Si vs Thin Film Capacity

US utility-scale silicon vs thin-film capacity over time, according to LBL’s 2021 Utility-Scale PV report.

import pandas as pd
import matplotlib.pyplot as plt

url = 'https://emp.lbl.gov/sites/default/files/2021_utility-scale_solar_data_update.xlsm'

df = pd.read_excel(url, sheet_name='Individual_Project_Data')
df = df.loc[df['Solar Tech Main'] == 'PV', :]

fig, axes = plt.subplots(2, 1, sharex=True)
fig.suptitle('LBL Utility-Scale Solar, 2021 Edition')


for tech in ['c-Si', 'Thin-Film']:
    subset = df.loc[df['Solar Tech Sub'] == tech, :]
    subset = subset.set_index('Solar COD').sort_index()
    subset.assign(n=1)['n'].cumsum().plot(label=tech, ax=axes[0])
    subset['Solar Capacity MW-DC'].cumsum().plot(label=tech, ax=axes[1])

axes[0].legend()
axes[0].set_ylabel('Project Count')
axes[1].legend()
axes[1].set_ylabel('Project Capacity [MWdc]')

fig.tight_layout()

for dt in pd.date_range('2008-12-31', '2020-12-31', freq='a'):
    axes[0].axvline(dt, c='k', alpha=0.3, ls=':')
    axes[1].axvline(dt, c='k', alpha=0.3, ls=':')

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