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Energy Efficiency and Sustainability in Buildings

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

Deadline for manuscript submissions: closed (10 August 2020) | Viewed by 25933

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Dr. Edward Halawa

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Guest Editor

RIEL, Charles Darwin University, Darwin, Australia
Interests: energy systems analysis; renewable energy; thermal energy storage; thermal comfort
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Special Issue Information

Dear Colleagues,

In their operation, residential and commercial buildings consume significant amounts of energy to provide space cooling, heating, lighting, powering appliances and equipment, and other services. In this Special Issue, energy researchers, practitioners, and policymakers are invited to present research outcomes, innovations, or ideas on the energy efficiency and sustainability in buildings. Potential contributors to this Issue are also invited to look into existing “sustainable” energy practices in this sector. How efficient are those systems when delivering thermal and visual comfort and other services in buildings? Alternatively, are the building owners or occupants satisfied with the quality of services delivered by those systems? Are existing definitions of sustainability adequate to capture the real issues of energy sustainability in buildings? What lessons have we learned from existing buildings' energy systems and their sustainability status? How and where renewable energy can play an important role in achieving energy sustainability in this sector? These are some challenging questions that can be considered by potential contributors when preparing their manuscripts.

Dr. Edward Halawa
Guest Editor

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.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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.

Published Papers (7 papers)

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Research

16 pages, 5058 KiB

Open AccessArticle

Hybrid CHP/Geothermal Borehole System for Multi-Family Building in Heating Dominated Climates

by Saeed Alqaed, Jawed Mustafa, Kevin P. Hallinan and Rodwan Elhashmi

Sustainability 2020, 12(18), 7772; https://doi.org/10.3390/su12187772 - 20 Sep 2020

Cited by 24 | Viewed by 2327

Abstract

A conventional ground-coupled heat pump (GCHP) can be used to supplement heat rejection or extraction, creating a hybrid system that is cost-effective for certainly unbalanced climes. This research explores the possibility for a hybrid GCHP to use excess heat from a combined heat power (CHP) unit of natural gas in a heating-dominated environment for smart cities. A design for a multi-family residential building is considered, with a CHP sized to meet the average electrical load of the building. The constant electric output of the CHP is used directly, stored for later use in a battery, or sold back to the grid. Part of the thermal output provides the building with hot water, and the rest is channeled into the GCHP borehole array to support the building’s large heating needs. Consumption and weather data are used to predict hourly loads over a year for a specific multi-family residence. Simulations of the energies exchanged between system components are performed, and a cost model is minimized over CHP size, battery storage capacity, number of boreholes, and depth of the borehole. Results indicate a greater cost advantage for the design in a severely heated (Canada) climate than in a moderately imbalanced (Ohio) climate. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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28 pages, 2664 KiB

Open AccessArticle

Retrofitting High-Rise Residential Building in Cold and Severe Cold Zones of China—A Deterministic Decision-Making Mechanism

by Qiong He, Md. Uzzal Hossain, S. Thomas Ng and Godfried L. Augenbroe

Sustainability 2020, 12(14), 5831; https://doi.org/10.3390/su12145831 - 20 Jul 2020

Cited by 5 | Viewed by 2188

Abstract

This study aimed to develop a deterministic decision-making mechanism for finding the optimum set of retrofit solutions of existing high-rise residential buildings in two different climatic zones of China. The retrofit solutions were critically examined with different energy saving targets based on the local climatic conditions, building features, and retrofit costs in cold and severe cold zones comparatively. By making the extensive review and analyzing considerable statistics data and cost information, net present value (NPV) method was employed in the prototype building apartments to develop this deterministic model. The results demonstrated that the heating system is the most important factor in saving energy and obtaining the optimum revenue in these two regions. The highest optimal NPV can be obtained by achieving 60% energy saving in the cold zone, as energy saving is around 319 kWh/m²/year with the total retrofit costs of USD $3560, while it is 281 kWh/m²/year with the total retrofit costs of USD $3480 to achieve the 50% energy-saving target in the severe cold zone. Based on the analysis of energy savings and retrofit costs, the results can be effectively implemented for the purpose of creating sustainable retrofits in existing buildings, and the model can be adapted for selecting appropriate retrofit choices in other climatic zones. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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41 pages, 5549 KiB

Open AccessArticle

Significant Implication of Optimal Capacitor Placement and Sizing for a Sustainable Electrical Operation in a Building

by Muhd Azri Abdul Razak, Muhammad Murtadha Othman, Ismail Musirin, Mohd Ainor Yahya and Zilaila Zakaria

Sustainability 2020, 12(13), 5399; https://doi.org/10.3390/su12135399 - 03 Jul 2020

Cited by 6 | Viewed by 3220

Abstract

The improvement of energy efficiency plays an important role to ensure sustainable electrical operation in large-scale buildings. In relation to the low-cost electrical components, a capacitor is an electrical component that can be used to sustain or improve the operating performance of an unbalanced electrical system in large-scale buildings so that energy efficiency improvement can be obtained. This is important to overcome the ineffective utilization of energy caused by the occurrence of power losses in an unbalanced electrical system of large-scale buildings. Further improvement of energy efficiency can be obtained by reducing an excessive amount of incoming power through the determination of tap setting for incoming transformer, and this is classified under the concept of conservative voltage regulation (CVR) approach. In order to solve the problem, the optimal capacitor placement and sizing (OCPS) with CVR is introduced as a new approach for energy efficiency improvement while ensuring a sustainable operation in an unbalanced electrical system of large-scale buildings. The proposed technique utilizes the artificial intelligence (AI) based differential evolution particle swarm optimization (DEPSO) technique with the objective function of total cost minimization for the real power losses, real power consumption, and capacitors installation. The effectiveness of the proposed technique to achieve energy efficiency improvement is investigated through a case study of an unbalanced electrical system in a large-scale office building. The significance of the research output is related to its low-cost technology that has the potential for a comprehensive, pragmatic implementation in large-scale buildings, and subsequently, it will significantly accelerate the increase of national agenda in energy efficiency. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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16 pages, 4122 KiB

Open AccessEditor’s ChoiceArticle

A Deep Learning Approach to Forecasting Monthly Demand for Residential–Sector Electricity

by Hyojoo Son and Changwan Kim

Sustainability 2020, 12(8), 3103; https://doi.org/10.3390/su12083103 - 13 Apr 2020

Cited by 32 | Viewed by 3454

Abstract

Forecasting electricity demand at the regional or national level is a key procedural element of power-system planning. However, achieving such objectives in the residential sector, the primary driver of peak demand, is challenging given this sector’s pattern of constantly fluctuating and gradually increasing energy usage. Although deep learning algorithms have recently yielded promising results in various time series analyses, their potential applicability to forecasting monthly residential electricity demand has yet to be fully explored. As such, this study proposed a forecasting model with social and weather-related variables by introducing long short-term memory (LSTM), which has been known to be powerful among deep learning-based approaches for time series forecasting. The validation of the proposed model was performed using a set of data spanning 22 years in South Korea. The resulting forecasting performance was evaluated on the basis of six performance measures. Further, this model’s performance was subjected to a comparison with the performance of four benchmark models. The performance of the proposed model was exceptional according to all of the measures employed. This model can facilitate improved decision-making regarding power-system planning by accurately forecasting the electricity demands of the residential sector, thereby contributing to the efficient production and use of resources. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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17 pages, 8297 KiB

Open AccessEditor’s ChoiceArticle

Energy Efficiency and GHG Emissions Mapping of Buildings for Decision-Making Processes against Climate Change at the Local Level

by Edgar Lorenzo-Sáez, José-Vicente Oliver-Villanueva, Eloina Coll-Aliaga, Lenin-Guillermo Lemus-Zúñiga, Victoria Lerma-Arce and Antonio Reig-Fabado

Sustainability 2020, 12(7), 2982; https://doi.org/10.3390/su12072982 - 08 Apr 2020

Cited by 14 | Viewed by 3350

Abstract

Buildings have become a key source of greenhouse gas (GHG) emissions due to the consumption of primary energy, especially when used to achieve thermal comfort conditions. In addition, buildings play a key role for adapting societies to climate change by achieving more energy efficiency. Therefore, buildings have become a key sector to tackle climate change at the local level. However, public decision-makers do not have tools with enough spatial resolution to prioritise and focus the available resources and efforts in an efficient manner. The objective of the research is to develop an innovative methodology based on a geographic information system (GIS) for mapping primary energy consumption and GHG emissions in buildings in cities according to energy efficiency certificates. The developed methodology has been tested in a representative medium-sized city in Spain, obtaining an accurate analysis that shows 32,000 t of CO₂ emissions due to primary energy consumption of 140 GWh in residential buildings with high spatial resolution at single building level. The obtained results demonstrate that the majority of residential buildings have low levels of energy efficiency and emit an average of 45 kg CO₂/m². Compared to the national average in Spain, this obtained value is on the average, while it is slightly better at the regional level. Furthermore, the results obtained demonstrate that the developed methodology is able to directly identify city districts with highest potential for improving energy efficiency and reducing GHG emissions. Additionally, a data model adapted to the INSPIRE regulation has been developed in order to ensure interoperability and European-wide application. All these results have allowed the local authorities to better define local strategies towards a low-carbon economy and energy transition. In conclusion, public decision-makers will be supported with an innovative and user-friendly GIS-based methodology to better define local strategies towards a low-carbon economy and energy transition in a more efficient and transparent way based on metrics of high spatial resolution and accuracy. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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22 pages, 3395 KiB

Open AccessArticle

Microservices and Machine Learning Algorithms for Adaptive Green Buildings

by Diego Rodríguez-Gracia, José A. Piedra-Fernández, Luis Iribarne, Javier Criado, Rosa Ayala, Joaquín Alonso-Montesinos and Capobianco-Uriarte Maria de las Mercedes

Sustainability 2019, 11(16), 4320; https://doi.org/10.3390/su11164320 - 09 Aug 2019

Cited by 5 | Viewed by 3297

Abstract

In recent years, the use of services for Open Systems development has consolidated and strengthened. Advances in the Service Science and Engineering (SSE) community, promoted by the reinforcement of Web Services and Semantic Web technologies and the presence of new Cloud computing techniques, such as the proliferation of microservices solutions, have allowed software architects to experiment and develop new ways of building open and adaptable computer systems at runtime. Home automation, intelligent buildings, robotics, graphical user interfaces are some of the social atmosphere environments suitable in which to apply certain innovative trends. This paper presents a schema for the adaptation of Dynamic Computer Systems (DCS) using interdisciplinary techniques on model-driven engineering, service engineering and soft computing. The proposal manages an orchestrated microservices schema for adapting component-based software architectural systems at runtime. This schema has been developed as a three-layer adaptive transformation process that is supported on a rule-based decision-making service implemented by means of Machine Learning (ML) algorithms. The experimental development was implemented in the Solar Energy Research Center (CIESOL) applying the proposed microservices schema for adapting home architectural atmosphere systems on Green Buildings. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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22 pages, 7637 KiB

Open AccessArticle

A Comparative Study of Traditional and Contemporary Building Envelope Construction Techniques in Terms of Thermal Comfort and Energy Efficiency in Hot and Humid Climates

by Pooya Lotfabadi and Polat Hançer

Sustainability 2019, 11(13), 3582; https://doi.org/10.3390/su11133582 - 28 Jun 2019

Cited by 35 | Viewed by 7353

Abstract

Expectations of traditional and contemporary buildings are different in terms of thermal comfort. Traditional buildings mostly achieve comfort through passive means, without HVAC support, but old levels of thermal satisfaction do not meet today’s expectations, although their passive thermal performances are notable for contemporary building designs. In this regard, the current study tries to investigate the possibility of comparing traditional and contemporary buildings’ construction techniques to achieve thermal comfort from an architectural point of view. In other words, is it possible to achieve passive building design by considering vernacular architecture principals as a reference? Likewise, how well can architects define insulation layers in contemporary construction surfaces in hot and humid climates? To this end, a dynamic, numerical, thermal calculation case study has been modeled in Famagusta, Northern Cyprus, to answer the above-mentioned questions. A mixed-use mode benefitting free-run periods is proposed and compared with a mode providing 24 hours of air-conditioning in different scenarios using the same initial settings. Thus, different floor-to-ceiling heights, insulation placements and indoor conditions have been tested separately in both winter and summer periods. The results show that thermal comfort can be achieved in free-run periods only during a limited percentage of the year. Furthermore, although increasing building heights may lead to a rise in the free-run periods, in contemporary buildings it increases the total energy usage of the buildings between 6% and 9% in the mixed mode. Therefore, vernacular architecture strategies are proper in their own context. However, this energy usage can still be controlled and optimized by such considerations as insulation material placement. In this regard, the best envelope properties for different building functions are proposed for application in hot and humid climates. Full article

(This article belongs to the Special Issue Energy Efficiency and Sustainability in Buildings)

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