Simulation Analysis and Scheme Optimization of Energy Consumption in Public Buildings

Liu, Yang; Zou, Shiqing; Chen, Hongyu; Wu, Xianguo; Chen, Wenman

doi:10.1155/2019/6326138

Cited by 10 publications

(4 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DesignBuilder is a comprehensive simulation software for building energy consumption including heating, cooling, lighting, and ventilation, etc., based on EnergyPlus dynamic simulation engine [57][58][59][60]. It will provide a data-supported reference for determining the energy-saving contribution of the generated design.…”

Section: Building Energy Consumption Simulation Based On Designbuildermentioning

confidence: 99%

A Deep Learning Approach toward Energy-Effective Residential Building Floor Plan Generation

Wan

Zhao

et al. 2022

Sustainability

View full text Add to dashboard Cite

The ability of deep learning has been tested to learn graphical features for building-plan generation. However, whether the deeper space allocation strategies can be obtained and thus reduce energy consumption has still not been investigated. In the present study, we aimed to train a neural network by employing a characterized sample set to generate a residential building floor plan (RBFP) for achieving energy reduction effects. The network is based on Pix2Pix, including two sub-models: functional segmentation layout (FSL) generation and building floor plan (BFP) generation. To better characterize the energy efficiency, 98 screened floor plans of Solar Decathlon (SD) entries were labeled as the sample set. The data augmentation method was adopted to improve the performance of the FSL sub-model after the preliminary testing. Three existing residential buildings were used as cases to observe whether the network-generated RBFP gained the effect of decreasing energy consumption with decent space allocation. The results showed that, under the same simulation settings and building exterior profile (BEP) conditions, the function arrangement of the generated scheme was more reasonable compared to the original scheme in each case. The annual total energy consumption was reduced by 13.38%, 12.74%, and 7.47%, respectively. In conclusion, trained by the sample set that characterizes energy efficiency, the RBFP generation network has a positive effect in both optimizing the space allocation and reducing energy consumption. The implemented data augmentation method can significantly improve the network’s training results with a small sample size.

show abstract

Section: Building Energy Consumption Simulation Based On Designbuildermentioning

confidence: 99%

A Deep Learning Approach toward Energy-Effective Residential Building Floor Plan Generation

Wan

Zhao

et al. 2022

Sustainability

View full text Add to dashboard Cite

show abstract

“…Clearly, the results of these two studies show that the smaller the value of WWR, the more significant the effect on building energy efficiency. The current "Design Standard for Energy Efficiency of Residential Buildings in Hot Summer and Cold Winter Zone" (JGJ134-2010) [17] of China uses the dynamic simulation analysis method to study the relationship between the reasonable value of WWR of each orientation and the thermal insulation performance of external windows [18]. It has been noted that the maximum WWR of 0.6 for south-facing can only be set when the heat transfer coefficient of the external windows is reduced to 2.5 W/(m 2• C) [19].…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization Analysis of the Residential Window-to-Wall Ratio Based on Numerical Calculation of Energy Consumption in the Hot-Summer and Cold-Winter Zone of China

Liu

Zhang

et al. 2021

Sustainability

View full text Add to dashboard Cite

Along with the rapid urbanization and economic growth of China over the past decades, the thermal comfort needs of the people in this region have risen dramatically, and at the same time, promoting building energy efficiency is cited as part of the major projects in the 14th five-year plan for energy efficiency improvement. In addition, the outbreak of the COVID-19 epidemic has plunged people into long-term panic, and promoted the entire construction industry to think about a healthier and more sustainable living environment. To respond to the imbalance between energy supply and demand, an optimization analysis based on energy use is developed, assessing the energy efficiency of the window-to-wall ratio (WWR) design and calculating the energy consumption of three different types of residential buildings for both cooling and heating loads as well as for year-round loads. Owing to its harsh climate and huge energy consumption, in this study, the Hot-summer and Cold-winter (HSCW) zone of China was chosen as the experimental setting for the optimization analysis of WWR. Then, in the three main types of residential buildings, including detached houses, multi-story dwellings and high-rise dwellings, a correlation between WWRS and energy consumption in the cooling season, heating season and year-round was built. The comparisons between the WWRS and energy consumption for different types of residential buildings are presented. The design optimization recommendation for WWRS are proposed. It has significant positive meanings for the development of green and sustainably designed residential buildings that offer high levels of thermal comfort and energy efficiency.

show abstract

“…Depending on the energy cost, the insulation cost of an enclosure system in a hot climate will be 2.5-5 cm more than that of an enclosure system in a warm and humid climate. Liu et al [25] built a simulation model through the energy consumption simulation analysis method and verified the reliability of the model by comparing it with the actual energy consumption. In order of energy-saving sensitivity, the thermal design parameters of six building envelopes, including the heat transfer coefficient of external walls, were analysed.…”

Section: Introductionmentioning

confidence: 99%

Sensitivity analysis of design parameters of envelope enclosure performance in the dry-hot and dry-cold areas

Wang

Zheng

et al. 2021

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

In a bid to quantify the sensitivity of envelope enclosure’s design parameters in the dry-hot and dry-cold areas and to provide a reference for the local building performance design, this paper uses ANN modelling which combined with the improved Garson algorithm to calculate the connection weight sensitivity (CWS), the first-order sensitivity (RBD-S1 and DMIM-S1) and the global sensitivity (DMIM-delta) of the design parameters. These parameters were calculated by using different methods in SALib. Through the verification and analysis of the sensitive result, the applicability of the CWS and DMIM-delta was confirmed. Among the design parameters involved in this study, the sum of the sensitive values of S-D, S-N and S-A exceeds 60% in each performance label, and the sum of the sensitive values of WWR_S and WWR_N exceeds 20%. The performance design of envelope enclosure in this area requires applying reasonable shading components and appropriate optimisation of the North and South of WWR. After the sensitivity analysis process, the calculation efficiency of the model can be improved as far as possible without reducing the accuracy of the model in the later simplified calculation and multi-objective optimisation. The building performance simulation model has a high degree of non-linearity, and the interpretability of the model can be enhanced through the sensitivity analysis process. Although the internal calculation process is unknowable, the perception of the results caused by the input parameters is significantly enhanced.

show abstract

Simulation Analysis and Scheme Optimization of Energy Consumption in Public Buildings

Cited by 10 publications

References 12 publications

A Deep Learning Approach toward Energy-Effective Residential Building Floor Plan Generation

A Deep Learning Approach toward Energy-Effective Residential Building Floor Plan Generation

Optimization Analysis of the Residential Window-to-Wall Ratio Based on Numerical Calculation of Energy Consumption in the Hot-Summer and Cold-Winter Zone of China

Sensitivity analysis of design parameters of envelope enclosure performance in the dry-hot and dry-cold areas

Contact Info

Product

Resources

About