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Vukadinovic Greetham, Danica and Giasemidis, Georgios
(2019).
DOI: https://doi.org/10.1145/3307772.3330164
Abstract
Recurrence Quantification Analysis (RQA) is becoming a popular technique to analyse time-series obtained from complex dynamical systems. In this work, a recently presented RQA-based method to analyse and manage energy demand at low sampling rate (5 min and 30 min) is tested using data-sets from three small enterprises. From recurrence plots, different RQA variables are obtained and analysed, following parameter optimisation that depends on a system observed. Based on RQA variables, energy maps of ‘normal’ behaviour are created. Here, preliminary robustness tests concern- ing the training phase length, missing data and noise are presented. Our test results show that this approach has great potential in energy management of small and medium enterprises.
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About
- Item ORO ID
- 61432
- Item Type
- Conference or Workshop Item
- ISBN
- 1-4503-6671-6, 978-1-4503-6671-7
- Project Funding Details
-
Funded Project Name Project ID Funding Body RAE2 (Responsive Algorithmic Enterprise 2) Not Set AND Technology and Research - Keywords
- recurrence quantification analysis(RQA); SME energy profiles; disaggregation
- Academic Unit or School
-
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM) - Copyright Holders
- © 2019 The Authors
- Depositing User
- Danica Vukadinovic Greetham