activity
20242026
collaborators

8 papers

cs.AI2026

Simulating Tenant Responses to Energy Policy Interventions with Transaction-Cost-Aware LLM Agent

Weijie Xia, Stefanie Horian, Hanyue Huang +3

Recent studies use Large language models (LLMs) to simulate human opinions and decisions by prompting models with demographic, attitudinal, or persona-based descriptions. Yet such…

eess.SY2026

Risk-Based PV-Rich Distribution System Planning Using Generative AI

Habtemariam Aberie Kefale, Weijie Xia, Nanda Kishor Panda +2

Hosting capacity (HC) assessment plays a critical role in distribution system planning under increasing penetration of distributed energy resources (DERs) and associated uncertaint…

eess.SY2026

Estimating Density Functions for Probabilistic Power Flow Using Invertible Neural Networks

Weijie Xia, James Ciyu Qin, Edgar Mauricio Salazar Duque +4

Probabilistic power flow (PPF) is essential for quantifying operational uncertainty in modern power systems with high penetrations of renewable generation and flexible loads. Conve…

eess.SY2025

An OPF-based Control Framework for Hybrid AC-MTDC Power Systems under Uncertainty

Hongjin Du, Rahul Rane, Weijie Xia +2

The increasing integration of renewable energy, particularly offshore wind, introduces significant uncertainty into hybrid AC-HVDC systems due to forecast errors and power fluctuat…

eess.SY2024

Comparative Analysis of Zero-Shot Capability of Time-Series Foundation Models in Short-Term Load Prediction

Nan Lin, Dong Yun, Weijie Xia +2

Short-term load prediction (STLP) is critical for modern power distribution system operations, particularly as demand and generation uncertainties grow with the integration of low-…

cs.LG2024

RL-ADN: A High-Performance Deep Reinforcement Learning Environment for Optimal Energy Storage Systems Dispatch in Active Distribution Networks

Shengren Hou, Shuyi Gao, Weijie Xia +3

Deep Reinforcement Learning (DRL) presents a promising avenue for optimizing Energy Storage Systems (ESSs) dispatch in distribution networks. This paper introduces RL-ADN, an innov…