LLM-MPC for Home Energy Management
What it is
A framework that combines Large Language Models (LLMs) with Model Predictive Control (MPC) to manage residential energy. It uses a zero-shot LLM to interpret natural language commands and orchestrate tool calls to optimize battery scheduling and minimize electricity costs.
The problem it solves
The difficulty of users interacting with complex energy optimization systems and managing the intermittency of renewable energy sources.
What you could use it for
- Home Energy Management Systems (HEMS)
- Optimizing residential solar self-consumption
- Automated battery charging/discharging based on grid pricing
- Natural language control of smart home energy systems
Read the source ↗Back to the library →
Summary written by an AI model from the source; check the source before you rely on it.