Achieving energy and cost savings through simple daylighting control in tropical historic buildings

Kamaruzzaman, Syahrul Nizam; Edwards, Rodger; Zawawi, Emma Marinie Ahmad; Che‐Ani, Adi Irfan

doi:10.1016/j.enbuild.2014.12.045

Cited by 27 publications

(10 citation statements)

References 25 publications

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“…Moreover, the (DF) is used for indication of daylight availability in each room. The DF = , where is the internal illuminance and is the external illumina on the horizontal plane from the whole of an unobstructed CIE International Commission on Illumination [7,30,46].…”

Section: Experimental Results Analysis and Findingsmentioning

confidence: 99%

Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

Kaminska

Ożadowicz

2018

Energies

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Energy used for lighting is one of the major components of total energy consumption in buildings. Nowadays, buildings have a great potential to reduce their energy consumption, but to achieve this purpose additional efforts are indispensable. In this study, the need for energy savings evaluation before the implementation of lighting control algorithms for a specified building is highlighted. Therefore, experimental tests have been carried out in a university building with laboratories and other rooms, equipped with KNX building automation system. A dimmable control strategy has been investigated, dependent on daylight illuminance. Moreover, a relationship between external and internal daylight illuminance levels has been evaluated as well. Based on the experimental results, the authors proposed a method for the rough estimation of electrical energy savings. Since, according to the EN 15232 standard, Building Automation and Control Systems (BACS) play an important role in buildings’ energy efficiency improvements, the BACS efficiency factors from this standard have been used to verify the experimental results presented in the paper. The potential to reduce energy consumption from lighting in non-residential buildings by 28% for offices and 24% for educational buildings has been confirmed, but its dependence on specific building parameters has been discussed as well.

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Section: Experimental Results Analysis and Findingsmentioning

confidence: 99%

Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

Kaminska

Ożadowicz

2018

Energies

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“…The study by Shoubi et al [22] examined energy performance in several cases/scenarios for building, climate, and environmental conditions as well as HVAC systems by involving various information models and building physical conditions. The study by Kamaruzzaman et al [23] analyzed energy and cost savings by controlling daylight in historical buildings in tropical areas. This study stated that lighting consumption in buildings can be influenced by building use, daytime electricity usage, lighting levels and hours of use.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy Analysis of the Educational Building in Palembang Indonesia

Fitriani¹,

Rifki²,

Indriyati³

et al. 2021

cea

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“…While the introduction of daylight in buildings can be used to indirectly offset electric lighting usage through the use of sensors and control systems (i.e., dimmers and illuminance sensors) (Kamaruzzaman et al, 2015;Xue et al, 2016), this is not only dependent on whether the daylight can meet -and does not exceed -the design illuminance value but also on its spatial distribution throughout the entire occupied space. In fact, Yun et al (Yun et al, 2012) suggests that energy use from artificial light can be reduced by 30 % when lighting controls are carefully designed in relation to indoor daylight distribution levels.…”

Section: Introductionmentioning

confidence: 99%

A dimensionality reduction method to select the most representative daylight illuminance distributions

Kent

Schiavon

Jakubiec

2020

Journal of Building Performance Simulation

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One challenge when evaluating daylight distribution is dealing with the large amount of temporal and spatial data, visualisations and variability in illuminances that are assessed in buildings. Using a dimensionality reduction method based on principal component analysis, we identified the most representative annual daylight distributions. We modelled a rectangular room containing an analysis grid of 3200 illuminance sensor points and simulated 3285 different temporal daylight conditions using an annual occupancy schedule ranging from 08:00 to 17:00 with one-hour sampling intervals in two locations: Singapore and Oakland, California. Our approach explained 98 % of the illuminance variability with three daylight distributions in Singapore, and 92 % using six in Oakland, California. Our dimensionality reduction strategy was also generalised using a complex building geometry showing the utility of the method. We think this approach can be used to provide a more efficient and reliable method to analyse daylight performance in building practice.

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Achieving energy and cost savings through simple daylighting control in tropical historic buildings

Cited by 27 publications

References 25 publications

Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

Energy Analysis of the Educational Building in Palembang Indonesia

A dimensionality reduction method to select the most representative daylight illuminance distributions

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