Abstract
The management of electricity system in home environments plays an important role in generating energy consumption and improving efficiency of energy usage. At present, nonintrusive appliance load monitoring (NIALM) techniques are the most effective approach for estimating the electrical power consumption of individual appliances. This paper presents our contribution in intelligent electrical appliance decomposition in home environment. It is a modified power appliance disaggregation technique based on power harmonic features and support vector machine (SVM). It has higher recognition accuracy and faster computational speed. The experimental results of the power decomposition technique on real date are presented with promising results.
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