Appliance Recognition Based on Continuous Quadratic Programming

Liu, Xiaodong; Liu, Qi

Abstract

The detailed information of residents' electricity consumption is of great significance to the planning of the use of electrical appliances and the reduction of electrical energy consumption. On the basis of analyzing the characteristics of residents' load, through the event detection of changes in the status of electrical appliances, using binary planning to solve the idea of global optimal solution, using the constraints of 0-1, proposed a continuous binary planning model. Based on the proposed load identification algorithm, personal power consumption data can be subdivided into load levels. The test results show that the recognition accuracy can be obtained by selecting the appropriate load identification index. The algorithm can be applied to non-intrusive load monitoring systems in residential buildings.

Citation

Liu, X., & Liu, Q. (2018). Appliance Recognition Based on Continuous Quadratic Programming. In Proceedings of 4th International Conference on Cloud Computing and Security (ICCCS 2018) (63-72). https://doi.org/10.1007/978-3-030-00018-9_6

• Conference Name: 4th International Conference on Cloud Computing and Security (ICCCS 2018)
• Conference Location: Haikou, China
• Start Date: Jun 8, 2018
• End Date: Jun 10, 2018
• Acceptance Date: Apr 20, 2018
• Online Publication Date: Sep 26, 2018
• Publication Date: Sep 26, 2018
• Deposit Date: Jun 22, 2018
• Publicly Available Date: Jun 22, 2018
• Publisher: Springer
• Pages: 63-72
• Series Title: Lecture Notes in Computer Science
• Series Number: 11067
• Series ISSN: 0302-9743
• Book Title: Proceedings of 4th International Conference on Cloud Computing and Security (ICCCS 2018)
• ISBN: 978-3-030-00017-2
• DOI: https://doi.org/10.1007/978-3-030-00018-9_6
• Keywords: Load Signature; Nonintrusive Load Monitoring; Load Identification; Quadratic Programming
• Public URL: http://researchrepository.napier.ac.uk/Output/1233466