Automated energy management and learning

Gabriel Santos, B. Teixeira, T. Pinto, Z. Vale
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Abstract

Automatic energy management systems allow users’ active participation in flexibility management while assuring their energy demands. We propose a transparent framework for automated energy management to increase trust and improve the learning process, combining machine learning, experts’ knowledge, and semantic reasoning. A practical example of thermal comfort shows the advantages of the framework.
自动化的能量管理和学习
自动能源管理系统允许用户积极参与灵活性管理,同时保证他们的能源需求。我们提出了一个透明的自动化能源管理框架,以增加信任并改善学习过程,结合机器学习,专家知识和语义推理。热舒适的实例表明了该框架的优点。
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