Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
A novel blinds control approach based on dynamic radiance and solar radiation energy prediction
https://orcid.org/0009-0007-9418-1672
https://orcid.org/0009-0004-9490-4912
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.
A novel blinds control approach based on dynamic radiance and solar radiation energy prediction
https://orcid.org/0009-0007-9418-1672
https://orcid.org/0009-0004-9490-4912
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.
A novel blinds control approach based on dynamic radiance and solar radiation energy prediction
https://orcid.org/0009-0007-9418-1672
https://orcid.org/0009-0004-9490-4912
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.
A novel blinds control approach based on dynamic radiance and solar radiation energy prediction
Li, Jianzhang (Autor:in) / Zeng, Xianhui (Autor:in)
Building Services Engineering Research & Technology ; 45 ; 21-38
01.01.2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Validation of dynamic RADIANCE-based daylight simulations for a test office with external blinds
| Online Contents | 2001
Solar Radiation Reflective and Infrared Radiation Emissive and Reflective Window Blinds
| Europäisches Patentamt | 2018