Evaluating annual solar heat gains from manually operated shading system

Abstract

Predicting occupant behaviour is vital to ensure energy performance in the built environment. Several studies reported discrepancies between the predicted and actual occupant behaviour in buildings, including that towards manual solar shading systems. This results in an energy performance gap between predicted and actual energy use in buildings.

In this research, the self-reported use of manual shading for an office building in Gothenburg, Sweden was combined with a user survey on the luminous environment. The scope of the study was: 1) to understand the actual use of shading, and 2) to understand the actual drivers leading to action on shading systems. Based on the outcomes, a simple prediction model for the use of a manually operated shading system is built for the specific case study. This prediction model was used to estimate the impact of occupant behaviour on annual solar heat gains through a manual solar shading system. The performance of a manually operated solar shading system based on the prediction model was compared to an automated solar shading system.

In concluding this research, the difference in the performance of manual and automated solar shading systems is defined for the provided case. The study shows that occupant behaviour on the shading system has a negative impact on the building cooling load. It is found that a manually operated shading system can lead to 25 % or higher unwanted solar heat gains in the studied building due to fewer blind movements. The results also show that without proper inclusion of occupant behaviour in building energy rating calculation, it is highly possible to have a performance gap between predicted and actual building energy use. The findings of this research may contribute to the understanding and development of a behaviour model for shading systems based on glare as a control strategy.

Popular Abstract

In recent years, there has been a predominant focus on studies related to occupant behaviour and their impact on building energy use. Solar shading systems are one of the building systems where occupant behaviour plays a major role in the efficiency of the system to help reduce the building energy use. The lack of research investigating occupant behaviour on solar shading systems and studies on understanding and predicting the impact of occupant behaviour on building energy use leads to a performance gap between the predicted and actual building energy use.

The existing standard behaviour models for the use of solar shading devices are based on the control strategies of solar radiation or indoor temperature. According to the literature review, minimizing glare and visual discomfort is the primary driving force for occupants to close blinds. Hence, it was important to develop a prediction model for the manually operated solar shading use based on glare as a control strategy to measure the impact of occupant behaviour.
This research aimed to understand the impact of occupant behaviour on annual solar heat gains by developing a realistic shading position prediction model with respect to the standard behavioural models. A highly glazed office building located in Gothenburg, Sweden which uses a manually operated shading system was studied for the purpose of this research. The existing daylight and visual comfort of the building were studied with the help of a climate-based daylight model. The climate-based daylight model was verified by capturing HDR images on-site and comparing them with the simulated HDR images from the Radiance engine. The DGP value at each occupants’ desk from the verified climate-based model was later used in the prediction model to find the shade positions.

The study dealt with understanding the drivers leading to the use of a manually operated shading system in the studied office building. This was carried out by a series of surveys and self-reported occupant behaviour on the solar shading system. The shading position prediction model was built from this data, and it was tested to verify its reliability of the prediction model.

The results from the verified prediction model were later used in the second part of the study to calculate the annual solar heat gains from the manually operated shading system. Determining the solar factor of the glazing system with shading devices in a partially open/close state is not possible. Hence, assumptions and simplifications were made to the method of calculating annual solar heat gains through a manually operated shading system. Instead of a reduction in solar factor with the presence of a shading device, a reduction in the solar irradiance which was simulated from Honeybee was considered. The reduction of solar irradiation on the glazing surface with internal blinds was considered to be proportionate to the solar irradiance on a glazing surface with the external blinds. While this simplification makes the result inaccurate and underestimates the annual solar heat gains for the internal manually operated shading system, it indicates the effect of occupant behaviour on the building heating and cooling loads. The results from the calculations were compared with a hypothetical case where the building used an automated shading system in place of a manually operated shading system. It was considered that the automated shading system worked on the basis of control of solar radiation with a threshold of 150 W/m2.

Overall, the results from both parts of the study show that the automated shading system is the most active system in comparison to the manually operated shading system. It was determined by defining two new indices for the blind movement in the building, i.e., Blind use frequency (BUF) and number of blind movement (NBM). The calculation of annual solar heat gains also showed that the solar heat gains between the vernal to autumnal equinox increases by 25 % with the use of a manually operated shading system in comparison to the considered automated shading system. It is also noted that the manually operated shading system can increase the solar heat gains by 9 % in the winter period, that is from autumnal to vernal equinox. Thus, it can be said that even though occupants have higher degree of satisfaction on daylighting when they have more control over the shading system, the occupant behaviour has a negative impact on the building cooling load. It also helps in reducing the building heating load slightly in the specific case study. The results from the calculation of peak load indicate that without the consideration of the impact of occupant behaviour in the calculation of building energy rating, the building might perform poorly than expected. This will lead to a performance gap between the simulated or expected and actual building energy use.

• author: Raghavendher Kumar, Sunil
• supervisor: Niko Gentile; Anton Hendrix
• organization: Division of Energy and Building Design; Department of Architecture and Built Environment
• course: AEBM01 20221
• year: 2022
• type: H2 - Master's Degree (Two Years)
• subject: Technology and Engineering
• keywords: Occupant behaviour, Shading system, Annual solar heat gains, Prediction model
• language: English
• id: 9083563
• date added to LUP: 2022-06-08 09:45:10
• date last changed: 2022-06-08 15:59:59