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Advanced Research on Low Carbon Buildings Design and Energy Efficiency

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Green Building".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3412

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Special Issue Editors

Dr. Jiaqiang Wang

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Guest Editor

School of Energy Science and Engineering, Central South University, Changsha 410083, China
Interests: building energy saving; data center efficient cooling technology; model predictive control in building system; virtual sensor calibration

Dr. Linfeng Zhang

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Guest Editor

School of Transportation, Southeast University, Nanjing 411189, China
Interests: optimal design method for low carbon buildings; renewable energy application for buildings; grid-interactive efficient buildings

Dr. Sungmin Yoon

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Guest Editor

Department of Global Smart City, Sungkyunkwan University, Suwon 16419, Republic of Korea
Interests: building science; digitalization and energy; in situ virtual sensing; information fusion in buildings; self-evolving building systems

Special Issue Information

Dear Colleagues,

The building sector consumes 40% of energy from primary sources and contributes to 36% of greenhouse gases emissions; thus, it plays an important role in energy usage, raising environmental concerns. However, with people's continuous demand for a healthy and comfortable living environment, carbon emissions in the building field will continue to increase. Therefore, promoting green and low-carbon development in this area is the key strategy to achieve the goal of carbon neutrality.

This Special Issue aims to cover the most recent advances in low-carbon research with a focus on buildings design and energy efficiency. This issue welcomes original research article and reviews. Research areas may include, but are not limited to, the following topics:

Modeling and design method for net-zero carbon buildings;
Renewable energy utilization for low-carbon buildings;
Carbon emission calculation method for low-carbon buildings;
Energy efficiency renovation methods for existing buildings;
Roadmap for net-zero carbon buildings;
Sustainable and green architecture design;
Demand-based control and optimization;
Modelling, control and optimization for building energy systems;
Simulation model and sensor calibration methods;
Artificial intelligence for building integrated renewable energy systems.

We look forward to receiving your contributions.

Dr. Jiaqiang Wang
Dr. Linfeng Zhang
Dr. Sungmin Yoon
Guest Editors

Manuscript Submission Information

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Keywords

building energy saving
low-carbon buildings
building integrated renewable energy systems
building system control and optimization

Published Papers (4 papers)

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Research

19 pages, 2026 KiB

Open AccessArticle

Optimising Building Energy and Comfort Predictions with Intelligent Computational Model

by Salah Alghamdi, Waiching Tang, Sittimont Kanjanabootra and Dariusz Alterman

Sustainability 2024, 16(8), 3432; https://doi.org/10.3390/su16083432 - 19 Apr 2024

Viewed by 382

Abstract

Building performance prediction is a significant area of research, due to its potential to enhance the efficiency of building energy management systems. Its importance is particularly evident when such predictions are validated against field data. This paper presents an intelligent computational model combining Monte Carlo analysis, Energy Plus, and an artificial neural network (ANN) to refine energy consumption and thermal comfort predictions. This model addresses various combinations of architectural building design parameters and their distributions, effectively managing the complex non-linear relationships between the response variables and predictors. The model’s strength is demonstrated through its alignment with R² values exceeding 0.97 for both thermal discomfort hours and energy consumption during the training and testing phases. Validation with field investigation data further confirms its accuracy, demonstrating average relative errors below 2.0% for total energy consumption and below 1.0% for average thermal discomfort hours. In particular, an average underestimation of −12.5% in performance discrepancies is observed when comparing the building energy simulation model with field data, while the intelligent computational model presented a smaller overestimation error (of +8.65%) when validated against the field data. This discrepancy highlights the model’s potential and reliability for the simulation of real-world building performance metrics, marking it as a valuable tool for practitioners and researchers in the field of building sustainability. Full article

(This article belongs to the Special Issue Advanced Research on Low Carbon Buildings Design and Energy Efficiency)

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20 pages, 3489 KiB

Open AccessArticle

Optimal Planning of Urban Building-Type Integrated Energy Systems Considering Indoor Somatosensory Comfort and PV Consumption

by Guangzeng You, Peng Sun, Yi Lei, Donghui Zhang and Haibo Li

Sustainability 2024, 16(1), 411; https://doi.org/10.3390/su16010411 - 03 Jan 2024

Viewed by 638

Abstract

Building energy consumption is the main urban energy consumption component, which mainly serves people-centered work and living energy demands. Based on the physical requirements of humans in urban buildings and to determine the comfortable body temperature in each season, this paper establishes a sizing optimization model of building-type integrated energy systems (IES) for sustainable development, where the cooling and heating loads required to maintain indoor somatosensory body comfort temperature are calculated. Depending on the external energy price, internal power balance, and other constraints, the model develops an optimal sizing and capacity-planning method of energy conversion and storage unit in a building-type IES with PV generation. The operating principle is described as follows: the PV generation is fully consumed, a gas engine satisfies the electric and thermal base load requirements, and the power system and a heat pump supply the remaining loads. The gas price, peak-valley electricity price gap, and heat-to-power ratio of gas engines are considered important factors for the overall techno-economic analysis. The developed method is applied to optimize the economic performance of building-type IES and verified by practical examples. The results show that using the complementary characteristics of different energy conversion units is important to the overall IES cost. A 300 kW building photovoltaic system can reduce the gas engine capacity from 936.7 kW to 854.7 kW, and the annual cost can be approximately reduced from 7.82 million to 7.50 million RMB yuan. Full article

(This article belongs to the Special Issue Advanced Research on Low Carbon Buildings Design and Energy Efficiency)

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22 pages, 19055 KiB

Open AccessArticle

The Relationship between Residential Block Forms and Building Carbon Emissions to Achieve Carbon Neutrality Goals: A Case Study of Wuhan, China

by Haitao Lian, Junhan Zhang, Gaomei Li and Rui Ren

Sustainability 2023, 15(22), 15751; https://doi.org/10.3390/su152215751 - 08 Nov 2023

Viewed by 911

Abstract

Controlling building carbon emissions (CEs) is key to achieving the goal of carbon neutrality. Residential blocks are the main contributors of buildings’ carbon emissions and intensity, and thus can be manipulated to achieve carbon neutrality. This work aimed to evaluate the building carbon emissions intensity (CEI) levels of residential blocks using Rhino and Grasshopper and to quantify the relationship between the block form parameters and a building’s carbon emissions (CEs). Firstly, 48 cases were selected by stratified sampling, and they were classified by architectural typology. Secondly, the residential block morphological parameters and building carbon emissions were calculated. Thirdly, the relationship between the block form parameters and the building’s CE was quantified using statistical methods. Lastly, low-carbon planning strategies for residential blocks under the target of carbon neutrality were proposed. The findings showed that the influence of the block form parameters on a building’s CE was 31.66%. A building’s shape factor has a positive influence on its CE, and the floor area ratio, building volume–site area ratio, and building height have negative influences on its CE. A building’s shape factor, cover ratio, and surface–site area ratio synergistically impact its CE. The weight of a building’s shape factor on its carbon emissions was 3.84 times that of its cover ratio and 4.46 times that of its surface–site area ratio. The technology workflow proposed in this study can provide data in support of carbon emissions assessments and low-carbon planning strategies for urban blocks in other cities in China and worldwide. Full article

(This article belongs to the Special Issue Advanced Research on Low Carbon Buildings Design and Energy Efficiency)

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20 pages, 5668 KiB

Open AccessArticle

Study on Effects of Operating Parameters on a Water-Cooled Loop Thermosyphon System under Partial Server Utilization

by Sikai Zou, Chang Yue, Ting Xiao, Xingyi Ma and Yiwei Wang

Sustainability 2023, 15(17), 13100; https://doi.org/10.3390/su151713100 - 31 Aug 2023

Viewed by 653

Abstract

During the operation of a data center, servers are gradually installed in racks, causing most racks to work under a low heating load for a long time and affecting the cooling efficiency of the loop thermosyphon system (LTS). Thus, the effects of operating parameters on the thermal performance should be investigated. In this study, a water-cooled LTS was experimentally investigated under different airflow rates and heating loads. The results show that the additional liquid refrigerant reduced the heat transfer performance and aggravated a drop in cooling capacity when the airflow rate and heating load were decreased. To further reveal the effects of the operating parameters on the thermal performance and cooling efficiency, a steady-state distributed-parameter model was developed and validated based on the experimental data. The results show that the excessive cooling capacity was reduced by decreasing the airflow rate according to the upper limit of the server exhaust air temperature under partial server utilization. The excessive cooling capacity was reduced by 14.5–52.1% under 5–56.5% server utilization. To further reduce the excessive cooling capacity while ensuring thermal security, the water side operating parameters (including the supply chilled water temperature and water flow rate) were adjusted according to the upper limit of the rack’s average outlet air temperature, which reduced the excessive cooling capacity by more than 23.8% under partial server utilization. Full article

(This article belongs to the Special Issue Advanced Research on Low Carbon Buildings Design and Energy Efficiency)

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