Appliance Recognition Based on Continuous Quadratic Programming

Research Output

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.

Date:

26 September 2018
Publication Status:

Published
DOI:

10.1007/978-3-030-00018-9_6
Library of Congress:

QA75 Electronic computers. Computer science
Dewey Decimal Classification:

005 Computer programming, programs & data
Funders:

European Commission

http://researchrepository.napier.ac.uk/output/1233466 <p>Liu, X., & Liu, Q. (2018). Appliance Recognition Based on Continuous Quadratic Programming. In <i>Proceedings of 4th International Conference on Cloud Computing and Security (ICCCS 2018)</i>, (63-72). https://doi.org/10.1007/978-3-030-00018-9_6</p>

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