https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
High-resolution estimates of diffuse fraction based on dynamic definitions of sky conditions
Cairo University, Giza, Giza, 12613, Egypt.
Cairo University, Giza, Giza, 12613, Egypt.
Cairo University, Giza, Giza, 12613, Egypt.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-1351-9245
Show others and affiliations
2021 (English)In: Renewable energy, ISSN 0960-1481, E-ISSN 1879-0682, Vol. 169, p. 641-659Article in journal (Refereed) Published
Abstract [en]

Accurate monitoring and operation of solar power systems require high-resolution solar radiation measurements and precise separation models. This study aims to improve the accuracy of classic diffuse fraction-clearness index piecewise separation models by applying data-driven classifications of sky conditions. This is achieved through a novel outlier-insensitive clustering algorithm and shape prescriptive modeling, applied to 1-, 10-, 30-, and 60-min ground measurements from 4 different locations in the MENA region. This study shows that classifications of sky conditions are not uniform among the selected locations even though all stations fall in the arid desert climate category. This highlights the importance of extracting the sky conditions from measurements rather than using available classifications in the literature. The selection of the number of clusters has to undergo optimization. The number of clusters is also a function of the time resolution. One of the selected locations shows four optimal clusters for 1-min data and six clusters for 60-min data. All developed piecewise separation models show high accuracy and stability with the mean bias errors approaching zero values and the mean absolute errors ranging between 8.7 and 11.8%. The models also outperform existing ones and have good generalization capabilities under the same climate classification. 

Place, publisher, year, edition, pages
Elsevier Ltd , 2021. Vol. 169, p. 641-659
Keywords [en]
Diffuse fraction, Diffuse horizontal irradiance, K-medoids clustering, One-minute observations, Piecewise model, Solar radiation
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:mdh:diva-53223DOI: 10.1016/j.renene.2021.01.066ISI: 000621819400009Scopus ID: 2-s2.0-85099637046OAI: oai:DiVA.org:mdh-53223DiVA, id: diva2:1523464
Available from: 2021-01-28 Created: 2021-01-28 Last updated: 2021-03-25Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Campana, Pietro Elia

Search in DiVA

By author/editor
Campana, Pietro Elia
By organisation
Future Energy Center
In the same journal
Renewable energy
Energy Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 106 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf