Abstract
Many time series in smart energy systems exhibit two different timescales. On the one hand there are patterns linked to daily human activities. On the other hand, there are relatively slow trends linked to seasonal variations. In this paper we interpret these time series as matrices, to be visualized as images. This approach has two advantages: First of all, interpreting such time series as images enables one to visually integrate across the image and makes it therefore easier to spot subtle or faint features. Second, the matrix interpretation also grants elucidation of the underlying structure using well-established matrix decomposition methods. We will illustrate both these aspects for data obtained from the German day-ahead market.
Original language | English |
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Title of host publication | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 1-6 |
Number of pages | 6 |
ISBN (Electronic) | 9781538619537 |
DOIs | |
Publication status | Published - 16 Jan 2018 |
Event | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Torino, Italy Duration: 26 Sept 2017 → 29 Sept 2017 |
Conference
Conference | 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 |
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Country/Territory | Italy |
City | Torino |
Period | 26/09/17 → 29/09/17 |
Funding
This work was supported in part by the Dutch STW under project grant
Funders | Funder number |
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Dutch STW |
Keywords
- Data analysis
- Data preprocessing
- Renewable energy sources
- Smart grids
- Time series analysis