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Development of a solar irradiance dataset for Oahu, Hawai'i

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  • Williamson, Sarah
  • Businger, Steven
  • Matthews, Dax

Abstract

Solar power as an alternative energy source in Hawai'i has grown in recent years [1], with increasing amounts of photovoltaic panels found statewide. Power resource management and grid stability require that the variability in irradiance, hence, solar power coming into the electric grid be understood. The aim of this study is to produce an irradiance dataset for Oahu, Hawai'i, containing temporal and spatial variability, so it can be used in modeling power generation.

Suggested Citation

  • Williamson, Sarah & Businger, Steven & Matthews, Dax, 2018. "Development of a solar irradiance dataset for Oahu, Hawai'i," Renewable Energy, Elsevier, vol. 128(PA), pages 432-443.
    • Handle: RePEc:eee:renene:v:128:y:2018:i:pa:p:432-443
    DOI: 10.1016/j.renene.2018.05.082
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    References listed on IDEAS

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    1. Kariuki, Boniface Wainaina & Sato, Tomonori, 2018. "Interannual and spatial variability of solar radiation energy potential in Kenya using Meteosat satellite," Renewable Energy, Elsevier, vol. 116(PA), pages 88-96.
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    1. Fernando Venâncio Mucomole & Carlos Augusto Santos Silva & Lourenço Lázaro Magaia, 2024. "Regressive and Spatio-Temporal Accessibility of Variability in Solar Energy on a Short Scale Measurement in the Southern and Mid Region of Mozambique," Energies, MDPI, vol. 17(11), pages 1-29, May.
    2. Llinet Benavides Cesar & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira & Ramon Alcarria, 2023. "CyL-GHI: Global Horizontal Irradiance Dataset Containing 18 Years of Refined Data at 30-Min Granularity from 37 Stations Located in Castile and León (Spain)," Data, MDPI, vol. 8(4), pages 1-21, March.
    3. Nunes Maciel, Joylan & Javier Gimenez Ledesma, Jorge & Hideo Ando Junior, Oswaldo, 2024. "Hybrid prediction method of solar irradiance applied to short-term photovoltaic energy generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    4. Joylan Nunes Maciel & Jorge Javier Gimenez Ledesma & Oswaldo Hideo Ando Junior, 2024. "Dataset for Machine Learning: Explicit All-Sky Image Features to Enhance Solar Irradiance Prediction," Data, MDPI, vol. 9(10), pages 1-12, September.

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