EnergyBridge: Benchmarking Household Energy Management, User Participation, and Grid Flexibility

arXiv:2608.08691 · cs.AI · Submitted 2026-08-09 · Read on arXiv

Xudong Wu, Zeqing Wu, Jiarui Zhang, Xuhao Fan, Ziang Ding, Yuming Zhuang, Mingqi Yuan, Yilun Du, Hongjie Jia, Yunfei Mu, Jiayu Chen

cs.AI

Submitted: 2026-08-09

Updated: 2026-08-11

Code: https://github.com/Agentic-Intelligence-Lab/EnergyBridge

License: http://creativecommons.org/licenses/by/4.0/

The gist: Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity only when residents authorize a plan and the

Terminology

Abstract

Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity only when residents authorize a plan and the promised response is delivered. Existing benchmarks evaluate control but omit event-specific authorization. We present EnergyBridge, a benchmark and agent framework connecting capacity reporting, household authorization, and physical execution. It combines region-specific EnergyPlus environments for Tianjin and Berlin with an LLM-based User Participation Simulator. Against 584 persona- and event-matched human role-play judgments, the LLM-based User Participation Simulator preserves method ordering with a 5.3-point mean absolute acceptance error. Across conventional controllers and agent baselines, EnergyBridge achieves the highest simulated authorization, lowest event-window energy, and the most reliable capacity commitment in both regions. We release human data and codes for reproducible human-centered grid-flexibility research: https://github.com/Agentic-Intelligence-Lab/EnergyBridge.

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