An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity
Acting as a virtual sensor network for household appliance energy use monitoring, non-intrusive load monitoring is emerging as the technical basis for refined electricity analysis as well as home energy management. Aiming for robust and reliable monitoring, the ensemble approach has been expected in...
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MDPI AG
2021-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/22/7750 |
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| author | Yu Liu Qianyun Shi Yan Wang Xin Zhao Shan Gao Xueliang Huang |
| author_facet | Yu Liu Qianyun Shi Yan Wang Xin Zhao Shan Gao Xueliang Huang |
| author_sort | Yu Liu |
| collection | DOAJ |
| description | Acting as a virtual sensor network for household appliance energy use monitoring, non-intrusive load monitoring is emerging as the technical basis for refined electricity analysis as well as home energy management. Aiming for robust and reliable monitoring, the ensemble approach has been expected in load disaggregation, but the obstacles of design difficulty and computational inefficiency still exist. To address this, an ensemble design integrated with multi-heterogeneity is proposed for non-intrusive energy use disaggregation in this paper. Firstly, the idea of utilizing a heterogeneous design is presented, and the corresponding ensemble framework for load disaggregation is established. Then, a sparse coding model is allocated for individual classifiers, and the combined classifier is diversified by introducing different distance and similarity measures without consideration of sparsity, forming mutually heterogeneous classifiers. Lastly, a multiple-evaluations-based decision process is fine-tuned following the interactions of multi-heterogeneous committees, and finally deployed as the decision maker. Through verifications on both a low-voltage network simulator and a field measurement dataset, the proposed approach is demonstrated to be effective in enhancing load disaggregation performance robustly. By appropriately introducing the heterogeneous design into the ensemble approach, load monitoring improvements are observed with reduced computational burden, which stimulates research enthusiasm in investigating valid ensemble strategies for practical non-intrusive load monitoring implementations. |
| first_indexed | 2024-03-10T05:04:28Z |
| format | Article |
| id | doaj.art-c68633e83c65499eab7a181071aed56f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T05:04:28Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c68633e83c65499eab7a181071aed56f2023-11-23T01:29:13ZengMDPI AGSensors1424-82202021-11-012122775010.3390/s21227750An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional HeterogeneityYu Liu0Qianyun Shi1Yan Wang2Xin Zhao3Shan Gao4Xueliang Huang5School of Electrical Engineering, Southeast University, Nanjing 210018, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210018, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210018, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210018, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210018, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210018, ChinaActing as a virtual sensor network for household appliance energy use monitoring, non-intrusive load monitoring is emerging as the technical basis for refined electricity analysis as well as home energy management. Aiming for robust and reliable monitoring, the ensemble approach has been expected in load disaggregation, but the obstacles of design difficulty and computational inefficiency still exist. To address this, an ensemble design integrated with multi-heterogeneity is proposed for non-intrusive energy use disaggregation in this paper. Firstly, the idea of utilizing a heterogeneous design is presented, and the corresponding ensemble framework for load disaggregation is established. Then, a sparse coding model is allocated for individual classifiers, and the combined classifier is diversified by introducing different distance and similarity measures without consideration of sparsity, forming mutually heterogeneous classifiers. Lastly, a multiple-evaluations-based decision process is fine-tuned following the interactions of multi-heterogeneous committees, and finally deployed as the decision maker. Through verifications on both a low-voltage network simulator and a field measurement dataset, the proposed approach is demonstrated to be effective in enhancing load disaggregation performance robustly. By appropriately introducing the heterogeneous design into the ensemble approach, load monitoring improvements are observed with reduced computational burden, which stimulates research enthusiasm in investigating valid ensemble strategies for practical non-intrusive load monitoring implementations.https://www.mdpi.com/1424-8220/21/22/7750artificial intelligenceenergy disaggregationensemble methodheterogeneous designnon-intrusive load monitoring |
| spellingShingle | Yu Liu Qianyun Shi Yan Wang Xin Zhao Shan Gao Xueliang Huang An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity Sensors artificial intelligence energy disaggregation ensemble method heterogeneous design non-intrusive load monitoring |
| title | An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity |
| title_full | An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity |
| title_fullStr | An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity |
| title_full_unstemmed | An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity |
| title_short | An Enhanced Ensemble Approach for Non-Intrusive Energy Use Monitoring Based on Multidimensional Heterogeneity |
| title_sort | enhanced ensemble approach for non intrusive energy use monitoring based on multidimensional heterogeneity |
| topic | artificial intelligence energy disaggregation ensemble method heterogeneous design non-intrusive load monitoring |
| url | https://www.mdpi.com/1424-8220/21/22/7750 |
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