How to distribute charging loads for EVs using IoT and multi-agents?
A novel load distribution strategy for aggregators using IoT-enabled mobile devices
September 24, 2024
https://arxiv.org/pdf/2409.14293This paper tackles the problem of efficiently distributing energy loads in a smart grid with diverse devices, including mobile ones like electric vehicles (EVs). It proposes a new strategy considering:
- Heterogeneous devices: Devices have varying energy needs, deadlines, and can operate in multiple power modes (e.g., an EV charging at different speeds).
- Mobility: Some devices, like EVs, can move between aggregators (local energy providers) to find better access to power.
The authors formulate this as a mixed-integer non-linear programming (MINLP) problem and offer a lightweight, distributed algorithm for real-time scheduling.
Relevance to LLM-based Multi-Agent Systems:
- Decentralized decision-making: The proposed algorithm highlights the potential of having intelligent agents (devices) make local decisions based on their needs and available information, similar to how LLMs can enable agency in multi-agent systems.
- Resource allocation: Balancing energy demand and supply across the grid mirrors the challenges of managing resources in complex LLM-powered applications.
- Dynamic environment: The incorporation of mobile devices with changing needs and locations showcases the system's ability to adapt to a dynamic environment, a crucial aspect of real-world multi-agent systems.