University of Oulu

E K Juuso 2018 IOP Conf. Ser.: Earth Environ. Sci. 136 012007

Intelligent trend analysis for a solar thermal energy collector field

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Author: Juuso, Esko K.1
Organizations: 1Control Engineering, Faculty of Technology, 90014 University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202201249876
Language: English
Published: IOP Publishing, 2017
Publish Date: 2022-01-24
Description:

Abstract

Solar thermal power plants collect available solar energy in a usable form at a temperature range which is adapted to the irradiation levels and seasonal variations. Solar energy can be collected only when the irradiation is high enough to produce the required temperatures. During the operation, a trade-off of the temperature and the flow is needed to achieve a good level for the collected power. The scaling approach brings temporal analysis to all measurements and features: trend indices are calculated by comparing the averages in the long and short time windows, a weighted sum of the trend index and its derivative detects the trend episodes and severity of the trend is estimated by including also the variable level in the sum. The trend index, trend episodes and especially, the deviation index reveal early evolving changes in the operating conditions, including cloudiness and load disturbances. The solution is highly compact: all variables, features and indices are transformed to the range [-2, 2] and represented in natural language which is important in integrating data-driven solutions with domain expertise. The special situations detected during the test campaigns are explained well.

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Series: IOP conference series. Earth and environmental science
ISSN: 1755-1307
ISSN-E: 1755-1315
ISSN-L: 1755-1307
Issue: 136
Article number: 012007
DOI: 10.1088/1755-1315/136/1/012007
OADOI: https://oadoi.org/10.1088/1755-1315/136/1/012007
Host publication: 2017 6th International Conference on Power Science and Engineering (ICPSE 2017) 2–4 December 2017, St. Petersburg, Russian Federation
Conference: 6th International Conference on Power Science and Engineering (ICPSE 2017)
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
111 Mathematics
113 Computer and information sciences
222 Other engineering and technologies
119 Other natural sciences
Subjects:
Funding: Experiments were carried out within the project "Intelligent control and optimisation of solar collection with linguistic equations (ICOSLE)" as a part of the project "Solar Facilities for the European Research Area (SFERA)" supported by the 7th Framework Programme of the EU (SFERA Grant Agreement 228296).
Copyright information: Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Published under licence by IOP Publishing Ltd.
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