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36 pages, 5399 KiB

Open AccessArticle

Quantifying and Rating the Energy Resilience Performance of Buildings Integrated with Renewables in the Nordics under Typical and Extreme Climatic Conditions

by Hassam ur Rehman, Vahid M. Nik, Rakesh Ramesh and Mia Ala-Juusela

Buildings 2024, 14(9), 2821; https://doi.org/10.3390/buildings14092821 - 7 Sep 2024

Cited by 2 | Viewed by 1426

Abstract

The future buildings and society need to be resilient. This article aims to propose a novel concept of the energy resilience framework and implement a color-based rating system to quantify and rate the energy resilience performance of buildings in Nordic climates. The objective [...] Read more.

The future buildings and society need to be resilient. This article aims to propose a novel concept of the energy resilience framework and implement a color-based rating system to quantify and rate the energy resilience performance of buildings in Nordic climates. The objective is to conduct a comparative analysis between old (1970s) and new (2020s) single-family buildings integrated with renewable energy sources and storage, assessing their energy resilience performance for heating during power outages, under extreme and typical climatic conditions. The study utilizes dynamic simulation of the buildings and renewable energy systems, conducting parametric studies to calculate proposed resilience indicators and rate their resilience performance, employing both passive and active methods. The total costs of the design variables are also calculated for economic evaluation. Given the complexities arising from climate change, the article uses a simplified method to synthesize regional climate to consider extreme climate change impacts on energy resilience performance. For the old building lacking PV, the robustness duration increased from 1 h to 3 h, and the degree of disruption (DoD) varied from 0.545 to 0.3 in extreme cold to warm climate scenarios, with the higher DoD number indicating worse performance. The impact of the season within the same climate scenario is also evident, as the habitability and robustness durations increased during spring compared to winter. The resilience improved with PV and battery. The new building showed that the robustness duration increased from 3 to 15 h, habitability durations increased, and the DoD varied from 0.496 to 0.22 from extreme cold to warm climates without renewables and storage. With the integration of PV and battery, the new building was able to achieve a lower DoD and better performance with lower PV and battery capacity, compared to the old building. Furthermore, utilizing the color grading method (red to green), optimal technical solutions and corresponding design variables were identified for each building type and climate scenario that could support decision-making. The total cost of the optimal solutions varied, as new buildings required lower costs to reach optimal performance. However, for optimal resilience performance during extreme cold climate scenarios, higher costs are required for each building type. The proposed resilience framework, indicators, color grading system, and costing could potentially support improvements in building regulations, ensuring the development of optimally resilient buildings, particularly in the face of extreme climatic conditions. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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36 pages, 12052 KiB

Open AccessArticle

Building Information Modeling and AI Algorithms for Optimizing Energy Performance in Hot Climates: A Comparative Study of Riyadh and Dubai

by Mohammad H. Mehraban, Aljawharah A. Alnaser and Samad M. E. Sepasgozar

Buildings 2024, 14(9), 2748; https://doi.org/10.3390/buildings14092748 - 2 Sep 2024

Cited by 5 | Viewed by 3066

Abstract

In response to increasing global temperatures and energy demands, optimizing buildings’ energy efficiency, particularly in hot climates, is an urgent challenge. While current research often relies on conventional energy estimation methods, there has been a decrease in the efforts dedicated to leveraging AI-based [...] Read more.

In response to increasing global temperatures and energy demands, optimizing buildings’ energy efficiency, particularly in hot climates, is an urgent challenge. While current research often relies on conventional energy estimation methods, there has been a decrease in the efforts dedicated to leveraging AI-based methodologies as technology advances. This implies a dearth of multiparameter examinations in AI-driven extreme case studies. For this reason, this study aimed to enhance the energy performance of residential buildings in the hot climates of Dubai and Riyadh by integrating Building Information Modeling (BIM) and Machine Learning (ML). Detailed BIM models of a typical residential villa in these regions were created using Revit, incorporating conventional, modern, and green building envelopes (BEs). These models served as the basis for energy simulations conducted with Green Building Studio (GBS) and Insight, focusing on crucial building features such as floor area, external and internal walls, windows, flooring, roofing, building orientation, infiltration, daylighting, and more. To predict Energy Use Intensity (EUI), four ML algorithms, namely, Gradient Boosting Machine (GBM), Random Forest (RF), Support Vector Machine (SVM), and Lasso Regression (LR), were employed. GBM consistently outperformed the others, demonstrating superior prediction accuracy with an R² of 0.989. This indicates that the model explains 99% of the variance in EUI, highlighting its effectiveness in capturing the relationships between building features and energy consumption. Feature importance analysis (FIA) revealed that roofs (29% in Dubai scenarios (DS) and 40% in Riyadh scenarios (RS)), external walls (19% in DS and 29% in RS), and windows (15% in DS and 9% in RS) have the most impact on energy consumption. Additionally, the study explored the potential for energy optimization, such as cavity green walls and green roofs in RS and double brick walls with VIP insulation and green roofs in DS. The findings of the paper should be interpreted in light of certain limitations but they underscore the effectiveness of combining BIM and ML for sustainable building design, offering actionable insights for enhancing energy efficiency in hot climates. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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19 pages, 25530 KiB

Open AccessArticle

Multivariate Evaluation of Photovoltaic Utilization Potential of Primary and Secondary School Buildings: A Case Study in Hainan Province, China

by Chaohong Wang, Xudong Zhang, Wang Chen, Feihu Jiang and Xiaogang Zhao

Buildings 2024, 14(3), 810; https://doi.org/10.3390/buildings14030810 - 16 Mar 2024

Cited by 2 | Viewed by 1527

Abstract

Modernization and industrialization have significantly increased energy consumption, causing environmental problems. Given that China is the largest energy user, the rise in building energy consumption necessitates clean energy alternatives. The purpose of this study is to summarize typical building models for primary and [...] Read more.

Modernization and industrialization have significantly increased energy consumption, causing environmental problems. Given that China is the largest energy user, the rise in building energy consumption necessitates clean energy alternatives. The purpose of this study is to summarize typical building models for primary and secondary schools in Hainan Province, and to use software to simulate and calculate the photovoltaic utilization potential of primary and secondary school buildings. In China, the government is usually the manager of primary and secondary schools, and due to their architectural characteristics, these buildings can be used to assess photovoltaic applications. The aim is to drive the application of photovoltaic systems in all types of buildings and promote urban energy reform. This study summarizes the types of primary and secondary school buildings in Hainan Province and analyzes them. It evaluates rooftop photovoltaic projects at the Second Middle School and the Siyuan School in Wanning City, Hainan Province, and uses PVsyst 7.2 software to assess the photovoltaic utilization potential. The results show that the optimal orientation in Hainan Province is south-facing, and the optimal inclination angle is 10° to 20°. The most favorable orientations of facade photovoltaic systems are 20° southeast or southwest. The longest dynamic investment payback period is approximately 15 years, and the environmental benefits are $0.012/kWh. The findings indicate significant potential for photovoltaic applications in primary and secondary school buildings. A combination of facade and rooftop photovoltaics can result in the zero-energy consumption of these buildings, reducing the pressure on urban power grids and achieving sustainable utilization. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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14 pages, 2899 KiB

Open AccessArticle

Green Energy Harvesting and Management Systems in Intelligent Buildings for Cost-Effective Operation

by Qingbin Dai, Jingui Qian, Shun Li and Li Tao

Buildings 2024, 14(3), 769; https://doi.org/10.3390/buildings14030769 - 12 Mar 2024

Cited by 2 | Viewed by 2158

Abstract

Nowadays, the rise of Internet of Things (IoT) devices is driving technological upgrades and transformations in the construction industry, the integration of IoT devices in buildings is crucial for both the buildings themselves and the intelligent cities. However, large-scale IoT devices increase energy [...] Read more.

Nowadays, the rise of Internet of Things (IoT) devices is driving technological upgrades and transformations in the construction industry, the integration of IoT devices in buildings is crucial for both the buildings themselves and the intelligent cities. However, large-scale IoT devices increase energy consumption and bring higher operating costs to buildings. Therefore, harvesting the ambient cost-effective and clean energy sources is essential for the future development of intelligent buildings. In this work, we investigate the feasibility of integrating a typical triboelectric droplet energy harvester (DEH) into buildings. We demonstrate the energy harvesting capabilities of DEH on different sloped roof surfaces and complex curved building surfaces by simulating rainy weather with various rainfall intensities. The results indicate energy harvesting efficiency increases with larger tilt angles, which guides future smart architectural designs. This work is significant for the future integration of diversified, all-weather green energy collection and management systems, including raindrop energy, wind power generation, and solar energy, which will contribute to energy conservation and cost control in the next generation of smart buildings. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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28 pages, 5149 KiB

Open AccessArticle

Renewable Energy Use for Buildings Decarbonization Causes Inequity in Consumers? Comparative Analysis of Spain, Mexico, and Colombia

by Iván Valencia-Salazar, Elisa Peñalvo-López, Vicente León-Martínez and Joaquín Montañana-Romeu

Buildings 2024, 14(3), 665; https://doi.org/10.3390/buildings14030665 - 1 Mar 2024

Viewed by 1632

Abstract

Building decarbonization strategy with Distributed renewable energy sources (DRES) is applied and extended worldwide for its climate change mitigation benefits, however, it generates debate regarding equity in sharing electric system operation costs. To analyze DRES effects on equity, it is conducted a case [...] Read more.

Building decarbonization strategy with Distributed renewable energy sources (DRES) is applied and extended worldwide for its climate change mitigation benefits, however, it generates debate regarding equity in sharing electric system operation costs. To analyze DRES effects on equity, it is conducted a case study, in which same residential consumer is evaluated in three different markets (Spain, Mexico, Colombia). We analyze not only electrical system technical variables, but we also include society’s economic, social, technological, and environmental characteristics. Next, energy, economic, and environmental benefits are obtained in each the three case studies, analyzing the impact of using DERS on equity to recover electric system operating costs. We also evaluate whether tariff mechanisms are equitable to motivate all consumers participation, as well as whether all consumers have equal opportunity for using DERS. We conclude that tariff mechanisms in Mexico and Colombia lead to inequity to recover market operating costs, favoring large consumers with high incomes. Furthermore, tariff mechanisms discourage the use of DERS by small and medium consumers due to economic, social, and technological aspects. In Spain, inequity arises due to increased difficulty for some consumers to use DERS, i.e., consumers in apartment buildings. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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27 pages, 7429 KiB

Open AccessArticle

International Comparison of Weather and Emission Predictive Building Control

by Christian Hepf, Ben Gottkehaskamp, Clayton Miller and Thomas Auer

Buildings 2024, 14(1), 288; https://doi.org/10.3390/buildings14010288 - 20 Jan 2024

Cited by 4 | Viewed by 1780

Abstract

Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial [...] Read more.

Building operational energy alone accounts for 28% of global carbon emissions. A sustainable building operation promises enormous savings, especially under the increasing concern of climate change and the rising trends of the digitalization and electrification of buildings. Intelligent control strategies play a crucial role in building systems and electrical energy grids to reach the EU goal of carbon neutrality in 2050 and to manage the rising availability of regenerative energy. This study aims to prove that one can create energy and emission savings with simple weather and emission predictive control (WEPC). Furthermore, this should prove that the simplicity of this approach is key for the applicability of this concept in the built world. A thermodynamic simulation (TRNSYS) evaluates the performance of different variants. The parametrical study varies building construction, location, weather, and emission data and gives an outlook for 2050. The study showcases five different climate locations and reveals heating and cooling energy savings of up to 50 kWh/(m²a) and emission savings between 5 and 25% for various building types without harming thermal comfort. This endorses the initial statement to simplify building energy concepts. Furthermore, it proposes preventing energy designers from overoptimizing buildings with technology as the solution to a climate-responsible energy concept. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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23 pages, 6081 KiB

Open AccessArticle

Impacts of Rooftop Photovoltaics on the Urban Thermal Microclimate: Metrological Investigations

by Elisabeth Fassbender, Simon Pytlik, Josef Rott and Claudia Hemmerle

Buildings 2023, 13(9), 2339; https://doi.org/10.3390/buildings13092339 - 14 Sep 2023

Cited by 5 | Viewed by 1764

Abstract

Ambitious climate protection requires decentralized renewable energy production via building-related photovoltaics in cities. However, cities are also subject to the Urban Heat Island effect, which negatively impacts human health. In this context, the installation of PV modules in urban areas raises the question [...] Read more.

Ambitious climate protection requires decentralized renewable energy production via building-related photovoltaics in cities. However, cities are also subject to the Urban Heat Island effect, which negatively impacts human health. In this context, the installation of PV modules in urban areas raises the question of how the energy-active building component affects its surrounding thermal microclimate. The topic is approached with a novel, twofold methodology: First, a horizontal ambient air temperature profile above a rooftop PV installation and the analysis of surface temperatures provide primal indications of the impacts of PV on the thermal microclimate. Secondly, establishing energy balances allows us to retrace the energy fluxes. The data required for the comparative analyses are gathered through metrological investigations of two rooftops with and without PVs in Munich, Germany. The results of the investigation show a daytime heating effect of photovoltaics on the ambient air temperature of up to +1.35 K and a nighttime cooling effect of up to −1.19 K. Cumulated daily, the daytime heating effect exceeds the impact of the nighttime cooling. The main driver of the heating and cooling is the additional convective heat transfer from the PV modules. However, the impacts of the PV modules are marginal and restricted to their direct surroundings. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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21 pages, 3317 KiB

Open AccessArticle

Impact of a Weather Predictive Control Strategy for Inert Building Technology on Thermal Comfort and Energy Demand

by Christian Hepf, Lennard Overhoff, Sebastian Clark Koth, Martin Gabriel, David Briels and Thomas Auer

Buildings 2023, 13(4), 996; https://doi.org/10.3390/buildings13040996 - 10 Apr 2023

Cited by 6 | Viewed by 2376

Abstract

The sun’s total radiation alone exceeds the world population’s entire energy consumption by 7.500 times and ignites secondary renewable energy sources. The end energy consumption buildings use for heating amounts to 28% of Germany’s total energy consumption. With the ongoing trend of digitalization [...] Read more.

The sun’s total radiation alone exceeds the world population’s entire energy consumption by 7.500 times and ignites secondary renewable energy sources. The end energy consumption buildings use for heating amounts to 28% of Germany’s total energy consumption. With the ongoing trend of digitalization and the transition of the German energy supply away from fossil fuels and the consequent political dependency, electric heat pumps and photovoltaic (PV) systems have become increasingly important to the discussion. This has led to an increasing demand for smart control strategies, especially for inert systems such as thermally activated building systems (TABS). This paper presents and analyses a weather predictive control (WPC) strategy using a validated thermodynamic simulation model. The literature review of this paper outlines that the current common control strategies are data intense and complex in their implementation into the built environment. The simple approach of the WPC uses future ambient temperature and solar radiation to optimize the control of the heating, cooling, ventilation, and sun protection system. The thermal comfort and energy demand evaluate the concept. We show that with a WPC for TABS, thermal comfort can improve without increasing the energy demand for the office building in the moderate climate of Munich. Furthermore, this paper concludes that the WPC works more effectively with more thermal mass. This simplified building control strategy promotes the European roadmap goal of climate neutrality in 2050, as it bridges the phenomenon of the performance gap. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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14 pages, 1934 KiB

Open AccessArticle

Application of Scheduling Techniques for Load-Shifting in Smart Homes with Renewable-Energy-Sources Integration

by Otilia Elena Dragomir and Florin Dragomir

Buildings 2023, 13(1), 134; https://doi.org/10.3390/buildings13010134 - 4 Jan 2023

Cited by 7 | Viewed by 2521

Abstract

The general context of this proposal is represented by the energy-efficient smart home that integrates renewable energy sources such as photovoltaic panels. The objective of this article is to minimize the amount of energy consumed from the national energy grid by producer-consumers of [...] Read more.

The general context of this proposal is represented by the energy-efficient smart home that integrates renewable energy sources such as photovoltaic panels. The objective of this article is to minimize the amount of energy consumed from the national energy grid by producer-consumers of energy from renewable sources, in their own smart homes. In order to fulfill this goal, it was necessary to estimate the amount of renewable energy produced on the day-ahead horizon and to schedule the operation of controllable consumers in a smart home. To predict the amount of energy produced, two approaches were used: the first was based on data, and used techniques specific to artificial intelligence, more specifically, multilayer perceptron and radial-basis-function neural networks, and the second was based on models. The accuracy of the short-term prediction horizon of the techniques used was evaluated with quantitative performance indicators so that the most appropriate one in relation to the goal of the article could be selected to be used in the test scenarios. The scheduling of consumer functioning was based on their classification in relation to their ability to be controlled, and on the selection from the peer-reviewed literature of an optimization algorithm which, by load shifting from a smart home, ensured the optimal fulfillment of the objective function. The selected load-shifting algorithm was then integrated into and tested on a real database. The data used were monitored for two representative days, in terms of the amount of energy from renewable energy sources produced and consumed. The load-shifting algorithm proved its effectiveness through the results obtained and which are reported in the article. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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18 pages, 4424 KiB

Open AccessFeature PaperArticle

Impact of Dynamic Emission Factors of the German Electricity Mix on the Greenhouse Gas Balance in Building Operation

by Christian Hepf, Konstantin Bausch, Lukas Lauss, Sebastian Clark Koth and Thomas Auer

Buildings 2022, 12(12), 2215; https://doi.org/10.3390/buildings12122215 - 14 Dec 2022

Cited by 6 | Viewed by 2357

Abstract

Due to climate change, emission balancing is a relevant tool to quantify the environmental impact of a building system. The electrification of energy production at a national level, as well as energy supply at a building level, shifts the focus to the emission [...] Read more.

Due to climate change, emission balancing is a relevant tool to quantify the environmental impact of a building system. The electrification of energy production at a national level, as well as energy supply at a building level, shifts the focus to the emission factor (EF) of the electricity grid. Currently, static EFs are used for calculating the emission balance. However, the electricity grid already shows fluctuations in power generation and EF due to renewable energies. The paper reviews recent literature outlining the research gap and presents the development of a simulation setup and concept, in which the emission balance of the building operation changes, using dynamic EFs that map fluctuations at an hourly resolution. In the first step, we simulate the thermal building and radiance performance. The data are than used in a second step to conduct a system simulation, which analyzes the effects of the dynamic EFs. The results show that the dynamic balance approach for different building system variants deviates considerably from the static approach. By comparing different concepts for the loading strategy, the predictive strategy outperforms a common control strategy, when considering the energy prices and/or the emissions. This is especially true for systems with inert storage units, where charging times significantly influence the balance, as well as for systems with PV integration. This paper outlines the potential of the EFs-optimized control increases when evaluating a potential scenario for the year 2040, factoring in increased seasonal and daily fluctuations in electricity generation. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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16 pages, 2654 KiB

Open AccessArticle

A Case Study of Mapping the Heating Storage Capacity in a Multifamily Building within a District Heating Network in Mid-Sweden

by Abolfazl Hayati, Jan Akander and Martin Eriksson

Buildings 2022, 12(7), 1007; https://doi.org/10.3390/buildings12071007 - 13 Jul 2022

Cited by 2 | Viewed by 2371

Abstract

The building sector accounts for a third of the total energy use in Sweden, and district heating provides half of the heating needs. The peak demand loads within a district heating network occur both regularly and irregularly and impose a burden on the [...] Read more.

The building sector accounts for a third of the total energy use in Sweden, and district heating provides half of the heating needs. The peak demand loads within a district heating network occur both regularly and irregularly and impose a burden on the energy company to fulfill the demand, often by using more expensive and less environmentally friendly resources (e.g., fossil fuels) instead of the waste heat from industry or biofuels. Heat storage during hours of less demand and prior to colder periods can be used for load management and sustainable planning of energy supply, as well as reduction of total greenhouse gas emissions. Thus, heat supply to the building can be lowered temporarily during the peak power period to utilize the stored thermal energy within the building thermal inertia. The use of indoor temperature decay and the delivery of heating power to a multifamily building are studied here, and heating storage capacity and thermal inertia are calculated. During the performed decay test, the energy supply was estimated to be reduced by 61% for 5 h, which resulted in only a 0.3 °C temperature decay. Therefore, the suggested method can shave eventual peaks in supplied heat with minimal influence on the thermal comfort. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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20 pages, 1871 KiB

Open AccessArticle

Energy Production of Solar DSF for Ceiling-Mounted Localized Air Distribution Systems in a Virtual Classroom

by Eusébio Conceição, João Gomes, Maria Manuela Lúcio and Hazim Awbi

Buildings 2022, 12(4), 495; https://doi.org/10.3390/buildings12040495 - 16 Apr 2022

Cited by 3 | Viewed by 2341

Abstract

This paper presents an application of energy production in a solar Double Skin Facade (DSF) used in a Heating, Ventilation and Air-Conditioning (HVAC) system for a ceiling-mounted localized air distribution systems in a virtual classroom. In this numerical work, a virtual classroom, an [...] Read more.

This paper presents an application of energy production in a solar Double Skin Facade (DSF) used in a Heating, Ventilation and Air-Conditioning (HVAC) system for a ceiling-mounted localized air distribution systems in a virtual classroom. In this numerical work, a virtual classroom, an inlet ceiling-mounted localized air distribution system, an exhaust ventilation system, and a DSF system are considered. The numerical simulations consider an integral building thermal response (BTR) and a coupling of an integral human thermal-physiology response (HTR) and differential computational fluid dynamics (CFD). The BTR numerical model calculates, among other parameters, the DSF indoor air temperature and energy production. The HTR numerical model calculates, among other parameters, the human thermal comfort. The CFD numerical model, among other parameters, calculates the indoor air quality. In this study which is performed for winter conditions, the energy produced in the DSF is used for driving the HVAC system. Six different airflow rates are used. The air temperature and energy production in the DSF are also evaluated. The influence of the airflow rate on the HVAC system performance is evaluated by the Air Distribution Index for mid-morning and mid-afternoon conditions. The results show that energy production reduces when the airflow increases and the operating point can be selected using the acceptable levels of thermal comfort and air quality levels or using the maximum Air Distribution Index value. In this study, the application of the thermal comfort and air quality levels criteria demonstrates that the HVAC system uses an optimum airflow rate. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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25 pages, 11104 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Implementation of BIM Energy Analysis and Monte Carlo Simulation for Estimating Building Energy Performance Based on Regression Approach: A Case Study

by Faham Tahmasebinia, Ruifeng Jiang, Samad Sepasgozar, Jinlin Wei, Yilin Ding and Hongyi Ma

Buildings 2022, 12(4), 449; https://doi.org/10.3390/buildings12040449 - 5 Apr 2022

Cited by 30 | Viewed by 6815

Abstract

The energy performance prediction of buildings plays a significant role in the design phases. Theoretical analysis and statistical analysis are typically carried out to predict energy consumption. However, due to the complexity of the building characteristics, precise energy performance can hardly be predicted [...] Read more.

The energy performance prediction of buildings plays a significant role in the design phases. Theoretical analysis and statistical analysis are typically carried out to predict energy consumption. However, due to the complexity of the building characteristics, precise energy performance can hardly be predicted in the early design stage. This study considers both building information modeling (BIM) and statistical approaches, including several regression models for the prediction purpose. This paper also highlights a number of findings of energy modeling related to building energy performance simulation software, particularly Autodesk Green Building Studio. In this research, the geometric models were created using Autodesk Revit. Based on the energy simulation conducted by Autodesk Green Building Studio (GBS), the energy properties of five prototype and case study models were determined. The GBS simulation was carried out using DOE 2.2 engine. Eight parameters were used in BIM, including building type, location, building area, analysis year, floor-to-ceiling height, floor construction, wall construction, and ceiling construction. The Monte Carlo simulation method was performed to predict precise energy consumption. Among the regression models developed, the single variable linear regression models appear to have high accuracy. Although there exist some limitations in applying the equation in EUI prediction, the rough estimation of energy use was realized. Regression model validation was carried out using the model from the case study and Monte Carlo simulation results. A total of 35 runs of validation were performed, and most differences were maintained within 5%. The results show some limitations in the application of the linear regression model. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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29 pages, 8597 KiB

Open AccessFeature PaperArticle

Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings

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

Buildings 2022, 12(3), 329; https://doi.org/10.3390/buildings12030329 - 9 Mar 2022

Cited by 43 | Viewed by 10213

Abstract

It has been challenging for designers to identify the appropriate design parameters that would reduce building energy consumption while achieving thermal comfort for building occupants. This study aims to determine the most important architectural building design parameters (ABDPs) that can increase thermal comfort [...] Read more.

It has been challenging for designers to identify the appropriate design parameters that would reduce building energy consumption while achieving thermal comfort for building occupants. This study aims to determine the most important architectural building design parameters (ABDPs) that can increase thermal comfort and reduce energy use in educational buildings. The effect of 15 ABDPs in an Australian educational lecture theatre and their variabilities on energy consumption and students’ thermal comfort for each parameter were analysed using Monte Carlo (MC) techniques. Two thousand simulations for every input parameter were performed based on the selected distribution using the Latin hypercube sampling (LHS) technique. Sensitivity analyses (SA) and uncertainty analyses (UA) were used to assess the most important ABDPs in terms of thermal discomfort hours and energy consumption. The study found that the ABDPs, such as cooling set-point temperatures and roof construction, significantly reduce the operative temperature by up to 14.2% and 20.0%, respectively. Consequently, these reductions could significantly shorten the thermal discomfort hours, thereby reducing energy consumption by 43.7% and 41.0%, respectively. The findings of this study enable building designers to identify which ABDPs have a substantial impact on thermal comfort and energy consumption. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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23 pages, 1654 KiB

Open AccessArticle

A Framework for Developing Green Building Rating Tools Based on Pakistan’s Local Context

by Muhammad Afrasiab Khan, Cynthia Changxin Wang and Chyi Lin Lee

Buildings 2021, 11(5), 202; https://doi.org/10.3390/buildings11050202 - 12 May 2021

Cited by 33 | Viewed by 6951

Abstract

Most countries have developed green building rating tools that are based on social, environmental, and economic dimensions. Pakistan followed a similar approach and has developed a rating tool known as Sustainability in Energy and Environmental Development (SEED). However, SEED is built on developed [...] Read more.

Most countries have developed green building rating tools that are based on social, environmental, and economic dimensions. Pakistan followed a similar approach and has developed a rating tool known as Sustainability in Energy and Environmental Development (SEED). However, SEED is built on developed western countries’ rating tool standards which do not address Pakistan’s unique local context, especially from the cultural and governmental perspectives. This research aims to fill this research gap by developing a holistic framework of building rating tools that incorporates cultural and governmental dimensions. Based on an extensive literature review, a hypothetical framework, incorporating Pakistan’s unique local contexts and adding cultural and governmental dimensions to the widely adopted social, environmental, and economic dimensions of sustainability, was proposed in this paper. This framework was further validated by in-depth interviews with multiple stakeholders in Pakistan. A qualitative analysis of the interview results was carried out, and the final framework was proposed with key indicators, reflecting all five dimensions of sustainability. The verified sustainability framework can be used to improve or develop green building rating tools for Pakistan, and it can also inform other developing countries’ rating tool development. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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18 pages, 2788 KiB

Open AccessArticle

Optimal Sizing of Solar-Assisted Heat Pump Systems for Residential Buildings

by Alessandro Franco and Fabio Fantozzi

Buildings 2020, 10(10), 175; https://doi.org/10.3390/buildings10100175 - 4 Oct 2020

Cited by 12 | Viewed by 3796

Abstract

This paper analyzes the optimal sizing of a particular solution for renewable energy residential building integration. The solution combines a photovoltaic (PV) plant with a heat pump (HP). The idea is to develop a system that permits the maximum level of self-consumption of [...] Read more.

This paper analyzes the optimal sizing of a particular solution for renewable energy residential building integration. The solution combines a photovoltaic (PV) plant with a heat pump (HP). The idea is to develop a system that permits the maximum level of self-consumption of renewable energy generated by using a small-scale solar array installed on the same building. The problem is analyzed using data obtained from an experimental system installed in a building in Pisa, Italy. The residential house was equipped with a PV plant (about 3.7 kW of peak power), assisting a HP of similar electrical power (3.8 kW). The system was monitored for eight years of continuous operation. With reference to the data acquired from the long-term experimental analysis and considering a more general perspective, we discuss criteria and guidelines for the design of such a system. We focus on the possibility of exporting energy to the electrical grid, from the perspective of obtaining self-consumption schemes. Considering that one of the problems with small-scale PV plants is represented by the bidirectional energy flows from and to the grid, possible alternative solutions for the design are outlined, with both a size reduction in the plant and utilization of a storage system considered. Different design objectives are considered in the analysis. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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Review

Jump to: Research

24 pages, 7789 KiB

Open AccessReview

State-of-the-Art Technologies for Building-Integrated Photovoltaic Systems

by Hussein M. Maghrabie, Mohammad Ali Abdelkareem, Abdul Hai Al-Alami, Mohamad Ramadan, Emad Mushtaha, Tabbi Wilberforce and Abdul Ghani Olabi

Buildings 2021, 11(9), 383; https://doi.org/10.3390/buildings11090383 - 27 Aug 2021

Cited by 52 | Viewed by 8230

Abstract

Advances in building-integrated photovoltaic (BIPV) systems for residential and commercial purposes are set to minimize overall energy requirements and associated greenhouse gas emissions. The BIPV design considerations entail energy infrastructure, pertinent renewable energy sources, and energy efficiency provisions. In this work, the performance [...] Read more.

Advances in building-integrated photovoltaic (BIPV) systems for residential and commercial purposes are set to minimize overall energy requirements and associated greenhouse gas emissions. The BIPV design considerations entail energy infrastructure, pertinent renewable energy sources, and energy efficiency provisions. In this work, the performance of roof/façade-based BIPV systems and the affecting parameters on cooling/heating loads of buildings are reviewed. Moreover, this work provides an overview of different categories of BIPV, presenting the recent developments and sufficient references, and supporting more successful implementations of BIPV for various globe zones. A number of available technologies decide the best selections, and make easy configuration of the BIPV, avoiding any difficulties, and allowing flexibility of design in order to adapt to local environmental conditions, and are adequate to important considerations, such as building codes, building structures and loads, architectural components, replacement and maintenance, energy resources, and all associated expenditure. The passive and active effects of both air-based and water-based BIPV systems have great effects on the cooling and heating loads and thermal comfort and, hence, on the electricity consumption. Full article

(This article belongs to the Special Issue Renewable Energy in Buildings)

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