Altrabalsi, Hana and Liao, Jing and Stankovic, Lina and Stankovic, Vladimir (2014) A low-complexity energy disaggregation method : performance and robustness. In: 2014 IEEE Symposium on Computational Intelligence Applications in Smart Grid (CIASG). IEEE, Piscataway, NJ., pp. 1-8.
Altrabalsi_etal_CIASG2014_low_complexity_energy_disaggregation_method.pdf - Accepted Author Manuscript
Disaggregating total household's energy data down to individual appliances via non-intrusive appliance load monitoring (NALM) has generated renewed interest with ongoing or planned large-scale smart meter deployments worldwide. Of special interest are NALM algorithms that are of low complexity and operate in near real time, supporting emerging applications such as in-home displays, remote appliance scheduling and home automation, and use low sampling rates data from commercial smart meters. NALM methods, based on Hidden Markov Model (HMM) and its variations, have become the state of the art due to their high performance, but suffer from high computational cost. In this paper, we develop an alternative approach based on support vector machine (SVM) and k-means, where k-means is used to reduce the SVM training set size by identifying only the representative subset of the original dataset for the SVM training. The resulting scheme outperforms individual k-means and SVM classifiers and shows competitive performance to the state-of-the-art HMM-based NALM method with up to 45 times lower execution time (including training and testing).
|Item type:||Book Section|
|Notes:||(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.|
|Keywords:||complexity theory, feature extraction, hidden Markov models, home appliances, support vector machines, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering|
|Subjects:||Technology > Electrical engineering. Electronics Nuclear engineering|
|Department:||Faculty of Engineering > Electronic and Electrical Engineering|
|Depositing user:||Pure Administrator|
|Date Deposited:||02 Feb 2015 13:44|
|Last modified:||02 Apr 2017 02:43|