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Inspiring energy conservation through open source metering hardware and embedded real-time load disaggregation

机译:通过开源计量硬件和嵌入式实时负荷分解来鼓励节能

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Utility companies around the world are replacing electro-mechanical power meters with new smart meters. These digital power meters have enhanced communication capabilities, but they are not actually smart. We present the cognitive power meter (c-meter), a meter that is actually smart. By using load disaggregation intelligence, c-meter is the realization of demand response and other smart grid energy conservation initiatives. Our c-meter is made of two key components: a prototype open source ammeter and an optimized embedded load disaggregation algorithm (μDisagg). Additionally, we provide an open source multi-circuit ammeter array that can build probabilistic appliance (or load) consumption models that are used by the c-meter. μDisagg is the first load disaggregation algorithm to be implemented on an inexpensive low-power embedded processor that runs in real-time using a typical/basic smart meter measurement (current, in A). μDisagg can disaggregate loads with complex power states with a high degree of accuracy.
机译:世界各地的公用事业公司正在更换带新智能仪表的机电动力表。这些数字功率计具有增强的通信能力,但它们实际上并不智能。我们介绍了认知功率计(C计),实际智能的仪表。通过使用负荷分解智能,C计是实现需求响应和其他智能电网节能计划的实现。我们的C计由两个关键组件组成:原型开源电流表和优化的嵌入式负载分解算法(μdisagg)。此外,我们提供了一个开源多电路电流表阵列,可以构建C计使用的概率性设备(或负载)消耗模型。 μdisagg是第一个在廉价的低功耗嵌入式处理器上实现的负载分组算法,其使用典型/基本智能仪表测量(电流在a)中实时运行。 μdisagg可以以高精度与复杂功率状态分解负载。

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