Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System

Among the envelope components (e.g., walls, roofs, floors, and windows, etc.) affecting the cooling and heating load of buildings, windows are the most thermally vulnerable. Shading devices can minimize the thermal load on windows due to solar radiation and decrease radiation effects. However, the l...

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Main Authors: Dong Eun Jung, Chanuk Lee, Kwang Ho Lee, Minjae Shin, Sung Lok Do
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/14/7/1799
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author Dong Eun Jung
Chanuk Lee
Kwang Ho Lee
Minjae Shin
Sung Lok Do
author_facet Dong Eun Jung
Chanuk Lee
Kwang Ho Lee
Minjae Shin
Sung Lok Do
author_sort Dong Eun Jung
collection DOAJ
description Among the envelope components (e.g., walls, roofs, floors, and windows, etc.) affecting the cooling and heating load of buildings, windows are the most thermally vulnerable. Shading devices can minimize the thermal load on windows due to solar radiation and decrease radiation effects. However, the load changes due to convection and conduction should be considered. Therefore, when a shading device is applied to a window, control logic for thermal blocking and heat retention is necessary to prevent the load changes. In addition, by combining the opposite features of photovoltaic (PV) that require solar radiation and the shading device to block solar radiation, energy-saving and production can be achieved simultaneously. Therefore, this study minimized the thermal effects of windows using a movable shading device integrated with PV and evaluated the PV power generation. This study evaluated the effects on window heat transfer by applying artificial intelligence techniques, which have recently attracted attention, to system operation. To achieve this, artificial neural network (ANN)-based control logic was developed, and the control performance of the system was assessed using simulations. In ANN control, the window heat transfer was 86.3% lower in a cooling period and 9.7% lower in a heating period compared with that of a shading device fixed at 45°. Furthermore, the PV system produced 3.0 to 3.1% more electric power under optimal control during the cooling period.
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spelling doaj.art-c5d16c15419e4880a09632cc7f52a66f2023-11-21T11:48:01ZengMDPI AGEnergies1996-10732021-03-01147179910.3390/en14071799Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV SystemDong Eun Jung0Chanuk Lee1Kwang Ho Lee2Minjae Shin3Sung Lok Do4Department of Building and Plant Engineering, Hanbat National University, 125, Dongseo-daero, Yuseong-gu, Daejeon 34158, KoreaDepartment of Building and Plant Engineering, Hanbat National University, 125, Dongseo-daero, Yuseong-gu, Daejeon 34158, KoreaDepartment of Architecture, College of Engineering, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, KoreaArchitecture and Architectural Engineering, Hanyang University, 55, Hanyangdaehak-ro, Sangnok-gu, Ansan 15588, KoreaDepartment of Building and Plant Engineering, Hanbat National University, 125, Dongseo-daero, Yuseong-gu, Daejeon 34158, KoreaAmong the envelope components (e.g., walls, roofs, floors, and windows, etc.) affecting the cooling and heating load of buildings, windows are the most thermally vulnerable. Shading devices can minimize the thermal load on windows due to solar radiation and decrease radiation effects. However, the load changes due to convection and conduction should be considered. Therefore, when a shading device is applied to a window, control logic for thermal blocking and heat retention is necessary to prevent the load changes. In addition, by combining the opposite features of photovoltaic (PV) that require solar radiation and the shading device to block solar radiation, energy-saving and production can be achieved simultaneously. Therefore, this study minimized the thermal effects of windows using a movable shading device integrated with PV and evaluated the PV power generation. This study evaluated the effects on window heat transfer by applying artificial intelligence techniques, which have recently attracted attention, to system operation. To achieve this, artificial neural network (ANN)-based control logic was developed, and the control performance of the system was assessed using simulations. In ANN control, the window heat transfer was 86.3% lower in a cooling period and 9.7% lower in a heating period compared with that of a shading device fixed at 45°. Furthermore, the PV system produced 3.0 to 3.1% more electric power under optimal control during the cooling period.https://www.mdpi.com/1996-1073/14/7/1799movable shading devicephotovoltaic systemartificial neural networkoptimal controlwindow heat transfer
spellingShingle Dong Eun Jung
Chanuk Lee
Kwang Ho Lee
Minjae Shin
Sung Lok Do
Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System
Energies
movable shading device
photovoltaic system
artificial neural network
optimal control
window heat transfer
title Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System
title_full Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System
title_fullStr Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System
title_full_unstemmed Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System
title_short Evaluation of Building Energy Performance with Optimal Control of Movable Shading Device Integrated with PV System
title_sort evaluation of building energy performance with optimal control of movable shading device integrated with pv system
topic movable shading device
photovoltaic system
artificial neural network
optimal control
window heat transfer
url https://www.mdpi.com/1996-1073/14/7/1799
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