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A Semi-Intrusive Load Monitoring Approach for Demand Response Applications

机译:需求响应应用的半侵入式负荷监测方法

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Appliance-Load Monitoring (ALM) is essential for several demand-response (DR) programs. The techniques used for this purpose are broadly classified into two types: 1) Intrusive Load Monitoring (ILM), and 2) Non-Intrusive Load Monitoring (NILM). This paper proposes a semi-intrusive load monitoring (SILM) technique to exploit the bests of both. The method does not use any disaggregation algorithm; instead, it’s an instrumentation approach to monitor the power consumption of appliances. First, it groups all appliances of a residential house in some clusters and then monitors those, in near real-time, using only one sensing-unit per cluster. A lab-scale testbed is developed to verify the claims of the proposed method. Test results demonstrate the monitoring and controlling capability and prove the cost-effectiveness of the technique. Raspberry Pi is used as the programming platform along with Python programming language.
机译:电器负载监测(ALM)对于多个需求 - 响应(DR)计划至关重要。用于此目的的技术广泛地分为两种类型:1)侵入式负荷监测(ILM)和2)非侵入式负荷监测(NILM)。本文提出了一种半侵入式负荷监测(Silm)技术,用于利用两者的最佳产品。该方法不使用任何分类算法;相反,它是监控设备功耗的仪器方法。首先,它将住宅的所有设备群体分组在某些集群中,然后在近期实时监控那些,每簇仅使用一个传感单元。制定了实验室标准测试用来验证所提出的方法的权利要求。测试结果证明了监测和控制能力并证明了该技术的成本效益。 Raspberry PI用作编程平台以及Python编程语言。

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