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Welcome to this new tutorial. Off course Hadar is well designed to compute study for network adequacy. You can launch Hadar to compute adequacy for the next second or next year.
But Hadar can also be used like a asset investment tool. In this example, thanks to Hadar, we will make the best choice for renewable energy and network investment.
We have a small region, with metropole which doesn’t produce anything, a nuclear plan and two small cities with production.
First step parse data with pandas (and plot them)
import numpy as np import pandas as pd import hadar as hd import plotly.graph_objects as go
a = pd.read_csv('a.csv', index_col='date') fig = go.Figure() fig.add_traces(go.Scatter(x=a.index, y=a['consumption'], name='load')) fig.add_traces(go.Scatter(x=a.index, y=a['gas'], name='gas')) fig.update_layout(title_text='Node A', yaxis_title='MW')