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Comparison of a non-parametric and parametric method for interharmonic estimation in PV systems
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.ORCID iD: 0000-0002-3587-7879
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.ORCID iD: 0000-0003-4079-4776
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science. (Electrical power engineering)ORCID iD: 0000-0002-4004-0352
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Energy Science.ORCID iD: 0000-0003-4074-9529
2019 (English)Conference paper, Published paper (Refereed)
Abstract [en]

A comparative analysis of ‘Desynchronized processing technique’ (non-parametric) and ‘Sliding window ESPRIT method’ (parametric) for interharmonic estimation in PV systems is carried out. Both methods were applied to field measurements and semi-measured signals to test their feasibility under different conditions. In Desynchronized processing technique, in the second stage of estimation, a Short-term Fourier transform was used to address the time-varying nature of interharmonics. In Sliding window ESPRIT method, the signal subspace dimension was fixed in all analysed cases. An adaptive algorithm was used to find the best rank of the Hankel matrix and apt order of the filter to ensure stability. A set of critical parameters affecting the performance of these methods in interharmonic estimation are identified. This paper emphasizes the significance of using appropriate methods for accurate interharmonic estimation and also demonstrates through the illustrated results that different inferences can be drawn for the same measurements analysed using different methods.

Place, publisher, year, edition, pages
2019.
Keywords [en]
Interharmonics, power system measurements, time-frequency analysis, Photovoltaic systems, Power quality.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electric Power Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-73360OAI: oai:DiVA.org:ltu-73360DiVA, id: diva2:1300791
Conference
13th IEEE PowerTech 2019
Funder
Swedish Energy AgencyAvailable from: 2019-03-29 Created: 2019-03-29 Last updated: 2019-05-20

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Ravindran, VineethaBusatto, TatianoRönnberg, SarahBollen, Math

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