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@@ -24,7 +24,7 @@ potential = potential.loc[(
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# intermittent sources potential
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p = potential[["onshore", "offshore", "solar"]].to_xarray().to_array()
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-p = np.insert(p, 3, 0.68, axis=0) # nuclear power-like
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+p = np.insert(p, 3, 0.7, axis=0) # nuclear power-like
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times = potential.index.get_level_values(0)
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@@ -41,8 +41,11 @@ fig_dispatch, axes_dispatch = plt.subplots(nrows=6, ncols=2, sharex="col", share
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fig_dispatch.set_figwidth(w*1.5)
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fig_dispatch.set_figheight(h*1.5)
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-date_fmt = mdates.DateFormatter('%d/%m')
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+fig_gap_distribution, axes_gap_distribution = plt.subplots(nrows=3, ncols=2, sharex="col", sharey=True)
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+fig_gap_distribution.set_figwidth(w*1.5)
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+fig_gap_distribution.set_figheight(h*1.5)
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+date_fmt = mdates.DateFormatter('%d/%m')
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# for step in np.linspace(start, stop, 2050-2022, True)[::-1]:
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row = 0
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@@ -69,8 +72,8 @@ for scenario in rte:
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potential["dispatch"] = dp.sum(axis=0)
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data = [
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- potential.loc[(slice('2013-12-01 00:00:00',
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- '2014-01-01 00:00:00'), 'FR'), :],
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+ potential.loc[(slice('2013-02-01 00:00:00',
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+ '2013-03-01 00:00:00'), 'FR'), :],
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potential.loc[(slice('2013-06-01 00:00:00',
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'2013-07-01 00:00:00'), 'FR'), :]
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]
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@@ -121,7 +124,7 @@ for scenario in rte:
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ax.text(
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0.5, 0.87, f"Scénario {scenario} ({months[col]})", ha='center', transform=ax.transAxes)
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- ax.set_ylim(25, 225)
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+ ax.set_ylim(10, 210)
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ax = axes_storage[row, col]
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for i in np.arange(3):
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@@ -157,6 +160,17 @@ for scenario in rte:
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ax.text(
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0.5, 0.87, f"Scénario {scenario} ({months[col]})", ha='center', transform=ax.transAxes)
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+ ax = axes_gap_distribution[row%3, row//3]
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+ hist, bin_edges = np.histogram(gap, bins=1000)
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+ hist = np.cumsum(hist)
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+ hist = 100*(hist - hist.min()) / hist.ptp()
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+
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+ keep = np.abs(bin_edges[:-1]) < 50
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+ ax.plot(bin_edges[:-1][keep], hist[keep], label="power gap")
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+ ax.text(
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+ 0.5, 0.87, f"Scénario {scenario}", ha='center', transform=ax.transAxes)
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+
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+
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row += 1
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for label in axes[-1, 0].get_xmajorticklabels() + axes[-1, 1].get_xmajorticklabels():
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@@ -191,4 +205,11 @@ fig_dispatch.text(1, 0, 'Lucas Gautheron', ha="right")
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fig_dispatch.legend(labels_dispatch, loc='lower right', bbox_to_anchor=(1, -0.1),
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ncol=len(labels_dispatch), bbox_transform=fig_dispatch.transFigure)
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fig_dispatch.savefig("output_dispatch.png", bbox_inches="tight", dpi=200)
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+
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+fig_gap_distribution.suptitle(f"Power gap cumulative distribution (%)\nSimulations based on {begin}--{end} weather data.\n{flex} consumption flexibility; no nuclear seasonality (unrealistic)")
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+fig_gap_distribution.legend(["Power gap (available-load) (GW)"], loc='lower right', bbox_to_anchor=(1, -0.1),
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+ ncol=1, bbox_transform=fig_dispatch.transFigure)
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+fig_gap_distribution.text(1, 0, 'Lucas Gautheron', ha="right")
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+fig_gap_distribution.savefig("output_gap_distribution.png", bbox_inches="tight", dpi=200)
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+
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plt.show()
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