Retire: Coal Plant Retirement Analysis¶
Welcome to the documentation for the retire package, a comprehensive tool for analyzing coal plant retirement strategies based on research published in Nature Energy.
Overview¶
The retire package provides data and analysis tools for US coal plant retirement analysis based on research published in Nature Energy.
Key Features:
Comprehensive Dataset: Detailed coal plant data with operational and contextual factors
Network Analysis: Analyze plant relationships using similarity metrics
Visualization Suite: Rich plotting capabilities for retirement patterns
Research Reproducibility: Access to manuscript results and analysis
Quick Start¶
from retire import Retire, Explore
# Load data and create analysis objects
retire_obj = Retire()
explore = Explore(retire_obj.graph, retire_obj.raw_df)
# Visualize the network
fig, ax = explore.drawGraph(col="ret_STATUS")
(Source code, png, hires.png, pdf)
Figure adapted from Gathrid et al. (2025, Nature Energy).
In [1]: from retire import Retire, Explore
In [2]: retire_obj = Retire()
In [3]: retire_obj.get_group_report().head()
Out[3]:
Group ... Barriers
0 0 ... Plants are in counties with a significant swin...
1 1 ... Heavily invested in emissions control technolo...
2 2 ... Plants with the highest average cashflows and ...
3 3 ... Some of the most profitable plants (low forwar...
4 4 ... Of the 26% of plants that plan to retire, the ...
[5 rows x 7 columns]
In [4]: retire_obj.get_target_explanations().head()
Out[4]:
Name ... Explanation
0 Dolet Hills ... Plant's high operating costs and utility cost ...
1 Martin Drake // South Plant ... Plant is retiring due to aging and transition ...
2 E D Edwards ... Plant closed due to legal settlement from envi...
3 Lowman Energy Center ... Plant's aging infrastructure and coal ash pond...
4 Waukegan ... Plant's poor financial results and economic pr...
[5 rows x 4 columns]
Getting Started:
API Reference:
Development:
Tutorials: