')
houseName = pair[0]
if pair[1] == 'V1':
voltages[houseName] = parse_fncs_magnitude(value)
elif pair[1] == 'Tair':
temperatures[houseName] = parse_fncs_magnitude(value)
if bSetDeadbands:
bSetDeadbands = False
print('setting thermostat deadbands and heating setpoints at',
time_granted)
# set all of the house deadbands and initial setpoints
for house, row in dict['houses'].items():
topic = house + '_thermostat_deadband'
value = row['deadband']
fncs.publish(topic, value)
setpoints[house] = 0.0
lastchange[house] = -lockout_period
precooling_status[house] = False
fncs.publish(house + '_heating_setpoint', 60.0)
# update all of the house setpoints
count_temp_dev = 0
sum_temp_dev = 0.0
min_temp_dev = 10000.0
max_temp_dev = 0.0
for house, row in dict['houses'].items():
# time-scheduled setpoints
if hour_of_day >= row['day_start_hour'] and hour_of_day <= row[
'day_end_hour']:
value = row['day_set']
else:
value = row['night_set']
# comfort metrics
if house in temperatures:
temp_dev = abs(temperatures[house] - value)
if temp_dev < min_temp_dev:
min_temp_dev = temp_dev
if temp_dev > max_temp_dev:
max_temp_dev = temp_dev
sum_temp_dev += temp_dev
count_temp_dev += 1
# time-of-day price response
tdelta = (price - mean) * row['deadband'] / k / stddev
value += tdelta
# overvoltage checks
if time_granted >= precooling_quiet and not precooling_status[
house]:
if house in voltages:
if voltages[house] > row['vthresh']:
precooling_status[house] = True
nPrecoolers += 1
elif time_granted >= precooling_off:
precooling_status[house] = False
# overvoltage response
if precooling_status[house]:
value += row['toffset']
if abs(value - setpoints[house]) > 0.1:
if (time_granted - lastchange[house]) > lockout_period:
topic = house + '_cooling_setpoint'
fncs.publish(topic, value)
setpoints[house] = value
lastchange[house] = time_granted
print('setting', house, 'to', value, 'at', time_granted,
'precooling', precooling_status[house])
if count_temp_dev < 1:
count_temp_dev = 1
min_temp_dev = 0.0
precool_metrics[str(time_granted)] = [
min_temp_dev, max_temp_dev, sum_temp_dev / count_temp_dev
]
time_next = time_granted + dt
print(nPrecoolers, 'houses participated in precooling')
print('writing metrics', flush=True)
mp = open("precool_" + metrics_root + "_metrics.json", "w")
print(json.dumps(precool_metrics), file=mp)
mp.close()
print('done', flush=True)
print('finalizing FNCS', flush=True)
fncs.finalize()
if sys.platform != 'win32':
usage = resource.getrusage(resource.RUSAGE_SELF)
RESOURCES = [('ru_utime', 'User time'), ('ru_stime', 'System time'),
('ru_maxrss', 'Max. Resident Set Size'),
('ru_ixrss', 'Shared Memory Size'),
('ru_idrss', 'Unshared Memory Size'),
('ru_isrss', 'Stack Size'),
('ru_inblock', 'Block inputs'),
('ru_oublock', 'Block outputs')]
print('Resource usage:')
for name, desc in RESOURCES:
print(' {:<25} ({:<10}) = {}'.format(desc, name,
getattr(usage, name)))
def auction_loop (configfile, metrics_root, flag='WithMarket'):
bWantMarket = True
if flag == 'NoMarket':
bWantMarket = False
print ('Disabled the market', flush=True)
time_stop = int (48 * 3600) # simulation time in seconds
StartTime = '2013-07-01 00:00:00 -0800'
time_fmt = '%Y-%m-%d %H:%M:%S %z'
dt_now = datetime.strptime (StartTime, time_fmt)
# ====== load the JSON dictionary; create the corresponding objects =========
lp = open (configfile).read()
dict = json.loads(lp)
market_key = list(dict['markets'].keys())[0] # TODO: only using the first market
market_row = dict['markets'][market_key]
unit = market_row['unit']
auction_meta = {'clearing_price':{'units':'USD','index':0},'clearing_type':{'units':'[0..5]=[Null,Fail,Price,Exact,Seller,Buyer]','index':1}}
controller_meta = {'bid_price':{'units':'USD','index':0},'bid_quantity':{'units':unit,'index':1}}
auction_metrics = {'Metadata':auction_meta,'StartTime':StartTime}
controller_metrics = {'Metadata':controller_meta,'StartTime':StartTime}
aucObj = simple_auction.simple_auction (market_row, market_key)
dt = float(dict['dt'])
period = aucObj.period
topicMap = {} # to dispatch incoming FNCS messages; 0..5 for LMP, Feeder load, airtemp, mtr volts, hvac load, hvac state
topicMap['LMP'] = [aucObj, 0]
topicMap['refload'] = [aucObj, 1]
hvacObjs = {}
hvac_keys = list(dict['controllers'].keys())
for key in hvac_keys:
row = dict['controllers'][key]
hvacObjs[key] = simple_auction.hvac (row, key, aucObj)
ctl = hvacObjs[key]
topicMap[key + '#Tair'] = [ctl, 2]
topicMap[key + '#V1'] = [ctl, 3]
topicMap[key + '#Load'] = [ctl, 4]
topicMap[key + '#On'] = [ctl, 5]
# ==================== Time step looping under FNCS ===========================
fncs.initialize()
aucObj.initAuction()
LMP = aucObj.mean
refload = 0.0
bSetDefaults = True
tnext_bid = period - 2 * dt #3 * dt # controllers calculate their final bids
tnext_agg = period - 2 * dt # auction calculates and publishes aggregate bid
tnext_opf = period - 1 * dt # PYPOWER executes OPF and publishes LMP (no action here)
tnext_clear = period # clear the market with LMP
tnext_adjust = period # + dt # controllers adjust setpoints based on their bid and clearing
time_granted = 0
time_last = 0
while (time_granted < time_stop):
time_granted = fncs.time_request(time_stop)
time_delta = time_granted - time_last
time_last = time_granted
hour_of_day = 24.0 * ((float(time_granted) / 86400.0) % 1.0)
# TODO - getting an overflow error when killing process - investigate whether that happens if simulation runs to completion
# print (dt_now, time_delta, timedelta (seconds=time_delta))
dt_now = dt_now + timedelta (seconds=time_delta)
day_of_week = dt_now.weekday()
hour_of_day = dt_now.hour
print (' ', time_last, time_granted, time_stop, time_delta, hour_of_day, day_of_week, flush=True)
# update the data from FNCS messages
events = fncs.get_events()
for key in events:
topic = key.decode()
value = fncs.get_value(key).decode()
row = topicMap[topic]
if row[1] == 0:
LMP = simple_auction.parse_fncs_magnitude (value)
aucObj.set_lmp (LMP)
elif row[1] == 1:
refload = simple_auction.parse_kw (value)
aucObj.set_refload (refload)
elif row[1] == 2:
row[0].set_air_temp (value)
elif row[1] == 3:
row[0].set_voltage (value)
elif row[1] == 4:
row[0].set_hvac_load (value)
elif row[1] == 5:
row[0].set_hvac_state (value)
# set the time-of-day schedule
for key, obj in hvacObjs.items():
if obj.change_basepoint (hour_of_day, day_of_week):
fncs.publish (obj.name + '/cooling_setpoint', obj.basepoint)
if bSetDefaults:
for key, obj in hvacObjs.items():
fncs.publish (obj.name + '/bill_mode', 'HOURLY')
fncs.publish (obj.name + '/monthly_fee', 0.0)
fncs.publish (obj.name + '/thermostat_deadband', obj.deadband)
fncs.publish (obj.name + '/heating_setpoint', 60.0)
bSetDefaults = False
if time_granted >= tnext_bid:
print ('**', tnext_clear, flush=True)
aucObj.clear_bids()
time_key = str (int (tnext_clear))
controller_metrics [time_key] = {}
for key, obj in hvacObjs.items():
bid = obj.formulate_bid () # bid is [price, quantity, on_state]
if bWantMarket:
aucObj.collect_bid (bid)
controller_metrics[time_key][obj.name] = [bid[0], bid[1]]
tnext_bid += period
if time_granted >= tnext_agg:
aucObj.aggregate_bids()
fncs.publish ('unresponsive_mw', aucObj.agg_unresp)
fncs.publish ('responsive_max_mw', aucObj.agg_resp_max)
fncs.publish ('responsive_c2', aucObj.agg_c2)
fncs.publish ('responsive_c1', aucObj.agg_c1)
fncs.publish ('responsive_deg', aucObj.agg_deg)
tnext_agg += period
if time_granted >= tnext_clear:
if bWantMarket:
aucObj.clear_market()
fncs.publish ('clear_price', aucObj.clearing_price)
for key, obj in hvacObjs.items():
obj.inform_bid (aucObj.clearing_price)
time_key = str (int (tnext_clear))
auction_metrics [time_key] = {aucObj.name:[aucObj.clearing_price, aucObj.clearing_type]}
tnext_clear += period
if time_granted >= tnext_adjust:
if bWantMarket:
for key, obj in hvacObjs.items():
fncs.publish (obj.name + '/price', aucObj.clearing_price)
if obj.bid_accepted ():
fncs.publish (obj.name + '/cooling_setpoint', obj.setpoint)
tnext_adjust += period
# ==================== Finalize the metrics output ===========================
print ('writing metrics', flush=True)
auction_op = open ('auction_' + metrics_root + '_metrics.json', 'w')
controller_op = open ('controller_' + metrics_root + '_metrics.json', 'w')
print (json.dumps(auction_metrics), file=auction_op)
print (json.dumps(controller_metrics), file=controller_op)
auction_op.close()
controller_op.close()
print ('finalizing FNCS', flush=True)
fncs.finalize()
def update_plots(self, i):
"""This function is called by Matplotlib for each animation frame
Each time called, collect FNCS messages until the next time to plot
has been reached. Then update the plot quantities and return the
Line2D objects that have been updated for plotting. Check for new
data outside the plotted vertical range, which triggers a full
re-draw of the axes. On the last frame, finalize FNCS.
Args:
i (int): the animation frame number
"""
print('.', end='')
# print ('frame', i, 'of', self.nsteps)
bRedraw = False
while self.time_granted < self.time_stop: # time in minutes
self.time_granted = fncs.time_request(self.time_stop)
events = fncs.get_events()
self.root.update()
idx = int(self.time_granted / self.yaml_delta)
if idx <= self.idxlast:
continue
self.idxlast = idx
v0 = 0.0
v1 = 0.0
v2 = 0.0
v3 = 0.0
# for topic in events:
# value = fncs.get_value(topic)
# # if topic == 'vpos8':
# # v1 = float (value.strip('+ degFkW')) / 199185.0
# if topic == 'vpos1':
# v1 = float(value.strip('+ degFkW')) / 199185.0
# elif topic == 'distribution_load8':
# v3 = helpers.parse_kw (value)
# elif topic == 'vpos8':
# v0 = float (value.strip('+ degFkW')) / 199185.0
# # elif topic == 'clear_price':
# # v2 = float (value.strip('+ degFkW'))
# elif topic == 'LMP8':
# v2 = float (value.strip('+ degFkW'))
# # elif topic == 'SUBSTATION7':
# # v1 = float (value.strip('+ degFkW')) # already in kW
for topic in events:
value = fncs.get_value(topic)
if topic == self.topicDict[self.plot0.title.get()]:
v0 = self.CalculateValue(topic, value, self.plot0)
elif topic == self.topicDict[self.plot1.title.get()]:
v1 = self.CalculateValue(topic, value, self.plot1)
elif topic == self.topicDict[self.plot2.title.get()]:
v2 = self.CalculateValue(topic, value, self.plot2)
elif topic == self.topicDict[self.plot3.title.get()]:
v3 = self.CalculateValue(topic, value, self.plot3)
retval = [
self.plot0.ln, self.plot1.ln, self.plot2.ln, self.plot3.ln
]
h = float(self.time_granted / 3600.0)
self.plot0.hrs.append(h)
self.plot1.hrs.append(h)
self.plot2.hrs.append(h)
self.plot3.hrs.append(h)
self.plot0.y.append(v0) # Vpu
self.plot1.y.append(v1) # school kW
self.plot2.y.append(v2) # price
self.plot3.y.append(v3) # feeder load
self.plot0.ln.set_data(self.plot0.hrs, self.plot0.y)
self.plot1.ln.set_data(self.plot1.hrs, self.plot1.y)
self.plot2.ln.set_data(self.plot2.hrs, self.plot2.y)
self.plot3.ln.set_data(self.plot3.hrs, self.plot3.y)
if len(self.plot0.y) == 2:
diff = abs(self.plot0.y[0] - self.plot0.y[1])
if diff == 0:
self.plot0.ymin = self.plot0.y[0] - 0.00001
self.plot0.ymax = self.plot0.y[0] + 0.00001
else:
self.plot0.ymin = min(self.plot0.y) - 0.00001 * diff
self.plot0.ymax = max(self.plot0.y) + 0.00001 * diff
if self.plot0.ymin < 0:
self.plot0.ymin = 0
self.plot0.ax.set_ylim(self.plot0.ymin, self.plot0.ymax)
self.plot0.fig.canvas.draw()
diff = abs(self.plot1.y[0] - self.plot1.y[1])
if diff == 0:
self.plot1.ymin = self.plot1.y[0] - 0.00001
self.plot1.ymax = self.plot1.y[0] + 0.00001
else:
self.plot1.ymin = min(self.plot1.y) - 0.00001 * diff
self.plot1.ymax = max(self.plot1.y) + 0.00001 * diff
if self.plot1.ymin < 0:
self.plot1.ymin = 0
self.plot1.ax.set_ylim(self.plot1.ymin, self.plot1.ymax)
self.plot1.fig.canvas.draw()
diff = abs(self.plot2.y[0] - self.plot2.y[1])
if diff == 0:
self.plot2.ymin = self.plot2.y[0] - 0.00001
self.plot2.ymax = self.plot2.y[0] + 0.00001
else:
self.plot2.ymin = min(self.plot2.y) - 0.00001 * diff
self.plot2.ymax = max(self.plot2.y) + 0.00001 * diff
if self.plot2.ymin < 0:
self.plot2.ymin = 0
self.plot2.ax.set_ylim(self.plot2.ymin, self.plot2.ymax)
self.plot2.fig.canvas.draw()
diff = abs(self.plot3.y[0] - self.plot3.y[1])
if diff == 0:
self.plot3.ymin = self.plot3.y[0] - 0.00001
self.plot3.ymax = self.plot3.y[0] + 0.00001
else:
self.plot3.ymin = min(self.plot3.y) - 0.00001 * diff
self.plot3.ymax = max(self.plot3.y) + 0.00001 * diff
if self.plot3.ymin < 0:
self.plot3.ymin = 0
self.plot3.ax.set_ylim(self.plot3.ymin, self.plot3.ymax)
self.plot3.fig.canvas.draw()
else:
if v0 < self.plot0.ymin or v0 > self.plot0.ymax:
if v0 < self.plot0.ymin:
self.plot0.ymin = v0
if v0 > self.plot0.ymax:
self.plot0.ymax = v0
self.plot0.ax.set_ylim(self.plot0.ymin, self.plot0.ymax)
self.plot0.fig.canvas.draw()
if v1 < self.plot1.ymin or v1 > self.plot1.ymax:
if v1 < self.plot1.ymin:
self.plot1.ymin = v1
if v1 > self.plot1.ymax:
self.plot1.ymax = v1
self.plot1.ax.set_ylim(self.plot1.ymin, self.plot1.ymax)
self.plot1.fig.canvas.draw()
if v2 < self.plot2.ymin or v2 > self.plot2.ymax:
if v2 < self.plot2.ymin:
self.plot2.ymin = v2
if v2 > self.plot2.ymax:
self.plot2.ymax = v2
self.plot2.ax.set_ylim(self.plot2.ymin, self.plot2.ymax)
self.plot2.fig.canvas.draw()
if v3 < self.plot3.ymin or v3 > self.plot3.ymax:
if v3 < self.plot3.ymin:
self.plot3.ymin = v3
if v3 > self.plot3.ymax:
self.plot3.ymax = v3
self.plot3.ax.set_ylim(self.plot3.ymin, self.plot3.ymax)
self.plot3.fig.canvas.draw()
# if bRedraw:
# self.plot0.fig.canvas.draw()
# self.plot1.fig.canvas.draw()
# self.plot2.fig.canvas.draw()
# self.plot3.fig.canvas.draw()
if i >= (self.nsteps - 1):
fncs.finalize()
self.bFNCSactive = False
return retval
def update_plots(self, i):
print('.', end='')
# print ('frame', i, 'of', self.nsteps)
bRedraw = False
while self.time_granted < self.time_stop: # time in minutes
self.time_granted = fncs.time_request(self.time_stop)
events = fncs.get_events()
self.root.update()
idx = int(self.time_granted / self.yaml_delta)
if idx <= self.idxlast:
continue
self.idxlast = idx
v0 = 0.0
v1 = 0.0
v2 = 0.0
v3 = 0.0
# for topic in events:
# value = fncs.get_value(topic)
# # if topic == 'vpos8':
# # v1 = float (value.strip('+ degFkW')) / 199185.0
# if topic == 'vpos1':
# v1 = float(value.strip('+ degFkW')) / 199185.0
# elif topic == 'distribution_load8':
# v3 = simple_auction.parse_kw (value)
# elif topic == 'vpos8':
# v0 = float (value.strip('+ degFkW')) / 199185.0
# # elif topic == 'clear_price':
# # v2 = float (value.strip('+ degFkW'))
# elif topic == 'LMP8':
# v2 = float (value.strip('+ degFkW'))
# # elif topic == 'SUBSTATION7':
# # v1 = float (value.strip('+ degFkW')) # already in kW
for topic in events:
value = fncs.get_value(topic)
if topic == self.topicDict[self.plot0.title.get()]:
v0 = self.CalculateValue(topic, value, self.plot0)
elif topic == self.topicDict[self.plot1.title.get()]:
v1 = self.CalculateValue(topic, value, self.plot1)
elif topic == self.topicDict[self.plot2.title.get()]:
v2 = self.CalculateValue(topic, value, self.plot2)
elif topic == self.topicDict[self.plot3.title.get()]:
v3 = self.CalculateValue(topic, value, self.plot3)
retval = [self.plot0.ln, self.plot1.ln, self.plot2.ln, self.plot3.ln]
h = float(self.time_granted / 3600.0)
self.plot0.hrs.append(h)
self.plot1.hrs.append(h)
self.plot2.hrs.append(h)
self.plot3.hrs.append(h)
self.plot0.y.append(v0) # Vpu
self.plot1.y.append(v1) # school kW
self.plot2.y.append(v2) # price
self.plot3.y.append(v3) # feeder load
self.plot0.ln.set_data(self.plot0.hrs, self.plot0.y)
self.plot1.ln.set_data(self.plot1.hrs, self.plot1.y)
self.plot2.ln.set_data(self.plot2.hrs, self.plot2.y)
self.plot3.ln.set_data(self.plot3.hrs, self.plot3.y)
if len(self.plot0.y) == 2:
diff = abs(self.plot0.y[0] - self.plot0.y[1])
if diff == 0:
self.plot0.ymin = self.plot0.y[0] - 0.00001
self.plot0.ymax = self.plot0.y[0] + 0.00001
else:
self.plot0.ymin = min(self.plot0.y) - 0.00001 * diff
self.plot0.ymax = max(self.plot0.y) + 0.00001 * diff
if self.plot0.ymin < 0:
self.plot0.ymin = 0
self.plot0.ax.set_ylim(self.plot0.ymin, self.plot0.ymax)
self.plot0.fig.canvas.draw()
diff = abs(self.plot1.y[0] - self.plot1.y[1])
if diff == 0:
self.plot1.ymin = self.plot1.y[0] - 0.00001
self.plot1.ymax = self.plot1.y[0] + 0.00001
else:
self.plot1.ymin = min(self.plot1.y) - 0.00001 * diff
self.plot1.ymax = max(self.plot1.y) + 0.00001 * diff
if self.plot1.ymin < 0:
self.plot1.ymin = 0
self.plot1.ax.set_ylim(self.plot1.ymin, self.plot1.ymax)
self.plot1.fig.canvas.draw()
diff = abs(self.plot2.y[0] - self.plot2.y[1])
if diff == 0:
self.plot2.ymin = self.plot2.y[0] - 0.00001
self.plot2.ymax = self.plot2.y[0] + 0.00001
else:
self.plot2.ymin = min(self.plot2.y) - 0.00001 * diff
self.plot2.ymax = max(self.plot2.y) + 0.00001 * diff
if self.plot2.ymin < 0:
self.plot2.ymin = 0
self.plot2.ax.set_ylim(self.plot2.ymin, self.plot2.ymax)
self.plot2.fig.canvas.draw()
diff = abs(self.plot3.y[0] - self.plot3.y[1])
if diff == 0:
self.plot3.ymin = self.plot3.y[0] - 0.00001
self.plot3.ymax = self.plot3.y[0] + 0.00001
else:
self.plot3.ymin = min(self.plot3.y) - 0.00001 * diff
self.plot3.ymax = max(self.plot3.y) + 0.00001 * diff
if self.plot3.ymin < 0:
self.plot3.ymin = 0
self.plot3.ax.set_ylim(self.plot3.ymin, self.plot3.ymax)
self.plot3.fig.canvas.draw()
else:
if v0 < self.plot0.ymin or v0 > self.plot0.ymax:
if v0 < self.plot0.ymin:
self.plot0.ymin = v0
if v0 > self.plot0.ymax:
self.plot0.ymax = v0
self.plot0.ax.set_ylim(self.plot0.ymin, self.plot0.ymax)
self.plot0.fig.canvas.draw()
if v1 < self.plot1.ymin or v1 > self.plot1.ymax:
if v1 < self.plot1.ymin:
self.plot1.ymin = v1
if v1 > self.plot1.ymax:
self.plot1.ymax = v1
self.plot1.ax.set_ylim(self.plot1.ymin, self.plot1.ymax)
self.plot1.fig.canvas.draw()
if v2 < self.plot2.ymin or v2 > self.plot2.ymax:
if v2 < self.plot2.ymin:
self.plot2.ymin = v2
if v2 > self.plot2.ymax:
self.plot2.ymax = v2
self.plot2.ax.set_ylim(self.plot2.ymin, self.plot2.ymax)
self.plot2.fig.canvas.draw()
if v3 < self.plot3.ymin or v3 > self.plot3.ymax:
if v3 < self.plot3.ymin:
self.plot3.ymin = v3
if v3 > self.plot3.ymax:
self.plot3.ymax = v3
self.plot3.ax.set_ylim(self.plot3.ymin, self.plot3.ymax)
self.plot3.fig.canvas.draw()
# if bRedraw:
# self.plot0.fig.canvas.draw()
# self.plot1.fig.canvas.draw()
# self.plot2.fig.canvas.draw()
# self.plot3.fig.canvas.draw()
if i >= (self.nsteps - 1):
fncs.finalize()
self.bFNCSactive = False
return retval
def launch_all(self):
print('launching all simulators')
self.pids = []
for row in self.commands:
procargs = row['args']
procenv = os.environ.copy()
for var in row['env']:
procenv[var[0]] = var[1]
logfd = None
if 'log' in row:
logfd = open(row['log'], 'w')
# print ('*******************************************************')
# print (procargs, procenv)
proc = subprocess.Popen(procargs, env=procenv, stdout=logfd)
self.pids.append(proc)
# print ('*******************************************************')
print('launched', len(self.pids), 'simulators') # , self.pids)
self.root.update()
# print ('root update')
fncs.initialize()
print('FNCS initialized')
time_granted = 0
nsteps = int(self.time_stop / self.yaml_delta)
# plt.xlim(0.0, self.hour_stop)
hrs = np.linspace(0.0, self.hour_stop, nsteps + 1)
print('time_stop, hour_stop and nsteps =', self.time_stop,
self.hour_stop, nsteps)
idxlast = -1
x0 = np.empty(nsteps + 1)
x1 = np.zeros(nsteps + 1)
x2 = np.zeros(nsteps + 1)
x3 = np.zeros(nsteps + 1)
while time_granted < self.time_stop:
time_granted = fncs.time_request(self.time_stop)
events = fncs.get_events()
idx = int(time_granted / self.yaml_delta)
if idx <= idxlast:
continue
idxlast = idx
bWantX0 = True # pu volts
bWantX1 = True # school load
bWantX2 = True # prices
bWantX3 = True # total feeder load
for key in events:
tok = key.decode()
if bWantX1 and tok == 'power_A':
val = 3.0 * float(
fncs.get_value(key).decode().strip(
'+ degFkW')) / 1000.0
x1[idx] = val
self.ax[1].plot(hrs[1:idx], x1[1:idx], color='red')
bWantX1 = False
elif bWantX3 and tok == 'distribution_load':
val = simple_auction.parse_kw(fncs.get_value(key).decode())
x3[idx] = val
self.ax[3].plot(hrs[1:idx], x3[1:idx], color='magenta')
bWantX3 = False
elif bWantX0 and tok == 'vpos7':
val = float(
fncs.get_value(key).decode().strip(
'+ degFkW')) / 133000.0
x0[idx] = val
self.ax[0].plot(hrs[1:idx], x0[1:idx], color='green')
bWantX0 = False
elif bWantX2 and tok == 'clear_price':
val = float(fncs.get_value(key).decode().strip('+ degFkW'))
x2[idx] = val
self.ax[2].plot(hrs[1:idx], x2[1:idx], color='blue')
bWantX2 = False
elif bWantX2 and tok == 'LMP7':
val = float(fncs.get_value(key).decode().strip('+ degFkW'))
x2[idx] = val
self.ax[2].plot(hrs[1:idx], x2[1:idx], color='blue')
bWantX2 = False
elif bWantX1 and tok == 'SUBSTATION7':
val = float(
fncs.get_value(key).decode().strip(
'+ degFkW')) # already in kW
x1[idx] = val
self.ax[1].plot(hrs[1:idx], x1[1:idx], color='red')
bWantX1 = False
# print (time_granted, key.decode(), fncs.get_value(key).decode())
self.root.update()
self.fig.canvas.draw()
fncs.finalize()
