Method of Automated Blind Control Based on PGSV Taking Account of Surrounding Objects

智子, 谷口; 利枝, 岩田; 大輔, 伊藤

doi:10.2150/jieij.98.211

Cited by 3 publications

(3 citation statements)

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“…Goovaerts et al (2017) informed that DGP underestimated the impact of direct sunlight, which generated the set-point lowered by users when direct sunlight was present. A similar problem was reported by Taniguchi et al (2012) when the algorithm to evaluate indoor luminance overestimated glare sources in the afternoon. Other authors have said people's glare sensation increases gradually from morning until midday but becomes stable or more sensitive to glare in the afternoon (Bian et al, 2020).…”

Section: Impact Of Occupant Response To Indoor Environmental Conditio...supporting

confidence: 73%

“…Some studies used the term "comfort" and "satisfaction" interchangeably (Cheng et al, 2013(Cheng et al, , 2016Lee et al, 1998;Sadeghi et al, 2016), while other studies used these terms to describe different states of mind. For instance, comfort was intended as the threshold or set-point that defines comfortable environmental conditions, which was often contrasted by surveys of the occupant perception to the environmental quality (Bakker et al, 2014;Cheng et al, 2013Cheng et al, , 2016Clear et al, 2006;Guillemin & Morel, 2001, 2002Kim et al, 2009;Lee et al, 2012;Meerbeek et al, 2014;Motamed et al, 2017;Sadeghi et al, 2016;Taniguchi et al, 2012;Vine et al, 1998). Satisfaction was used to indicate occupant contentment with the visual environment (Cheng et al, 2013(Cheng et al, , 2016Choi et al, 2019;Clear et al, 2006;Day et al, 2019;Guillemin & Morel, 2002;Karlsen et al, 2015;Kim et al, 2009;Lolli et al, 2019Lolli et al, , 2020Luna-Navarro et al, 2022;Meerbeek et al, 2014;Sadeghi et al, 2016;Vine et al, 1998), thermal environment (Choi et al, 2019;Clear et al, 2006;Day et al, 2019;Lolli et al, 2020;Luna-Navarro et al, 2022;Meerbeek et al, 2014;Sadeghi et al, 2016;…”

Section: Type Of Occupant Response To Af Studied Through Previous Workmentioning

confidence: 99%

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Influence of Automated Façades on Occupants

De la Barra,

Luna-Navarro,

Prieto

et al. 2022

JFDE

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Several studies performing building simulations showed that the automated control of façades can provide higher levels of indoor environmental quality and lower energy demand in buildings, in comparison to manually controlled scenarios. However, in several case studies with human volunteers, automated controls were found to be disruptive or unsatisfactory for occupants. For instance, automated façades became a source of dissatisfaction for occupants when they did not fulfil individual environmental requirements, did not provide personal control options, or did not correctly integrate occupant preferences with façade operation in energy-efficient controls. This article reviews current evidence from empirical studies with human volunteers to identify the key factors that affect occupant response to automated façades. Only twenty-six studies were found to empirically investigate occupant response to automated façades from 1998 onwards. Among the reviewed studies, five groups of factors were found to influence occupant interaction with automated façades and namely: (1) personal factors, (2) environmental conditions, (3) type and mode of operation, (4) type of façade technology, and (5) contextual factors.. Overall, occupant response to automated façades is often poorly considered in research studies reviewed because of the following three reasons: (i) the lack of established methods or procedures for assessing occupant response to automated façade controls, (ii) poor understanding of occupant multi-domain comfort preferences in terms of façade operation, (iii) fragmented research landscape, on one hand results are mainly related to similar contextual or climatic conditions, which undermines their applicability to other climates, while on the other hand the lack of replication within the same conditions, which also undermines replicability within the same condition. Lastly, this paper suggests future research directions to achieve a holistic and more comprehensive understanding of occupant response to automated façades, aiming to achieve more user-centric automated façade solutions and advanced control algorithms. In particular, research on the impact of personal factors on occupant satisfaction with automated controls is deemed paramount.

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Section: Impact Of Occupant Response To Indoor Environmental Conditio...supporting

confidence: 73%

Section: Type Of Occupant Response To Af Studied Through Previous Workmentioning

confidence: 99%

Influence of Automated Façades on Occupants

De la Barra,

Luna-Navarro,

Prieto

et al. 2022

JFDE

View full text Add to dashboard Cite

show abstract

“…However, this method alone is insufficient to avoid discomfort glare. 5 Researchers have proposed methods for predicting glare, such as the Daylight Glare Index(DGI), 6 Daylight Glare Probability(DGP), 7 and Predicted Glare Sensation Vote (PGSV), 8 which predict uncomfortable glare based on the luminance of the glare source and background. Visual sensors have also been used to detect glare sources, as demonstrated in Michael Kim et al's study 9 using a low-cost, window-mounted, and programmable High Dynamic Range Image (HDRI) sensor.…”

Section: Introductionmentioning

confidence: 99%

A novel blinds control approach based on dynamic radiance and solar radiation energy prediction

Li,

Zeng

2023

Building Services Engineering Research and Technology

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Automatic shading devices are widely employed in office buildings to enhance daylight comfort and reduce electricity consumption. However, conventional blinds control methods rely heavily on numerous sensors to monitor indoor daylight conditions, posing challenges in implementing automated control systems. A novel blinds control approach based on dynamic radiance and solar radiation energy prediction is proposed to address this issue. Instead of relying on illumination sensors, the method utilizes the Bidirectional Scattering Distribution Function (BSDF) and a sky model-based three-phase approach to calculate indoor illumination. Artificial neural networks are employed to predict transmitted solar radiation energy, thereby minimizing energy consumption. Furthermore, the multiple criteria decision-making model is applied to determine the optimal angle for the blinds. Simulation experiments demonstrated that this approach achieved a significant reduction of approximately 17% in energy consumption compared to a fixed angle of 90° in the cooling season. And the average illumination of the indoor work plane can be effectively maintained at the recommended level, as ensures improving occupants’ comfort. Practical Application: The proposed blinds control approach has practical applications in building automation control systems. By effectively reducing building energy consumption, it offers an efficient alternative to traditional control methods. Notably, this approach minimizes reliance on sensors, making it a cost-effective and sustainable solution for optimizing building energy usage.

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