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import plotly
import plotly.subplots
import plotly.express as px
import plotly.graph_objects as go
import matplotlib.pyplot as plt
import data_processing
def visualize_simulation(results, date_range):
start_date, end_date = date_range
fig = plt.figure()
results = results.loc[start_date: end_date]
x = results.index
y = [results.consumption_from_solar, results.consumption_from_network, results.consumption_from_bess]
plt.plot(x, y[0], label='Demand served by solar', color='yellow', linewidth=0.5)
plt.plot(x, y[0]+y[1], label='Demand served by network', color='blue', linewidth=0.5)
plt.plot(x, y[0]+y[1]+y[2], label='Demand served by BESS', color='green', linewidth=0.5)
plt.fill_between(x, y[0]+y[1]+y[2], 0, color='green')
plt.fill_between(x, y[0]+y[1], 0, color='blue')
plt.fill_between(x, y[0], 0, color='yellow')
# plt.xlim(datetime.datetime.fromisoformat(start_date), datetime.datetime.fromisoformat(end_date))
plt.legend()
return fig
MARGIN = dict(
l=0,
r=0,
b=0,
t=0,
pad=0
)
def plotly_visualize_simulation(results, date_range):
start_date, end_date = date_range
results = results.loc[start_date: end_date]
'''
fig = px.area(results, x=results.index, y="consumption_from_network")
return fig'''
fig = plotly.subplots.make_subplots(specs=[[{"secondary_y": True}]])
fig.update_layout(yaxis2=dict(range=[0.0, 110]))
fig.add_trace(go.Scatter(
x=results.index, y=results['consumption_from_network'],
hoverinfo='x+y',
mode='lines',
line=dict(width=0.5, color='blue'),
name='Network',
stackgroup='one' # define stack group
))
fig.add_trace(go.Scatter(
x=results.index, y=results['consumption_from_solar'],
hoverinfo='x+y',
mode='lines',
line=dict(width=0.5, color='orange'),
name='Solar',
stackgroup='one'
))
fig.add_trace(go.Scatter(
x=results.index, y=results['consumption_from_bess'],
hoverinfo='x+y',
mode='lines',
line=dict(width=0.5, color='green'),
name='BESS',
stackgroup='one'
))
fig.add_trace(go.Scatter(
x=results.index, y=results['soc_series'] * 100,
hoverinfo='x+y',
mode='lines',
line=dict(width=1.5, color='red'),
name='State of charge'),
secondary_y=True
)
# could not kill the huge padding this introduces:
# fig.update_layout(title=f"Simulation for {start_date} - {end_date}")
fig.update_layout(height=400, yaxis_title="Consumption [kW]", yaxis2_title="State of charge [%]", yaxis2_showgrid=False)
return fig
def plotly_visualize_monthly(result):
consumption = data_processing.monthly_analysis(result)
# months = monthly_results.index
months = list(range(1, 13))
fig = go.Figure()
fig.add_trace(go.Scatter(
x=months, y=consumption[:, 0], # monthly_results['consumption_from_network'],
hoverinfo='x+y',
mode='lines',
line=dict(width=0.5, color='blue'),
name='Network',
stackgroup='one' # define stack group
))
fig.add_trace(go.Scatter(
x=months, y=consumption[:, 1], # y=monthly_results['consumption_from_solar'],
hoverinfo='x+y',
mode='lines',
line=dict(width=0.5, color='orange'),
name='Solar',
stackgroup='one'
))
fig.add_trace(go.Scatter(
x=months, y=consumption[:, 2], # y=monthly_results['consumption_from_bess'],
hoverinfo='x+y',
mode='lines',
line=dict(width=0.5, color='green'),
name='BESS',
stackgroup='one'
))
fig.update_layout(
yaxis_title="Monthly consumption in [MWh]",
height=400
)
return fig
def monthly_visualization(consumptions_in_mwh):
percentages = consumptions_in_mwh[:, :3] / consumptions_in_mwh.sum(axis=1, keepdims=True) * 100
bats = 0
nws = 0
sols = 0
print("[Mwh]")
print("==========================")
print("month\tnetwork\tsolar\tbess")
for month_minus_1 in range(12):
network, solar, bess = consumptions_in_mwh[month_minus_1]
print(f"{month_minus_1+1}\t{network:0.2f}\t{solar:0.2f}\t{bess:0.2f}")
bats += bess
nws += network
sols += solar
print(f"\t{nws:0.2f}\t{sols:0.2f}\t{bats:0.2f}")
fig, ax = plt.subplots()
ax.stackplot(range(1, 13),
percentages[:, 0], percentages[:, 1], percentages[:, 2],
labels=["hálózat", "egyenesen a naptól", "a naptól a BESS-en keresztül"])
ax.set_ylim(0, 100)
ax.legend()
plt.title('A fogyasztás hány százalékát fedezte az adott hónapban?')
plt.show()
plt.stackplot(range(1, 13),
consumptions_in_mwh[:, 0], consumptions_in_mwh[:, 1], consumptions_in_mwh[:, 2],
labels=["hálózat", "egyenesen a naptól", "a naptól a BESS-en keresztül"])
plt.legend()
plt.title('Mennyi fogyasztást fedezett az adott hónapban? [MWh]')
plt.show()
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