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

2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) Pub Date : 2013-12-01 DOI:10.1109/APPEEC.2013.6837120

S. Makonin, William Sung, Ryan Dela Cruz, Brett Yarrow, Bob Gill, F. Popowich, I. Bajić

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引用次数: 13

Abstract

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.

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通过开源计量硬件和嵌入式实时负载分解激励节能

世界各地的公用事业公司正在用新的智能电表取代机电电表。这些数字电表增强了通信能力，但它们实际上并不智能。我们展示了认知能力测量仪(c-meter)，一个实际上很智能的测量仪。通过负荷分解智能，c-meter实现了需求响应等智能电网节能举措。我们的电流表由两个关键组件组成:一个开源电流表原型和一个优化的嵌入式负载分解算法(μDisagg)。此外，我们提供了一个开源的多电路电流表阵列，可以构建c-meter使用的概率设备(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解算法，该处理器使用典型/基本智能电表测量(电流，单位a)实时运行。μDisagg可以高精度地分解具有复杂功率状态的负载。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2013 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

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