# Optimized Renewable Energy Planning MDP for Socially-Equitable Electricity Coverage in the US

## TL;DR

This paper introduces an MDP framework for optimizing renewable energy distribution in US cities, balancing system efficiency with social equity to improve access for low-income communities.

## Contribution

It develops a novel MDP model that explicitly incorporates social equity factors into renewable energy planning, addressing a gap in existing approaches.

## Key findings

- Achieves 32.9% renewable energy penetration.
- Reduces underserved low-income populations by 55%.
- Monte Carlo Tree Search offers competitive performance with lower costs.

## Abstract

Traditional power grid infrastructure presents significant barriers to renewable energy integration and perpetuates energy access inequities, with low-income communities experiencing disproportionately longer power outages. This study develops a Markov Decision Process (MDP) framework to optimize renewable energy allocation while explicitly addressing social equity concerns in electricity distribution. The model incorporates budget constraints, energy demand variability, and social vulnerability indicators across eight major U.S. cities to evaluate policy alternatives for equitable clean energy transitions. Numerical experiments compare the MDP-based approach against baseline policies including random allocation, greedy renewable expansion, and expert heuristics. Results demonstrate that equity-focused optimization can achieve 32.9% renewable energy penetration while reducing underserved low-income populations by 55% compared to conventional approaches. The expert policy achieved the highest reward, while the Monte Carlo Tree Search baseline provided competitive performance with significantly lower budget utilization, demonstrating that fair distribution of clean energy resources is achievable without sacrificing overall system performance and providing ways for integrating social equity considerations with climate goals and inclusive access to clean power infrastructure.