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

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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
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    References listed on IDEAS

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    1. 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.
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    3. 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.
    4. 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.
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    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.

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