A thermal and acoustic co-simulation method for the multi-domain optimization of nearly zero energy buildings

Ferrara, Maria; Vallée, Jean Christophe; Shtrepi, Louena; Astolfi, Arianna; Fabrizio, Enrico

doi:10.1016/j.jobe.2021.102699

Cited by 7 publications

(7 citation statements)

References 26 publications

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“…My country has put forward the development goal of 30-30-30; that is, by 2030, 30% as well as 30% of their energy consumption should be provided by renewable energy [10]. Existing buildings should achieve "near-zero energy consumption" [11]. Under this goal, the one has officially launched the "Buildings," which is expected to be completed in 2018 and promulgated and implemented in 2019 [12].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Chen

Dai

Cai

2022

Adsorption Science & Technology

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This paper uses SketchUp and OpenStudio to design and optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. By establishing a basic model, the performance parameters such as insulation thickness, typical outer window, window-to-wall ratio, and their contribution rates within the threshold range are optimized for energy conservation; simulate the energy consumption of the determined multiperformance parameter combination scheme, select the most energy-saving scheme, and calculate its energy-saving contribution rate; calculate the life cycle cost of the above schemes, select the scheme with the lowest cost, and analyze its economic benefits; select energy-saving cost and economic benefit, and calculate energy-saving contribution rate and economic benefit. Finally, through the comparative analysis of the design and test data, this paper concludes that EnergyPlus will optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. At the same time, the multiobjective optimization method and process of the passive energy-saving technology of the near-zero energy consumption building proposed in this paper, as well as the technology combination template under different needs, provide a reference for the selection of the technology path.

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Section: Introductionmentioning

confidence: 99%

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Chen

Dai

Cai

2022

Adsorption Science & Technology

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“…Ascione combined Energy Plus with NSGA-II to optimize the design of residential buildings in Spain, balancing window sizes, types of glass, and external walls and roofs for heating and cooling demands [58]. Ferrara used the PSO algorithm in GenOpt to optimize buildings for energy, cost, and acoustic performance, while also incorporating analyses with the NSGA-II algorithm [59]. Delgarm, taking buildings in Iran as an example, used Energy Plus and NSGA-II for optimizing building orientation, window area, and window shading, showing a total energy consumption reduction of 23.8-42.2% [60].…”

Section: Multi-objective Optimization Algorithmmentioning

confidence: 99%

Multi-Objective Optimization for Winter Heating Retrofit in Rural Houses of Cold Regions: A Case Study in the Wusu Area

Xi,

Gao,

Hou

et al. 2024

Applied Sciences

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In regions of China experiencing severe cold, the duration of the winter heating season significantly contributes to elevated heating energy consumption in rural dwellings. This study focuses on typical brick-and-concrete rural homes in the Wusu area. Utilizing the Rhino–Grasshopper parametric modeling platform, it aims to minimize heating-related carbon emissions and the overall costs associated with retrofitting. The approach involves improving the insulation properties of the building envelope to reduce energy requirements. Additionally, the study incorporates solar photovoltaic systems atop rural homes, building upon low-carbon, passive, energy-efficient design principles. By examining the influence of various factors on rural housing energy consumption, the research employs the entropy weight method to identify the most effective design solutions. The goal is to explore strategies for the energy-efficient retrofitting of rural dwellings in areas faced with harsh winter conditions, aligning with the objectives and preferences of Applied Sciences. The simulation results reveal the following: (1). In comparison with the baseline scenario, 42.2% of the optimized solutions within the Pareto frontier satisfy the current standards for 75% energy savings in energy-efficient residential design. (2). The lowest recorded thermal consumption index for the buildings can reach 12.427 W/m2, at which point the rate of energy savings is elevated to 79.5%. (3). Within the solutions identified by the Pareto frontier, 80% exhibit initial investments that are lower than the cost savings over the lifecycle due to reduced energy consumption (dCg < 0), demonstrating the economic feasibility of the proposed retrofitting strategies.

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“…(3) Research on multi-objective optimization: multi objective optimization studies of near-zero energy buildings mainly focus on the thermal parameters of the envelope, the windowing/wall ratio, the capacity of the photovoltaic power generation system, wind power generation system and other energy supply systems as optimization parameters, and the system cost, energy production, carbon dioxide emissions, indoor thermal comfort as objective functions. In general, the thermal parameters, heating/cooling temperature and energy consumption indexes of the envelope structure stipulated in the existing standards are taken as the constraints for multi-objective optimization [22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Study on the Influencing Factors of Energy Consumption of Nearly Zero Energy Residential Buildings in Cold and Arid Regions of Northwest China

Yang

Yuan

Yang³

et al. 2022

Sustainability

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There are many factors influencing the energy consumption of buildings in complex working conditions. In order to study the factors influencing the energy consumption of residential buildings with nearly zero energy in cold and arid regions of northwest China, factors such as the roof heat transfer coefficient (KR), exterior wall heat transfer coefficient (KE), ground heat transfer coefficient (KG), exterior window heat transfer coefficient (KEW), north window wall ratio (WWRN), south window wall ratio (WWRS), east west window wall ratio (WWRWE), building orientation (BO), and ventilation times (VT) are taken as the influencing factors in this paper. Using the orthogonal test, 135 building energy consumption calculation models were built in DeST, and the influence of 9 factors on building energy consumption in 5 types of regions (severe cold region A (1A), severe cold region B (1B), severe cold region C (1C), cold region A (2A), and cold region B (2B)) were analyzed. The conclusions are as follows: in the process of realizing nearly zero energy of residential buildings in the cold and arid regions of northwest China, the KR, KE, KG, KEW, WWRN, WWEWE should be reduced as much as possible in the five regions. The 1A,1B,1C regions should increase WWEWE and VT, with BO of about 15° east of due north and VT of about 5, 8, and 10 times per hour, respectively. The WWES, BO and VT for the 2A region should be set at round 0.45, north-south, and about 10 times per hour, respectively. For the 2B region, WWES should be set at around 0.45, BO around 15° east of due north, and VT as low as possible within the scope of the ‘technical standard for nearly zero energy buildings’.

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A thermal and acoustic co-simulation method for the multi-domain optimization of nearly zero energy buildings

Cited by 7 publications

References 26 publications

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Multi-Objective Optimization for Winter Heating Retrofit in Rural Houses of Cold Regions: A Case Study in the Wusu Area

Study on the Influencing Factors of Energy Consumption of Nearly Zero Energy Residential Buildings in Cold and Arid Regions of Northwest China

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