用主动推理框架协调家庭能源，兼顾成本、排放与舒适度
EcoNet: Multiagent Planning and Control Of Household Energy Resources Using Active Inference
- 基于主动推理构建多智能体能源管理框架
- 在不确定条件下实现成本、排放与舒适度的平衡优化
- 适合研究智能电网与家庭能源系统的人参考
自动化系统的发展为家庭、区域及电网层级的能源智能化管理提供了新机遇。家庭能源管理系统（HEMS）可通过优化家用设备的调度与使用来发挥作用。然而，家庭目标常复杂且冲突，例如降低能源成本和电网碳排放的同时保持室内温度舒适。此外，智能HEMS需在不确定性下决策：尽管要规划未来行动，但天气和光伏发电预测本身存在固有不确定性。本文提出EcoNet，一种基于主动推理的贝叶斯方法，用于家庭与邻里层级的能源管理，旨在提升管理与协调能力，同时处理不确定性，并考虑可能条件化且相互冲突的目标与偏好。文中展示了仿真结果并进行了讨论。
原文摘要 · Abstract (English)
Advances in automated systems afford new opportunities for intelligent management of energy at household, local area, and utility scales. Home Energy Management Systems (HEMS) can play a role by optimizing the schedule and use of household energy devices and resources. One challenge is that the goals of a household can be complex and conflicting. For example, a household might wish to reduce energy costs and grid-associated greenhouse gas emissions, yet keep room temperatures comfortable. Another challenge is that an intelligent HEMS agent must make decisions under uncertainty. An agent must plan actions into the future, but weather and solar generation forecasts, for example, provide inherently uncertain estimates of future conditions. This paper introduces EcoNet, a Bayesian approach to household and neighborhood energy management that is based on active inference. The aim is to improve energy management and coordination, while accommodating uncertainties and taking into account potentially conditional and conflicting goals and preferences. Simulation results are presented and discussed.
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