IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v81y2015icp15-20.html
   My bibliography  Save this article

Comparison of sensorless dimming control based on building modeling and solar power generation

Author

Listed:
  • Lee, Naeun
  • Kim, Jonghun
  • Jang, Cheolyong
  • Sung, Yoondong
  • Jeong, Hakgeun

Abstract

Artificial lighting in office buildings accounts for about 30% of the total building energy consumption. Lighting energy is important to reduce building energy consumption since artificial lighting typically has a relatively large energy conversion factor. Therefore, previous studies have proposed a dimming control using daylight. When applied dimming control, method based on building modeling does not need illuminance sensors. Thus, it can be applied to existing buildings that do not have illuminance sensors. However, this method does not accurately reflect real-time weather conditions. On the other hand, solar power generation from a PV (photovoltaic) panel reflects real-time weather conditions. The PV panel as the sensor improves the accuracy of dimming control by reflecting disturbance. Therefore, we compared and analyzed two types of sensorless dimming controls: those based on the building modeling and those that based on solar power generation using PV panels.

Suggested Citation

  • Lee, Naeun & Kim, Jonghun & Jang, Cheolyong & Sung, Yoondong & Jeong, Hakgeun, 2015. "Comparison of sensorless dimming control based on building modeling and solar power generation," Energy, Elsevier, vol. 81(C), pages 15-20.
  • Handle: RePEc:eee:energy:v:81:y:2015:i:c:p:15-20
    DOI: 10.1016/j.energy.2014.10.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544214011761
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2014.10.027?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ahn, Byung-Lip & Jang, Cheol-Yong & Leigh, Seung-Bok & Yoo, Seunghwan & Jeong, Hakgeun, 2014. "Effect of LED lighting on the cooling and heating loads in office buildings," Applied Energy, Elsevier, vol. 113(C), pages 1484-1489.
    2. Chel, Arvind & Tiwari, G.N. & Singh, H.N., 2010. "A modified model for estimation of daylight factor for skylight integrated with dome roof structure of mud-house in New Delhi (India)," Applied Energy, Elsevier, vol. 87(10), pages 3037-3050, October.
    3. Chow, Stanley K.H. & Li, Danny H.W. & Lee, Eric W.M. & Lam, Joseph C., 2013. "Analysis and prediction of daylighting and energy performance in atrium spaces using daylight-linked lighting controls," Applied Energy, Elsevier, vol. 112(C), pages 1016-1024.
    4. Li, Danny H.W. & Wong, S.L., 2007. "Daylighting and energy implications due to shading effects from nearby buildings," Applied Energy, Elsevier, vol. 84(12), pages 1199-1209, December.
    5. Li, Danny H.W. & Cheung, K.L. & Wong, S.L. & Lam, Tony N.T., 2010. "An analysis of energy-efficient light fittings and lighting controls," Applied Energy, Elsevier, vol. 87(2), pages 558-567, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ignacio Acosta & Miguel Ángel Campano & Samuel Domínguez-Amarillo & Carmen Muñoz, 2018. "Dynamic Daylight Metrics for Electricity Savings in Offices: Window Size and Climate Smart Lighting Management," Energies, MDPI, vol. 11(11), pages 1-27, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu, Xu & Su, Yuehong, 2015. "Daylight availability assessment and its potential energy saving estimation –A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 494-503.
    2. Mangkuto, R.A. & Wang, S. & Meerbeek, B.W. & Aries, M.B.C. & van Loenen, E.J., 2014. "Lighting performance and electrical energy consumption of a virtual window prototype," Applied Energy, Elsevier, vol. 135(C), pages 261-273.
    3. Chow, Stanley K.H. & Li, Danny H.W. & Lee, Eric W.M. & Lam, Joseph C., 2013. "Analysis and prediction of daylighting and energy performance in atrium spaces using daylight-linked lighting controls," Applied Energy, Elsevier, vol. 112(C), pages 1016-1024.
    4. Acosta, Ignacio & Campano, Miguel Ángel & Molina, Juan Francisco, 2016. "Window design in architecture: Analysis of energy savings for lighting and visual comfort in residential spaces," Applied Energy, Elsevier, vol. 168(C), pages 493-506.
    5. Han, Yilong & Taylor, John E. & Pisello, Anna Laura, 2017. "Exploring mutual shading and mutual reflection inter-building effects on building energy performance," Applied Energy, Elsevier, vol. 185(P2), pages 1556-1564.
    6. Alrubaih, M.S. & Zain, M.F.M. & Alghoul, M.A. & Ibrahim, N.L.N. & Shameri, M.A. & Elayeb, Omkalthum, 2013. "Research and development on aspects of daylighting fundamentals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 494-505.
    7. Li, Danny H.W. & Lou, Siwei & Lam, Joseph C. & Wu, Ronald H.T., 2016. "Determining solar irradiance on inclined planes from classified CIE (International Commission on Illumination) standard skies," Energy, Elsevier, vol. 101(C), pages 462-470.
    8. Li, Danny H.W., 2010. "A review of daylight illuminance determinations and energy implications," Applied Energy, Elsevier, vol. 87(7), pages 2109-2118, July.
    9. Mangkuto, Rizki A. & Rohmah, Mardliyahtur & Asri, Anindya Dian, 2016. "Design optimisation for window size, orientation, and wall reflectance with regard to various daylight metrics and lighting energy demand: A case study of buildings in the tropics," Applied Energy, Elsevier, vol. 164(C), pages 211-219.
    10. Tettey, Uniben Yao Ayikoe & Dodoo, Ambrose & Gustavsson, Leif, 2016. "Primary energy implications of different design strategies for an apartment building," Energy, Elsevier, vol. 104(C), pages 132-148.
    11. Acosta, Ignacio & Varela, Carmen & Molina, Juan Francisco & Navarro, Jaime & Sendra, Juan José, 2018. "Energy efficiency and lighting design in courtyards and atriums: A predictive method for daylight factors," Applied Energy, Elsevier, vol. 211(C), pages 1216-1228.
    12. Chitnis, Dipti & Thejo kalyani, N. & Swart, H.C. & Dhoble, S.J., 2016. "Escalating opportunities in the field of lighting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 727-748.
    13. Ramos, Greici & Ghisi, Enedir, 2010. "Analysis of daylight calculated using the EnergyPlus programme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 1948-1958, September.
    14. Li, Danny H.W. & Lou, Siwei, 2018. "Review of solar irradiance and daylight illuminance modeling and sky classification," Renewable Energy, Elsevier, vol. 126(C), pages 445-453.
    15. Jianhua Ding & Xinyi Zou & Murong Lv, 2023. "Influence of Opposing Exterior Window Geometry on the Carbon Emissions of Indoor Lighting under the Combined Effect of Natural Lighting and Artificial Lighting in the City of Shenyang, China," Sustainability, MDPI, vol. 15(17), pages 1-20, August.
    16. Sara Eriksson & Lovisa Waldenström & Max Tillberg & Magnus Österbring & Angela Sasic Kalagasidis, 2019. "Numerical Simulations and Empirical Data for the Evaluation of Daylight Factors in Existing Buildings in Sweden," Energies, MDPI, vol. 12(11), pages 1-24, June.
    17. Ruparathna, Rajeev & Hewage, Kasun & Sadiq, Rehan, 2016. "Improving the energy efficiency of the existing building stock: A critical review of commercial and institutional buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1032-1045.
    18. Giovani Almeida Dávi & José López de Asiain & Juan Solano & Estefanía Caamaño-Martín & César Bedoya, 2017. "Energy Refurbishment of an Office Building with Hybrid Photovoltaic System and Demand-Side Management," Energies, MDPI, vol. 10(8), pages 1-24, August.
    19. Evangelos-Nikolaos D. Madias & Lambros T. Doulos & Panagiotis A. Kontaxis & Frangiskos V. Topalis, 2022. "Multicriteria decision aid analysis for the optimum performance of an ambient light sensor: methodology and case study," Operational Research, Springer, vol. 22(2), pages 1333-1361, April.
    20. Aiman Albatayneh & Adel Juaidi & Ramez Abdallah & Francisco Manzano-Agugliaro, 2021. "Influence of the Advancement in the LED Lighting Technologies on the Optimum Windows-to-Wall Ratio of Jordanians Residential Buildings," Energies, MDPI, vol. 14(17), pages 1-20, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:81:y:2015:i:c:p:15-20. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.