在智能家居中,分散式AI控制器在家用设备上运行对系统的影响

G. van Harmelen, I. E. Lane, G. Hancke
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引用次数: 5

摘要

减少系统负荷分布(由一组电力用户抽取的总负荷电流)上不希望发生的情况的经典方法是采用集中测量和控制系统。由于单个用户的随机性,以及对此类控制信号的群体响应(例如间歇泉的纹波控制),本文提出了一种分散的测量和控制方法,作为与传统方法相关的一些更常见问题的解决方案(例如:“冷负荷拾取效应”)。在两个层面上提出了一种自适应分布式控制系统,既在家庭内部(家庭自动化),也扩展到系统层面本身。然后,单个测量和控制节点(即单个家庭)将联合运行,以实现用户定制,以及系统特定目标(例如,没有冷水澡,但也可以实现最大需求控制)
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System impact of decentralised AI controllers operating on domestic devices in the intelligent home
The classical approach to curtailing unwanted occurrences on a system load profile (totalized load current drawn by a group of electricity consumers) has been to employ a centralised measurement and control system. Due to the stochastic nature of the individual users, and the group response to such control signals (e.g. ripple control of geysers) a decentralised measurement and control approach is proposed here as a solution to some of the more common problems associated with this conventional approach (e.g. "cold-load pickup effect"). An adaptive distributed control system is proposed on two levels, both within the home itself (home automation), as well as being expanded up into the system level itself. Individual measurement and control nodes (i.e. individual homes) will then operate in union to achieve user customization, as well as system specific objectives (e.g. no cold showers, but also enabling maximum demand control).<>
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