# Large Language Model-Assisted Planning of Electric Vehicle Charging Infrastructure with Real-World Case Study

arXiv: https://arxiv.org/abs/2511.19055 · HTML: https://mlsanity.com/paper/2511.19055/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 72 references that are in the map.
- First posted on arXiv 24 Nov 2025.

## Builds on (most cited first, 15 of 15)

- [Global Convergence of ADMM in Nonconvex Nonsmooth Optimization](https://mlsanity.com/paper/1511.06324/) (2015)
- [Evaluating Language Models for Mathematics through Interactions](https://mlsanity.com/paper/2306.01694/) (2023)
- [Convergence Analysis of Alternating Direction Method of Multipliers for a Family of Nonconvex Problems](https://mlsanity.com/paper/1410.1390/) (2014)
- [On the Linear Convergence of the ADMM in Decentralized Consensus Optimization](https://mlsanity.com/paper/1307.5561/) (2013)
- [LLMs for Mathematical Modeling: Towards Bridging the Gap between Natural and Mathematical Languages](https://mlsanity.com/paper/2405.13144/) (2024)
- [MM-Agent: LLM as Agents for Real-world Mathematical Modeling Problem](https://mlsanity.com/paper/2505.14148/) (2025)
- [Large Foundation Models for Power Systems](https://mlsanity.com/paper/2312.07044/) (2023)
- [LM4OPT: Unveiling the Potential of Large Language Models in Formulating Mathematical Optimization Problems](https://mlsanity.com/paper/2403.01342/) (2024)
- [Incentivizing Energy Trading for Interconnected Microgrids](https://mlsanity.com/paper/1609.07576/) (2016)
- [A Two-level ADMM Algorithm for AC OPF with Global Convergence Guarantees](https://mlsanity.com/paper/2008.12139/) (2020)
- [Blockchain-Based Decentralized Energy Management Platform for Residential Distributed Energy Resources in A Virtual Power Plant](https://mlsanity.com/paper/2105.00174/) (2021)
- [Joint Optimization of Autonomous Electric Vehicle Fleet Operations and Charging Station Siting](https://mlsanity.com/paper/2107.00165/) (2021)
- [Dynamic Rolling Horizon Optimization for Network-Constrained V2X Value Stacking of Electric Vehicles Under Uncertainties](https://mlsanity.com/paper/2502.09290/) (2025)
- [Joint Investment and Operation of Microgrid](https://mlsanity.com/paper/1511.01984/) (2015)
- [Towards a Multimodal Charging Network: Joint Planning of Charging Stations and Battery Swapping Stations for Electrified Ride-Hailing Fleets](https://mlsanity.com/paper/2212.12677/) (2022)

## Built on by (most cited first, 1 of 1)

- [LLMs and Agentic AI Systems for Smart Grids: A Tutorial on Architectures and Applications](https://mlsanity.com/paper/2607.18147/) (2026)

## Abstract (arXiv)

The growing demand for electric vehicle (EV) charging infrastructure presents significant planning challenges, requiring efficient strategies for investment and operation to deliver cost-effective charging services. However, the potential benefits of EV charging assignment, particularly in response to varying spatial-temporal patterns of charging demand, remain under-explored in infrastructure planning. This paper proposes an integrated approach that jointly optimizes investment decisions and charging assignments while accounting for spatial-temporal demand dynamics and their interdependencies. To support efficient model development, we leverage a large language model (LLM) to assist in generating and refining the mathematical formulation from structured natural-language descriptions, significantly reducing the modeling burden. The resulting optimization model enables optimal joint decision-making for investment and operation. Additionally, we propose a distributed optimization algorithm based on the Alternating Direction Method of Multipliers (ADMM) to address computational complexity in high-dimensional scenarios, which can be executed on standard computing platforms. We validate our approach through a case study using 1.5 million real-world travel records from Chengdu, China, demonstrating a 30% reduction in total cost compared to a baseline without EV assignment.