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The Journal of the Illuminating Engineering Society
Volume 7, 2010 - Issue 1
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Original Articles

Saving Energy with Highly-Controlled Lighting in an Open-Plan Office

Francis RubinsteinLawrence Berkeley National Laboratory
, FIES &
Abby EnscoeLawrence Berkeley National LaboratoryCorrespondence[email protected]
Pages 21-36 | Published online: 16 Sep 2013

Citations (18)

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Read on this site (3)

Brodie W. Hobson, Brent Huchuk, H. Burak Gunay & William O’Brien. (2021) A workflow for evaluating occupant-centric controls using building simulation. Journal of Building Performance Simulation 14:6, pages 730-748.
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Daniel Lowcay, H. Burak Gunay & William O’Brien. (2020) Simulating energy savings potential with high-resolution daylight and occupancy sensing in open-plan offices. Journal of Building Performance Simulation 13:5, pages 606-619.
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William O'Brien & H. Burak Gunay. (2019) Do building energy codes adequately reward buildings that adapt to partial occupancy?. Science and Technology for the Built Environment 25:6, pages 678-691.
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Articles from other publishers (15)

Tareq Abuimara, Brodie W Hobson, Burak Gunay & William O’Brien. (2022) A data-driven workflow to improve energy efficient operation of commercial buildings: A review with real-world examples. Building Services Engineering Research and Technology 43:4, pages 517-534.
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Farzam Kharvari, Sara Azimi & William O’Brien. (2021) A comprehensive simulation-based assessment of office building performance adaptability to teleworking scenarios in different Canadian climate zones. Building Simulation 15:6, pages 995-1014.
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Yuan Jin, Da Yan, Xingxing Zhang, Jingjing An & Mengjie Han. (2020) A data-driven model predictive control for lighting system based on historical occupancy in an office building: Methodology development. Building Simulation 14:1, pages 219-235.
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Govind B. Nair & S.J. Dhoble. 2021. The Fundamentals and Applications of Light-Emitting Diodes. The Fundamentals and Applications of Light-Emitting Diodes 155 176 .
Yuan Jin, Da Yan, Xingxing Zhang, Jingjing An & Mengjie Han. 2021. Data-driven Analytics for Sustainable Buildings and Cities. Data-driven Analytics for Sustainable Buildings and Cities 93 114 .
Seddigheh Norouziasl & Amirhosein Jafari. (2020) Comparing Office Layouts Regarding Lighting Energy Saving Potentials Using Agent-Based Real-Time Simulation of Occupancy Behavioral Patterns. Comparing Office Layouts Regarding Lighting Energy Saving Potentials Using Agent-Based Real-Time Simulation of Occupancy Behavioral Patterns.
Sascha Hammes, Johannes Weninger, Markus Canazei, Rainer Pfluger & Wilfried Pohl. (2020) Die Bedeutung von Nutzerzentrierung in automatisierten Beleuchtungssystemen. Bauphysik 42:5, pages 209-217.
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Jeremy Snyder. (2020) Energy-saving strategies for luminaire-level lighting controls. Building and Environment 169.
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Shide Salimi & Amin Hammad. (2019) Critical review and research roadmap of office building energy management based on occupancy monitoring. Energy and Buildings 182, pages 214-241.
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Christel de Bakker, Mariëlle Aarts, Helianthe Kort & Alexander Rosemann. (2018) The feasibility of highly granular lighting control in open-plan offices: Exploring the comfort and energy saving potential. Building and Environment 142, pages 427-438.
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A Pandharipande & GR Newsham. (2018) Lighting controls: Evolution and revolution. Lighting Research & Technology 50:1, pages 115-128.
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Christel de Bakker, Myriam Aries, Helianthe Kort & Alexander Rosemann. (2017) Occupancy-based lighting control in open-plan office spaces: A state-of-the-art review. Building and Environment 112, pages 308-321.
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D Caicedo & A Pandharipande. (2016) Daylight and occupancy adaptive lighting control system: An iterative optimization approach. Lighting Research & Technology 48:6, pages 661-675.
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Mustafa Sahin, Yuksel Oguz & Fuat Buyuktumturk. (2015) Approximate and Three-Dimensional Modeling of Brightness Levels in Interior Spaces by Using Artificial Neural Networks. Journal of Electrical Engineering and Technology 10:4, pages 1822-1829.
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Raphaela Walger da Fonseca, Evelise Leite Didoné & Fernando Oscar Ruttkay Pereira. (2013) Using artificial neural networks to predict the impact of daylighting on building final electric energy requirements. Energy and Buildings 61, pages 31-38.
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