def update_consumption(run, simulation):
start_time = time.time()
print("Run choice: {}".format(run))
print("Simulation choice: {}".format(simulation))
contracts, profiles = dataprocess.open_file(simulation)
contracts, profiles = contracts[int(run) - 1], profiles[int(run) - 1]
profiles = dataprocess.neighbourhood_execution_energy_over_time(
contracts, profiles)
end_time = time.time()
print("Time elapsed: {}".format(end_time - start_time))
return go.Figure(data=[
go.Scatter(x=profiles[0],
y=profiles[1],
name="Energy consumed locally",
marker=dict(color="#00A6FC")),
go.Scatter(x=profiles[2],
y=profiles[3],
name="Energy consumed remotely",
marker=dict(color="#FF0000")),
go.Scatter(x=profiles[4],
y=profiles[5],
name="Energy produced",
marker=dict(color="#008000")),
],
layout=go.Layout(
xaxis={"title": "Time [Minutes]"},
yaxis={"title": "Energy [Wh per minute]"}))
def update_peak_av_ratio_single_house(household, interval, simulation, run):
contracts, profiles = dataprocess.open_file(simulation)
contracts = contracts[int(run) - 1]
contracts_for_house = dataprocess.get_contracts_for_house(
household, contracts)
par = dataprocess.peak_to_average_ratio_consumption(
contracts_for_house, int(interval))
return html.P("Consumed peak to average ratio: {}".format(round(par, 2)))
def update_peak_av_ratio(run, interval, simulation):
if interval in [None, ""]:
return html.P("Not a valid interval")
contracts, profiles = dataprocess.open_file(simulation)
contracts = contracts[int(run) - 1]
par = dataprocess.peak_to_average_ratio_consumption(
contracts, int(interval))
return html.P("Consumed peak to average ratio: {}".format(round(par, 2)))
def self_consumption_all(run, simulation):
contracts = dataprocess.open_file(simulation)[0]
contracts = contracts[int(run) - 1]
grid = 0
pv = 0
for contract in contracts:
if contract.get("producer_id") == "grid":
grid += contract.get("load_profile").values[-1]
else:
pv += contract.get("load_profile").values[-1]
return html.P("Total consumption for whole neighbourhood: {}".format(
round(grid + pv, 2)))
def update_pie_chart_header(household, simulation, run):
contracts = dataprocess.open_file(simulation)[0]
contracts = contracts[int(run) - 1]
grid = 0
pv = 0
for contract in contracts:
if contract.get("job_id").startswith("[{}]".format(household)):
if contract.get("producer_id") == "grid":
grid += contract.get("load_profile").values[-1]
else:
pv += contract.get("load_profile").values[-1]
return html.P("Total consumption for household: {}".format(
round(grid + pv, 2)))
def update_contracts(run, simulation):
contracts = dataprocess.open_file(simulation)[0]
contracts = contracts[int(run) - 1]
rows = []
for contract in contracts:
contract["load_profile"] = round(contract["load_profile"].values[-1],
2)
contract["time"] = dataprocess.convert(contract["time"])
contract["time_of_agreement"] = dataprocess.convert(
contract["time_of_agreement"])
contract = dataprocess.rename_columns(contract)
rows.append(contract)
return rows
def update_contracts(household, run, simulation):
contracts = dataprocess.open_file(simulation)[0]
contracts = contracts[int(run) - 1]
rows = []
for contract in contracts:
if contract.get("job_id").startswith("[{}]".format(household)):
contract["load_profile"] = round(
contract.get("load_profile").values[-1], 2)
contract["time"] = dataprocess.convert(contract["time"])
contract["time_of_agreement"] = dataprocess.convert(
contract["time_of_agreement"])
contract = dataprocess.rename_columns(contract)
rows.append(contract)
return rows
def update_pie_chart(run, simulation):
contracts = dataprocess.open_file(simulation)[0]
contracts = contracts[int(run) - 1]
grid = 0
pv = 0
for contract in contracts:
if contract["producer_id"] == "grid":
grid += contract["load_profile"].values[-1]
else:
pv += contract["load_profile"].values[-1]
return go.Figure(data=[
go.Pie(values=[grid, pv],
labels=["Grid", "PV"],
marker=dict(colors=["#DF6461", "#2ecc71"]))
])
def update_consumption(simulation):
contracts, profiles = dataprocess.open_file(simulation)
profiles_combined = dataprocess.neighbourhood_execution_energy_over_time_average(
contracts, profiles)
return go.Figure(data=[
go.Scatter(x=profiles_combined[0],
y=profiles_combined[1],
name="Energy consumed locally",
marker=dict(color="#00A6FC")),
go.Scatter(x=profiles_combined[2],
y=profiles_combined[3],
name="Energy consumed remotely",
marker=dict(color="#FF0000")),
go.Scatter(x=profiles_combined[4],
y=profiles_combined[5],
name="Energy produced",
marker=dict(color="#008000")),
],
layout=go.Layout(xaxis={"title": "Time [Minutes]"},
yaxis={"title": "Energy [W]"}))