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22 pages, 11950 KiB

Open AccessArticle

Experimental and Co-Simulation Performance Evaluation of an Earth-to-Air Heat Exchanger System Integrated into a Smart Building

by Abdelhak Kharbouch, Soukayna Berrabah, Mohamed Bakhouya, Jaafar Gaber, Driss El Ouadghiri and Samir Idrissi Kaitouni

Energies 2022, 15(15), 5407; https://doi.org/10.3390/en15155407 - 26 Jul 2022

Cited by 10 | Viewed by 1689

Abstract

Building models and their connected subsystems are often simulated as standalone entities. However, in order to monitor a system′s reactions to changing parameters and to assess its energy efficiency, it must be exposed to the actual dynamic context of the building under study. Hence, frameworks assessing co-operative simulation of buildings and their subsystems should be used. In this study, the Building Control Virtual Test Bed (BCVTB) framework was used for co-simulation of a small-scale building (EEBLab) connected to an Earth-to-air heat exchanger (EAHE). The EnergyPlus tool was used to simulate the indoor air temperature variations within the EEBLab, and MATLAB was used to model the EAHE system and to calculate its performance based on various parameters. The HOLSYS internet of things platform was deployed to monitor and collect the experimental data from the sensors to validate the simulations. A favorable agreement between the experimental and simulation results was obtained, showing the contribution of the small-scale EAHE system in maintaining a comfortable indoor temperature range inside EEBLab. Moreover, it demonstrated the effectiveness and accuracy of the proposed approach for integrated building co-simulation and performance evaluation. Full article

(This article belongs to the Special Issue Advances in Energy-Efficient Buildings)

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17 pages, 4990 KiB

Open AccessArticle

Solar Energy Compensation for Building Energy Saving with Thermal Comfort in a Cold Climate

by Xiangping Chen, Yongxiang Cai, Xiaobing Xiao, Youzhuo Zheng and Anqian Yang

Electronics 2022, 11(3), 491; https://doi.org/10.3390/electronics11030491 - 8 Feb 2022

Viewed by 1750

Abstract

This paper proposes an energy-saving strategy with assistance from solar thermal compensation for building energy systems. The target of the control strategy was to minimize energy consumption under thermal comfort constraints in buildings. First, the factors influential to indoor temperature in building environments were analyzed. Secondly, the internal and external factors, such as building materials; building orientation; window size; heating, ventilation, and air conditioning (HVAC) facilities; blinding device; solar irradiation; wind speed; and outdoor temperature were used to construct a building model on the platform ENERGYPLUS (E+). A controller aiming to regulate the amount of solar irradiation was developed with the Building Controls Virtual Test Bed (BCVTB) tool. Afterward, the building performance under different strategies was tested by co-simulation using both the computational platforms, E+ and BCVTB. The optimum scheme achieved 30.6% energy savings while meeting the same comfort criterion of its competition strategy. The study verified that the proposed strategy of combined heating, ventilation, and air conditioning and blind control could realize the energy savings and comfort satisfaction at the same time. The proposed method provides a reference to the development of low-/zero-energy building concepts in the field. Full article

(This article belongs to the Section Power Electronics)

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18 pages, 7099 KiB

Open AccessArticle

Visualized Co-Simulation of Adaptive Human Behavior and Dynamic Building Performance: An Agent-Based Model (ABM) and Artificial Intelligence (AI) Approach for Smart Architectural Design

by Hwang Yi

Sustainability 2020, 12(16), 6672; https://doi.org/10.3390/su12166672 - 18 Aug 2020

Cited by 18 | Viewed by 6569

Abstract

Human (occupant) behavior has been a topic of active research in the study of architecture and energy. To integrate the work of architectural design with techniques of building performance simulation in the presence of responsive human behavior, this study proposes a computational framework that can visualize and evaluate space occupancy, energy use, and generative envelope design given a space outline. A design simulation platform based on the visual programming language (VPL) of Rhino Grasshopper (GH) and Python is presented so that users (architects) can monitor real-time occupant response to space morphology, environmental building operation, and the formal optimization of three-dimensional (3D) building space. For dynamic co-simulation, the Building Controls Virtual Test Bed, Energy Plus, and Radiance were interfaced, and the agent-based model (ABM) approach and Gaussian process (GP) were applied to represent agents’ self-learning adaptation, feedback, and impact on room temperature and illuminance. Hypothetical behavior scenarios of virtual agents with experimental building geometry were produced to validate the framework and its effectiveness in supporting dynamic simulation. The study’s findings show that building energy and temperature largely depend on ABMs and geometry configuration, which demonstrates the importance of coupled simulation in design decision-making. Full article

(This article belongs to the Special Issue Towards a Sustainable Life: Smart and Green Design in Buildings and Community)

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19 pages, 3390 KiB

Open AccessArticle

Uncertainty of Energy and Economic Performance of Manual Solar Shades in Hot Summer and Cold Winter Regions of China

by Jian Yao and Rongyue Zheng

Sustainability 2019, 11(20), 5711; https://doi.org/10.3390/su11205711 - 16 Oct 2019

Cited by 4 | Viewed by 1920

Abstract

Occupant behavior is recognized as a major source of discrepancy between simulated and actual energy consumption. This study investigates the uncertainty of energy and economic performance of manual solar shades for the south facade. A developed stochastic model for manual solar shades based on a discrete-time Markov chain method was constructed in Building Controls Virtual Test Bed (BCVTB) for co-simulation with EnergyPlus. The stochastic shade model was compared with deterministic models concerning energy savings potential and life cycle economic performance at different building scales (i.e., from a single room to a whole building). The results show that annual energy uncertainty, due to occupant behavior, on manual shades can be neglected at the building level, whereas for sizing heating equipment, energy uncertainty should be considered. The payback period for manual shades is about 10 years and, in general, a larger building has a higher economic performance. Comparative analysis shows that there is a relatively big performance overestimation or underestimation by commonly used deterministic models in building simulation tools, and thus may lead to a biased economic analysis or even an inappropriate design decision when comparing different energy-saving measures. Full article

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1647 KiB

Open AccessArticle

A Long-Short Term Memory Recurrent Neural Network Based Reinforcement Learning Controller for Office Heating Ventilation and Air Conditioning Systems

by Yuan Wang, Kirubakaran Velswamy and Biao Huang

Processes 2017, 5(3), 46; https://doi.org/10.3390/pr5030046 - 18 Aug 2017

Cited by 110 | Viewed by 13992

Abstract

Energy optimization in buildings by controlling the Heating Ventilation and Air Conditioning (HVAC) system is being researched extensively. In this paper, a model-free actor-critic Reinforcement Learning (RL) controller is designed using a variant of artificial recurrent neural networks called Long-Short-Term Memory (LSTM) networks. Optimization of thermal comfort alongside energy consumption is the goal in tuning this RL controller. The test platform, our office space, is designed using SketchUp. Using OpenStudio, the HVAC system is installed in the office. The control schemes (ideal thermal comfort, a traditional control and the RL control) are implemented in MATLAB. Using the Building Control Virtual Test Bed (BCVTB), the control of the thermostat schedule during each sample time is implemented for the office in EnergyPlus alongside local weather data. Results from training and validation indicate that the RL controller improves thermal comfort by an average of 15% and energy efficiency by an average of 2.5% as compared to other strategies mentioned. Full article

(This article belongs to the Collection Process Data Analytics)

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7282 KiB

Open AccessArticle

Impact of Manually Controlled Solar Shades on Indoor Visual Comfort

by Jian Yao, David Hou Chi Chow and Yu-Wei Chi

Sustainability 2016, 8(8), 727; https://doi.org/10.3390/su8080727 - 29 Jul 2016

Cited by 14 | Viewed by 4486

Abstract

Daylight plays a significant role in sustainable building design. The purpose of this paper was to investigate the impact of manual solar shades on indoor visual comfort. A developed stochastic model for manual solar shades was modeled in Building Controls Virtual Test Bed, which was coupled with EnergyPlus for co-simulation. Movable solar shades were compared with two unshaded windows. Results show that movable solar shades have more than half of the working hours with a comfortable illuminance level, which is about twice higher than low-e windows, with a less significant daylight illuminance fluctuation. For glare protection, movable solar shades increase comfortable visual conditions by about 20% compared to low-e windows. Moreover, the intolerable glare perception could be reduced by more than 20% for movable solar shades. Full article

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