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| Content Provider | IET Digital Library |
|---|---|
| Author | Luo, Fengji Ranzi, Gianluca Kong, Weicong Dong, Zhao Yang Wang, Shu Zhao, Junhua |
| Abstract | Demand side management is one of the key topics of smart grids. This study integrates the service computing paradigm in smart grid domain and proposes a demand side personalised recommendation system (PRS). The proposed PRS employs service recommendation techniques to infer residential users’ potential interests and needs on energy saving appliances, and then it recommends energy saving appliances to users, therefore potentially creating opportunities to save energy for the grid. The proposed approach starts by applying a non-intrusive appliance load monitoring (NILM) method based on generalised particle filtering to disaggregate the end users’ household appliance utilisation profiles from the smart meter data. Based on the NILM results, several inference rules are applied to infer the preferences and energy consumption patterns, and to form the user profile. In parallel, information retrieval techniques are applied to extract keywords from the textual appliance advertisements (Ads), and to define the appliance profile. Finally, the similarity measurement method is applied to compare the user profile and appliance profile, to rank the appliance Ad, and to make the recommendations. Experiments are conducted to validate the proposed system. |
| Starting Page | 1786 |
| Ending Page | 1793 |
| Page Count | 8 |
| ISSN | 17518687 |
| Volume Number | 11 |
| e-ISSN | 17518695 |
| Issue Number | Issue 7, May (2017) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/iet-gtd/11/7 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/iet-gtd.2016.1615 |
| Journal | IET Generation, Transmission & Distribution |
| Publisher Date | 2017-02-06 |
| Access Restriction | Open |
| Rights Holder | © The Institution of Engineering and Technology |
| Subject Keyword | Appliance Profile Demand Side Management Demand Side Personalised Recommendation System Domestic Appliances Energy Conservation Energy Consumption Pattern Energy Saving Appliances Generalised Particle Filtering Household Appliance Utilisation Profile Inference Mechanisms Inference Rules Information Network Information Retrieval Technique Knowledge Engineering Technique Nonintrusive Appliance Load Monitoring Nonintrusive Energy Saving Appliance Recommender System Power And Energy Measurement Power Engineering Computing Power System Economics Power System Managemen Power System Measurement And Metering Power System Operation Recommender System Service Computing Paradigm Service Recommendation Technique Similarity Measurement Method Smart Grid Domain Smart Grid Residential User Smart Meter Data Smart Meters Smart Power Grid Textual Appliance Advertisements User Profile |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Energy Engineering and Power Technology Electrical and Electronic Engineering |
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