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Building Energy Consumption and Urban Energy Planning

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A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Energy, Physics, Environment, and Systems".

Deadline for manuscript submissions: closed (10 August 2022) | Viewed by 9405

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Special Issue Editors

Dr. Rui Jing

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Guest Editor

School of Engineering, Cardiff University, Cardiff, UK
Interests: urban energy planning; integrated energy systems; modelling and optimization; energy and climate change; energy nexus

Dr. Wei Wang

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Guest Editor

School of Architecture, Southeast University, Nanjing 210096, China
Interests: urban building energy efficiency; occupancy studies; urban building environment monitoring
Special Issues, Collections and Topics in MDPI journals

Dr. Minda Ma

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Guest Editor

1. Building Technology & Urban Systems Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
2. School of Economics, Sichuan University, Chengdu 610065, China
Interests: time-series monitoring of global building emissions; carbon neutral scenario simulation of the building sector; decarbonization potential analysis of the building sector
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the quantitative and qualitative dimensions of building and urban energy, given that buildings account for one-third of global energy-related greenhouse gas emissions, and the share is even higher in cities. Therefore, building and urban energy stand on the frontline of mitigating and adapting to climate change [1]. Many interesting topics deserve investigation, e.g., precise modelling and simulation of building energy in urban context [2], multi-vector energy integration towards establishing low-carbon cities [3], flexibility provision by AI-enhanced smart buildings [4], and building energy transition towards carbon neutrality [5,6]. All these promising topics call for greater research efforts to address the technical, economic, environmental, and climate aspects of building energy consumption in urban environments and eventually to make cities more energy-efficient and decarbonized. Overall, research, analysis, methods, and synthesis papers are warmly welcome for submission to the Special Issue “Building Energy Consumption and Urban Energy Planning”.

Ref.

[1] Zhang, S. et al. Historical carbon abatement in the commercial building operation: China versus the US. Energy Economics 105, 105712, doi:https://doi.org/10.1016/j.eneco.2021.105712 (2022).

[2] Wang, W. et al. From simulation to data-driven approach: A framework of integrating urban morphology to low-energy urban design. Renewable Energy 179, 2016-2035, doi:https://doi.org/10.1016/j.renene.2021.08.024 (2021).

[3] Jing, R., Hastings, A. & Guo, M. Sustainable Design of Urban Rooftop Food-Energy-Land Nexus. iScience 23, 101743, doi:10.1016/j.isci.2020.101743 (2020).

[4] Zsembinszki, G., Fernández, C., Vérez, D. & Cabeza, L. F. Deep Learning Optimal Control for a Complex Hybrid Energy Storage System. Buildings 11, doi:10.3390/buildings11050194 (2021).

[5] Mostafavi, N., Heris, M. P., Gándara, F. & Hoque, S. The Relationship between Urban Density and Building Energy Consumption. Buildings 11, doi:10.3390/buildings11100455 (2021).

[6] Li, K. et al. Carbon reduction in commercial building operations: A provincial retrospection in China. Applied Energy 306, 118098, doi:https://doi.org/10.1016/j.apenergy.2021.118098 (2022).

Dr. Rui Jing
Dr. Wei Wang
Dr. Minda Ma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

building energy simulation
urban energy system modelling
integrated energy system
low carbon cities
green building and city
energy flexibility
smart buildings
AI for urban energy
urban building and climate
building and urban sustainability

Published Papers (5 papers)

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Editorial

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2 pages, 164 KiB

Open AccessEditorial

Editorial Special Issue: Building Energy Consumption and Urban Energy Planning

by Wei Wang

Buildings 2023, 13(1), 6; https://doi.org/10.3390/buildings13010006 - 20 Dec 2022

Viewed by 833

Abstract

As of 2021, the global urbanization rate was still increasing, especially in China, whose permanent urban population reached 64 [...] Full article

(This article belongs to the Special Issue Building Energy Consumption and Urban Energy Planning)

Research

Jump to: Editorial

23 pages, 3133 KiB

Open AccessArticle

Effects of the Built Environment on Travel-Related CO₂ Emissions Considering Travel Purpose: A Case Study of Resettlement Neighborhoods in Nanjing

by Yiwen Zhang, Wenzhu Zhou and Jiayi Ding

Buildings 2022, 12(10), 1718; https://doi.org/10.3390/buildings12101718 - 17 Oct 2022

Cited by 3 | Viewed by 1766

Abstract

With rapid urbanization, an increasing number of resettlement housing neighborhoods have been developed in suburbs in China. Such neighborhoods often face problems of spatial mismatch (jobs–housing and daily life), excessive street scale, and inconvenient transportation, which directly and indirectly lead to long travel distances and higher travel carbon emissions for residents. Understanding how to improve the built environment of resettlement housing and thus influence travel CO₂ emissions is essential to guide low-carbon travel and reduce greenhouse gas emissions. Based on an electronic questionnaire and travel carbon emission measurements collected in 12 resettlement housing neighborhoods in Nanjing in 2022, this study used a three-group structure equation model (SEM) to measure the impact of resettlement housing’s built environment on travel CO₂ emissions from commutes, housework trips, and recreational trips. It was found that the improvement of destination accessibility can significantly reduce the carbon emissions of residents’ trips. Second, the built environment of resettlement housing can affect travel carbon emissions through mediator variables and direct effects. In addition, these effects show different paths and sizes depending on the purpose of the travel trip. These results are significant for the planning and construction of resettlement houses and offer guidance for low-carbon travel. Full article

(This article belongs to the Special Issue Building Energy Consumption and Urban Energy Planning)

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25 pages, 9489 KiB

Open AccessArticle

Optimization of Urban Block Form by Adding New Volumes for Capacity Improvement and Solar Performance Using A Multi-Objective Genetic Algorithm: A Case Study of Nanjing

by Jingjin Li, Yuxiao Wang, Yang Xia, Yacheng Song and Huahua Xie

Buildings 2022, 12(10), 1710; https://doi.org/10.3390/buildings12101710 - 17 Oct 2022

Cited by 4 | Viewed by 1865

Abstract

During urban renewal, multi-story residential blocks face a contradiction of balancing residential capacity improvement and solar constraint. This paper constructed a set of automatic workflows for adding new volumes to existing buildings, and a multi-objective optimization was applied with a Wallacei plug-in in Grasshopper to optimize the solar radiation, solar hours, and block capacity. First, this study established three building addition modes of existing blocks in the horizontal direction, vertical direction, and mixed direction, respectively. Three optimization objectives—maximum floor area ratio, maximum average radiation amount, and minimum solar shade—were defined. Second, the net increase in the floor area ratio of the block was calculated to balance capacity improvement and solar constraint. Third, the advantages of the three addition modes under different orientations were discussed. Among all three modes, the mixed addition mode had the best capacity improvement effect, with a 70% increase in floor area ratio. The vertical addition mode had the least impact on the solar shade of existing buildings. The horizontal addition mode could further improve the floor area ratio in areas where building height was strictly limited. The results can provide insights and inspiring guidelines for the renewal of the existing residential blocks to solve the floor area ratio constraint from solar radiation, as well as achieve urban function reconstruction and vitality regeneration. Full article

(This article belongs to the Special Issue Building Energy Consumption and Urban Energy Planning)

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21 pages, 6297 KiB

Open AccessArticle

Classification of Household Room Air Conditioner User Groups by Running Time in the Hot Summer and Cold Winter Zone of China

by Xiaobei Gu, Meng Liu and Ziqiao Li

Buildings 2022, 12(9), 1415; https://doi.org/10.3390/buildings12091415 - 08 Sep 2022

Cited by 4 | Viewed by 1360

Abstract

Household room air conditioners (RACs) are widely used in residential buildings to maintain an indoor thermal climate in China’s hot summer and cold winter (HSCW) zone. The aggregate utilization of RACs in a region has a great impact on regional energy demand in both the heating and cooling seasons. Classifying household RAC users and identifying their RAC usage demands will contribute to better balanced regional energy management for building energy flexibility. In this study, a data-driven method was proposed to classify the household RAC user groups at the regional level, using running time as an indicator. The results showed that RAC users could be classified into four groups with different RAC usage demands. The Lower Class was determined by the absolute poverty line with the Gini coefficient. In addition, the Upper Class was distinguished through the determination of the scaling region in power-law distribution. At the same time, the similarities and differences between different classes in monthly and hourly periods and the flexibility potential were discussed. The rigid demand was observed in the monthly periods of June, July and August and during the hourly periods of 21:00–22:00 in both the bedroom and living-room. Full article

(This article belongs to the Special Issue Building Energy Consumption and Urban Energy Planning)

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20 pages, 21968 KiB

Open AccessArticle

Analysis of Energy and Environmental Indicators for Sustainable Operation of Mexican Hotels in Tropical Climate Aided by Artificial Intelligence

by S. G. Mengual Torres, O. May Tzuc, K. M. Aguilar-Castro, Margarita Castillo Téllez, J. Ovando Sierra, Andrea del Rosario Cruz-y Cruz and Francisco Javier Barrera-Lao

Buildings 2022, 12(8), 1155; https://doi.org/10.3390/buildings12081155 - 03 Aug 2022

Cited by 6 | Viewed by 2561

Abstract

This study assessed the energy-use index and carbon-footprint performance of nine medium-category Mexican hotels (two–four stars) located in tropical-climate regions. The consumption of electrical and thermal energies of each hotel was collected during audits. Based on this, various scenarios of the partial replacement of the most energy-consuming devices were evaluated and synthesized in an expert model based on artificial neural networks. The artificial-intelligence model was designed to simultaneously associate the energy-consumption indicators, environmental impact, and economic savings of hotels based on their category, location, room number, number of existing electrical or thermal devices, and their percentage of substitution with more energy-efficient technologies. The model was used to compare the various partial-technology-substitution alternatives in each hotel that could reduce energy consumption and CO₂ emissions based on the current values reported by the energy-use and environmental-impact indicators. The results of the proposed approach showed that even without making total replacements of equipment such as interior and exterior lighting or air conditioners, it was possible to identify configurations that could reduce the hotels’ energy use per room-year by 9–12%. In the environmental case, using more efficient technologies could reduce environmental mitigation. The proposed methodology represents an attractive option to facilitate the analyses and the decision making of administrators according to the needs of the type of hotel to improve its performance, which also affects the reduction in operating costs. Full article

(This article belongs to the Special Issue Building Energy Consumption and Urban Energy Planning)

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