⧉⌕$post array (20)
⇄datum => string (10) "22.09.2023"
$post['datum']
⇄⧉veroeffentlichungsart => array (10)
$post['veroeffentlichungsart']
⇄term_id => integer 836
$post['veroeffentlichungsart']['term_id']
⇄name => string (46) "Beitrag zu wissenschaftlicher Konferenz/Tagung"
$post['veroeffentlichungsart']['name']
⇄slug => string (50) "417_beitrag-zu-wissenschaftlicher-konferenz-tagung"
$post['veroeffentlichungsart']['slug']
⇄term_group => integer 0
$post['veroeffentlichungsart']['term_group']
⇄term_taxonomy_id => integer 836
$post['veroeffentlichungsart']['term_taxonomy_id']
⇄taxonomy => string (21) "veroeffentlichungsart"
$post['veroeffentlichungsart']['taxonomy']
⇄description => string (0) ""
$post['veroeffentlichungsart']['description']
⇄parent => integer 0
$post['veroeffentlichungsart']['parent']
⇄count => integer 198
$post['veroeffentlichungsart']['count']
⇄filter => string (3) "raw"
$post['veroeffentlichungsart']['filter']
⇄⧉forschungsschwerpunkt => array (10)
$post['forschungsschwerpunkt']
⇄term_id => integer 898
$post['forschungsschwerpunkt']['term_id']
⇄name => UTF-8 string (60) "HRK Schwerpunkt Nachhaltige Mobilitäts- und Energiekonzepte"
$post['forschungsschwerpunkt']['name']
⇄slug => string (63) "156_hrk-schwerpunkt-nachhaltige-mobilitaets-und-energiekonzepte"
$post['forschungsschwerpunkt']['slug']
⇄term_group => integer 0
$post['forschungsschwerpunkt']['term_group']
⇄term_taxonomy_id => integer 898
$post['forschungsschwerpunkt']['term_taxonomy_id']
⇄taxonomy => string (21) "forschungsschwerpunkt"
$post['forschungsschwerpunkt']['taxonomy']
⇄description => string (0) ""
$post['forschungsschwerpunkt']['description']
⇄parent => integer 0
$post['forschungsschwerpunkt']['parent']
⇄count => integer 45
$post['forschungsschwerpunkt']['count']
⇄filter => string (3) "raw"
$post['forschungsschwerpunkt']['filter']
⇄⧉autoren => array (3)
$post['autoren']
  • Table (3)
  • Contents (3)
  • namelinkinternpersonenkennziffer
    0Maximilian Schönautrue
    1Bernd Hüttlhttps://www.hs-coburg.de/personen/prof-dr-bernd-huettl/true
    2Dieter Landeshttps://www.hs-coburg.de/personen/prof-dr-dieter-landes/true
  • ⇄⧉0 => array (4)
    $post['autoren'][0]
    ⇄name => UTF-8 string (19) "Maximilian Schönau"
    $post['autoren'][0]['name']
    ⇄link => string (0) ""
    $post['autoren'][0]['link']
    ⇄intern => boolean true
    $post['autoren'][0]['intern']
    ⇄personenkennziffer => string (0) ""
    $post['autoren'][0]['personenkennziffer']
    ⇄⧉1 => array (4)
    $post['autoren'][1]
    ⇄name => UTF-8 string (12) "Bernd Hüttl"
    $post['autoren'][1]['name']
    ⇄link => string (55) "https://www.hs-coburg.de/personen/prof-dr-bernd-huettl/"
    $post['autoren'][1]['link']
    ⇄intern => boolean true
    $post['autoren'][1]['intern']
    ⇄personenkennziffer => string (0) ""
    $post['autoren'][1]['personenkennziffer']
    ⇄⧉2 => array (4)
    $post['autoren'][2]
    ⇄name => string (13) "Dieter Landes"
    $post['autoren'][2]['name']
    ⇄link => string (56) "https://www.hs-coburg.de/personen/prof-dr-dieter-landes/"
    $post['autoren'][2]['link']
    ⇄intern => boolean true
    $post['autoren'][2]['intern']
    ⇄personenkennziffer => string (0) ""
    $post['autoren'][2]['personenkennziffer']
⇄⧉titel => string (85) "Improving IV Curve Classification by Machine Learning Methods Using Deep Aut...
$post['titel']
Improving IV Curve Classification by Machine Learning Methods Using Deep Autoencoders
⇄medien => string (65) "Proceedings of 40th European Photovoltaic Solar Energy Conference"
$post['medien']
⇄doi => string (0) ""
$post['doi']
⇄⧉weblink => string (136) "https://www.researchgate.net/publication/373545457_Improving_IV_Curve_Classi...
$post['weblink']
https://www.researchgate.net/publication/373545457_Improving_IV_Curve_Classification_by_Machine_Learning_Methods_Using_Deep_Autoencoders
⇄⧉abstract => string (1188) "<p>On-site current-voltage (IV) measurements will play an essential role in ...
$post['abstract']
<p>On-site current-voltage (IV) measurements will play an essential role in the online monitoring of PV systems. However, challenging measurement conditions like inconsistent irradiance levels on PV arrays (e.g., due to local shading) can distort IV curves, leading to inaccurate characterizations. By accurately detecting deformed IV curves, the reliability of both on-site and remote IV measurements is significantly enhanced. For this purpose, several classifiers were evaluated using 4104 manually labeled IV measurements on a mc-Si-PV array. Machine learning tech-niques perform much better than a traditional rule-based filter, with accuracy above 99 %. A deep Autoencoder was employed to reduce IV measurements into a set of 7 features, which encoded the shape of the curves into a low dimen-sionality. The IV-Autoencoder improved the classification of IV curves, yielding better results than a feature reduction with Principal Component Analysis. The proposed classifiers are able to sort out on-site IV measurements under un-satisfactory environmental conditions, benefiting the online monitoring of PV systems. It may also be used as an indi-cator for faulty PV strings.<br></p>
⇄heft => string (0) ""
$post['heft']
⇄band => string (4) "2023"
$post['band']
⇄artikelnummer => string (0) ""
$post['artikelnummer']
⇄isbn => string (0) ""
$post['isbn']
⇄herausgeber => string (0) ""
$post['herausgeber']
⇄seiten => string (0) ""
$post['seiten']
⇄open_access => null
$post['open_access']
⇄peer_reviewed => boolean false
$post['peer_reviewed']
⇄detailseite => boolean true
$post['detailseite']
⇄⧉zitierung => UTF-8 string (218) "Schönau, Maximilian; Hüttl, Bernd; Landes, Dieter (2023): Improving IV Curve...
$post['zitierung']
Schönau, Maximilian; Hüttl, Bernd; Landes, Dieter (2023): Improving IV Curve Classification by Machine Learning Methods Using Deep Autoencoders. Proceedings of 40th European Photovoltaic Solar Energy Conference 2023.
⇄⧉permalink => string (128) "https://www.hs-coburg.de/publikation/4247-improving-iv-curve-classification-...
$post['permalink']
https://www.hs-coburg.de/publikation/4247-improving-iv-curve-classification-by-machine-learning-methods-using-deep-autoencoders/
⧉ Called from <ROOT>/wp-content/themes/Avada-Child-Theme/inc/bayfis-content.php:57 [d()]
  1. <ROOT>/wp-includes/shortcodes.php:434 [render_acf_publikation_content()]
  2. <ROOT>/wp-includes/shortcodes.php:273 [preg_replace_callback()]
  3. <ROOT>/wp-content/plugins/fusion-builder/shortcodes/fusion-code-block.php:45 [do_shortcode()]
  4. <ROOT>/wp-includes/shortcodes.php:434 [FusionSC_Code_Block->render()]
  5. <ROOT>/wp-includes/shortcodes.php:273 [preg_replace_callback()]
  6. <ROOT>/wp-content/plugins/fusion-builder/inc/class-fusion-column-element.php:588 [do_shortcode()]
  7. <ROOT>/wp-includes/shortcodes.php:434 [Fusion_Column_Element->render()]
  8. <ROOT>/wp-includes/shortcodes.php:273 [preg_replace_callback()]
  9. <ROOT>/wp-content/plugins/fusion-builder/inc/class-fusion-row-element.php:123 [do_shortcode()]
  10. <ROOT>/wp-includes/shortcodes.php:434 [Fusion_Row_Element->render()]
  11. <ROOT>/wp-includes/shortcodes.php:273 [preg_replace_callback()]
  12. <ROOT>/wp-content/plugins/fusion-builder/shortcodes/fusion-container.php:1095 [do_shortcode()]
  13. <ROOT>/wp-includes/shortcodes.php:434 [FusionSC_Container->render()]
  14. <ROOT>/wp-includes/shortcodes.php:273 [preg_replace_callback()]
  15. <ROOT>/wp-includes/class-wp-hook.php:324 [do_shortcode()]
  16. <ROOT>/wp-includes/plugin.php:205 [WP_Hook->apply_filters()]
  17. <ROOT>/wp-content/plugins/fusion-builder/inc/class-fusion-template-builder.php:1554 [apply_filters()]
  18. <ROOT>/wp-content/plugins/fusion-builder/inc/class-fusion-template-builder.php:1186 [Fusion_Template_Builder->render_content()]
  19. <ROOT>/wp-includes/class-wp-hook.php:324 [Fusion_Template_Builder->render_content_override()]
  20. <ROOT>/wp-includes/class-wp-hook.php:348 [WP_Hook->apply_filters()]
  21. <ROOT>/wp-includes/plugin.php:517 [WP_Hook->do_action()]
  22. <ROOT>/wp-content/plugins/fusion-builder/templates/template-page.php:23 [do_action()]
  23. <ROOT>/wp-includes/template-loader.php:106
  24. <ROOT>/wp-blog-header.php:18
  25. <ROOT>/index.php:30

The website of Coburg University of Applied Sciences was translated using translation software provided by a third-party provider such as DeepL. The official text is the German version of the website. No liability is assumed, either explicitly or implicitly, for the accuracy, reliability, or correctness of the translations into another language.

Improving IV Curve Classification by Machine Learning Methods Using Deep Autoencoders

On-site current-voltage (IV) measurements will play an essential role in the online monitoring of PV systems. However, challenging measurement conditions like inconsistent irradiance levels on PV arrays (e.g., due to local shading) can distort IV curves, leading to inaccurate characterizations. By accurately detecting deformed IV curves, the reliability of both on-site and remote IV measurements is significantly enhanced. For this purpose, several classifiers were evaluated using 4104 manually labeled IV measurements on a mc-Si-PV array. Machine learning tech-niques perform much better than a traditional rule-based filter, with accuracy above 99 %. A deep Autoencoder was employed to reduce IV measurements into a set of 7 features, which encoded the shape of the curves into a low dimen-sionality. The IV-Autoencoder improved the classification of IV curves, yielding better results than a feature reduction with Principal Component Analysis. The proposed classifiers are able to sort out on-site IV measurements under un-satisfactory environmental conditions, benefiting the online monitoring of PV systems. It may also be used as an indi-cator for faulty PV strings.

Titel:

Improving IV Curve Classification by Machine Learning Methods Using Deep Autoencoders

Veröffentlichungsdatum:

22.09.2023

Publikationsart:

Beitrag zu wissenschaftlicher Konferenz/Tagung

Forschungsschwerpunkt:

HRK Schwerpunkt Nachhaltige Mobilitäts- und Energiekonzepte

Medien:

Proceedings of 40th European Photovoltaic Solar Energy Conference

DOI:

Weblink:

https://www.researchgate.net/publication/373545457_Improving_IV_Curve_Classification_by_Machine_Learning_Methods_Using_Deep_Autoencoders

Heft:

Band:

2023

Artikelnummer:

ISBN:

Autoren:

Maximilian Schönau, Bernd Hüttl, Dieter Landes

Medien:

Proceedings of 40th European Photovoltaic Solar Energy Conference

Herausgeber:

Seiten:

Open Access:

Peer reviewed:

Nein

Zitierung:

Schönau, Maximilian; Hüttl, Bernd; Landes, Dieter (2023): Improving IV Curve Classification by Machine Learning Methods Using Deep Autoencoders. Proceedings of 40th European Photovoltaic Solar Energy Conference 2023.

Autoren:

Maximilian Schönau, Bernd Hüttl, Dieter Landes