Welt erneuerbare Energien gegen Kohle [OC]

[I saw this article ](https://www.carbonbrief.org/iea-renewables-will-be-worlds-top-power-source-by-2026/)that said renewable energy would surpass coal next year and thought that must be BS.

So i took ember energy data and matplotlib and graphed it. and it looks vaguely plausible given how this year is going. Winter Northern Hemisphere is different to summer. But also renewables are growing fast so next year will be more renewables. Renewables here means Hydro (big) Solar (not as big but growing fast) Wind (growing faster than hydro but smaller) bioenergy (small)

Code

import matplotlib.pyplot as plt
import pandas as pd
df = pd.read_csv(„https://storage.googleapis.com/emb-prod-bkt-publicdata/public-downloads/monthly_full_release_long_format.csv“)
df_world = df[df[‚Area‘] == ‚World‘].copy()

# Filter the dataframe for ‚World‘, Electricity generation, TWh unit
df_world_gen = df[
(df[‚Area‘] == ‚World‘) &
(df[‚Category‘] == ‚Electricity generation‘) &
(df[‚Unit‘] == ‚TWh‘)
].copy()

df_world_subset = df_world_gen[df_world_gen[‚Variable‘].isin([‚Coal‘, ‚Renewables‘])].copy()

# Convert ‚Date‘ to datetime and extract the year
df_world_subset[‚Date‘] = pd.to_datetime(df_world_subset[‚Date‘])
df_world_subset[‚Year‘] = df_world_subset[‚Date‘].dt.year

# Group by Year and Variable and sum the values
annual_generation = df_world_subset.groupby([‚Year‘, ‚Variable‘])[‚Value‘].sum().reset_index()

# Pivot the data for plotting
annual_generation_pivot = annual_generation.pivot(index=’Year‘, columns=’Variable‘, values=’Value‘)
plt.figure(figsize=(10, 6))
annual_generation_pivot.plot(kind=’bar‘, ax=plt.gca(), color={‚Coal‘: ‚black‘, ‚Renewables‘: ‚green‘}) #legend should be source not variable. I made this quick

plt.title(‚Annual Electricity Generation: Coal vs Renewables (World)‘, fontsize=16)
plt.xlabel(‚Year‘)
plt.ylabel(‚Annual Generation (TWh)‘)
plt.xticks(rotation=45)
plt.grid(axis=’y‘, linestyle=‘–‚, alpha=0.7)

# Change the legend title from variable to this (my mistake)
ax.legend(title=’Source‘)

plt.tight_layout()
plt.show()

We are hitting peak emissions right now (like this year/already hit), mainly as China is slowing down coal and massively adopting solar