Nonintrusive Load Monitoring Algorithm Using Mixed-Integer Linear Programming
Nonintrusive Load Monitoring Algorithm Using Mixed-Integer Linear Programming
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DOI：
10.1109/tce.2018.2843292
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发表时间：
2018-06
影响因子：
4.3
通讯作者：
Fernando Marcos Wittmann;J. López;M. J. Rider
中科院分区：
文献类型：
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作者：
Fernando Marcos Wittmann;J. López;M. J. Rider
提出了一种基于混合整数线性规划的非侵入式负荷监测算法。该公式解决了从复合功率测量中分解单个电器的消耗时出现的多个切换的问题。混合整数线性约束被用来有效地表示每个设备的负载签名。此外，还使用了基于窗口的策略来提高NILM算法的计算性能。可以仅使用低采样率下的有功功率测量来进行分解，这在大多数电能表中都是可用的。此外，如果可用，还可以将其他特征添加到模型中以提高其精度，例如无功特征或谐波。使用分钟功率数据集上的三个测试用例对该算法的性能进行了评估。并与一种称为辅助线性整数规划的解集方法进行了比较。结果表明，该方法能够以高效的计算方式准确地识别和分配个体能量特征，适合于低成本的家庭能源管理。
This paper presents a nonintrusive load monitoring (NILM) algorithm based on mixed-integer linear programming. The formulation deals with the problem of multiple switching that arises when disaggregating individual appliance’s consumptions from a compound power measurement. Mixed-integer linear constraints are used to efficiently represent the load signatures of each appliance. Also, a window-based strategy is used to enhance the computational performance of the proposed NILM algorithm. The disaggregation can be made using only active power measurements at a low sampling rate, which is available in most energy meters. Moreover, if available, other signatures can be added to the model to improve its accuracy, such as reactive power signatures or harmonics. The performance of the algorithm is evaluated using three test cases from the almanac of minutely power dataset. The proposed method is also compared with a disaggregation method called aided linear integer programming. Results demonstrate the ability of the proposed method to accurately identify and allocate individual energy signatures in a computationally efficient manner, which makes it suitable for inexpensive home energy management.