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Optimising Parameters in Recurrence Quantification Analysis of Smart Energy Systems

Giasemidis, Georgios and Vukadinovic Greetham, Danica (2018). Optimising Parameters in Recurrence Quantification Analysis of Smart Energy Systems. In: 9th International Conference on Information, Intelligence, Systems and Applications (IISA2018), 23-25 Jul 2018, Zakynthos, Greece.

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Recurrence Quantification Analysis (RQA) can help to detect significant events and phase transitions of a dynamical system, but choosing a suitable set of parameters is crucial for the success. From recurrence plots different RQA variables can be obtained and analysed. Currently, most of the methods for RQA radius optimisation are focusing on a single RQA variable. In this work we are proposing two new methods for radius optimisation that look for an optimum in the higher dimensional space of the RQA variables, therefore synchronously optimising across several variables. We illustrate our approach using two case studies: a well known Lorenz dynamical system, and a time-series obtained from monitoring energy consumption of a small enterprise. Our case studies show that both methods result in plausible values and can be used to analyse energy data.

Item Type: Conference or Workshop Item
Copyright Holders: 2018 The Authors
Project Funding Details:
Funded Project NameProject IDFunding Body
Keywords: Recurrence Quantification Analysis; Smart grids; Energy disaggregation
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 55774
Depositing User: Danica Vukadinovic Greetham
Date Deposited: 31 Jul 2018 11:19
Last Modified: 02 May 2019 13:35
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