Building Systems Research Articles

Transient analysis and thermal design of a solar-powered cooling system for an office building: Enhancements using phase change materials and zeotropic mixtures in ejector refrigeration cycle

This study explores an innovative integration of solar energy with thermal energy storage for power production and cooling system support, utilizing phase change materials (PCMs) to enhance solar system performance, particularly for the cooling demands of an office building. The cooling load of a target office building in Ardabil City, Iran, is calculated for a typical day. Optimization is conducted using Multi-Objective Particle Swarm Optimization (MOPSO) to select the optimal zeotropic mixture as the working fluid, aimed at maximizing efficiency and minimizing heat source requirements. The system is designed to meet the needs of a two-story office building. Analysis of photovoltaic modules integrated with PCM under various parameters led to the selection of 25 PVT-PCM units in a series. The total setup includes 730 modules covering 365 m2, achieving a mass flow rate of 2.92 kg/s and supporting a 40 kW cooling load in the Ejector Refrigeration Cycle (ERC). The development of this solar-powered cooling system presents a sustainable, economically viable solution for building cooling. It demonstrates significant advancements in thermal efficiency through the strategic use of PCMs and optimized zeotropic mixtures in ejector refrigeration cycles. The system's scalable design offers a model for adapting to diverse climatic conditions, marking a notable contribution to sustainable building technologies.

Dynamic grid emission factors and export limits reduce emission abatement and cost benefits of building PV systems

Photovoltaic (PV) installations in the building sector are expected to play a crucial role in Switzerland's efforts to achieve decarbonization targets. Nevertheless, most analyses on PV system design prioritize economic factors, and overlook the impact of angle-dependent PV generation, dynamic grid greenhouse gas (GHG) emissions, and export limitations on their emission abatement potential during operation. Our study sheds light on the cost- and emission-optimal orientation and sizing of PV systems in buildings, factoring in hourly grid GHG emission intensity and curtailment measures. We employ mixed-integer linear programming (MILP) and illustrate the methodology for a case study building under different scenarios, aiming to minimize costs and emissions by considering a combination of rooftop and façade PV systems, and a battery. We show that assuming a constant annual grid GHG emission intensity may overestimate annual emission abatement potential of PV generation by a factor of two, emphasizing the need for dynamic grid GHG emission intensity. When considered, cost-optimal solutions favour larger systems that maximize total production. In contrast, emission-optimal solutions increase self-consumption via inclusion of battery systems. Curtailment due to export limitations reduces the cost and emission benefits of excess generation (from feed-in tariff payments and carbon credits), prompting a trend towards smaller PV installations with steeper panel tilts. Thus, the emission abatement potential of PV generation heavily depends on the option to export excess electricity production.

Research on a zero water consumption operation model and feasibility for office buildings

ABSTRACT According to Taiwan's government policy on net zero emissions by 2050, building designs are moving toward zero energy and zero water consumption to achieve these challenge goals. Among these goals, establishing an independent water cycle within building systems is a primary objective. The present study examined office buildings as the research subject due to their crucial water usage characteristics, which can serve as a reference for other building types. We developed a water-use estimation model by conducting a literature review and data collection from existing green office building cases in Taiwan. The methods involved calculating the median annual water consumption per unit building area and discussing the current water-saving design status and water-saving rate. The findings indicate a median water-saving rate of 53%, which is far short of the goal of achieving a zero water building. This finding is primarily attributed to the infrequent use of water compensation in building designs. The feasibility of a zero water building is validated and determines its crucial operation. Consequently, design engineers can employ this methodology to compute water conservation rates for their designs, aiming for the construction of a zero water consumption building.

Configuration optimization and performance analysis of hybrid PV/wind systems in building groups

Distributed hybrid renewable energy is a promising technology for addressing environmental and energy issues, and its performance and system configuration play an essential role in the application. However, the contribution of energy sharing among buildings in building groups to the matching performance has yet to be fully explored. This study established a joint MATLAB-TRNSYS optimization model for the hybrid PV/wind building system to investigate the matching performance of energy consumption in building groups and energy production in PV/wind systems. The optimal system configuration for three objectives, technical, economic, and environmental, was also studied using the multi-objective particle swarm algorithm. Several factors influencing system performance and configuration were considered: renewable energy hybrid, a hybrid of different buildings, intensity of energy use and energy resource, and economic parameters. The results reveal that a hybrid system outperforms a single system, particularly a PV system with a smaller roof area and less installed capacity. Additionally, wind turbines contribute more to system performance than PV panels. Mixing buildings with different heights and functions could also improve system performance by renewable energy sharing in most instances, except multi-story office buildings. Increasing wind resources improves system performance more than solar resources, and increasing energy use intensity negatively impacts system performance for residential buildings but is beneficial for office buildings. Higher grid prices and feed-in tariffs can bring more economic benefits. This study revealed the contribution of energy sharing among different buildings, which could support better application of distributed hybrid renewable energy systems in complex urban environments.

Performance analysis of multi-stack fuel cell systems for large buildings using electricity and heat

The fuel cell market, which utilizes hydrogen as a fuel for zero-carbon power generation to address global warming, continues to grow steadily. In the building sector, where small-scale fuel cells of 10 kW or less have been predominant, there is increasing interest in scaling up fuel cells to increase deployment and reduce system costs. The multi-stack fuel cell system (MFCS), which consists of connecting multiple modules, is one method of configuring large-scale fuel cell systems, offering advantages in system efficiency, durability, and cost. The objective of this paper is to compare and analyze the behavior of the MFCS according to different operation strategies. In particular, it compares the Equivalent operation method, which behaves similarly to the single-stack fuel cell system (SFCS), with others (Daisy-Chain, Electrical Optimization). Unlike previous studies that only focused on the electrical efficiency of MFCS, this study analyzed thermal energy, which is indispensable in building applications, to maximize the effects of MFCS. Simulation of operation strategies based on the electricity and heat demand of a specific residence showed that MFCS outperformed the SFCS in terms of electrical and heat efficiency, hydrogen consumption, degradation, and operating costs.

Measuring the Performance of Industrialized Building System (IBS) Construction on Projects Towards Achieving IR 4.0 in Malaysia- Contractor’s Perspective

According to prolonged project completion times, excessive costs, and inadequate building products, the majority of construction projects are seen as underperforming. Alternatively, stakeholders are encouraged to move from conventional to Industrialized Building Systems (IBS) in line with today's technology. Previous studies show the performance of IBS practices in the Malaysian construction industry is still at a low level even though the government has diversified promotions and issued instructions for 70% of IBS use in government projects. These selection criteria affect contractors' performance of IBS practices and need to be done in a systematic way, along with current technology trends and sustainability. Content validity in IBS practice performance is an important step in instrument development. Content validity in IBS practice performance is an important step in instrument development. Therefore, this research aims to evaluate the content validity of the performance effectiveness of IBS practices by using the content validity index (CVI) and modified Kappa sensitivity. In an effort to accomplish the objectives of this study, a questionnaire was created using construct items that were taken from earlier research projects by various researcher. A panel of selected experts who are experienced in the field of IBS, such as CIDB, ​​JKR and contractors have reviewed and evaluated pig instruments to ensure the relevance of each item. The final instrument contains 39 items that are valid and considered permanent and all items will be tested again in the next study. The results showed that the S-CVI/AVE for every item met every requirement and received an outstanding rating for every assessment.

A comparative study of dynamic performance the shear-wall and bracing shapes on the tall building in seismic area

The solution to overcome earthquake loads in the seismic regions is to use resisting systems such as shear walls and braces. It can be used as an alternative design for resisting systems of tall buildings. The main purpose of this research is to compare the performance of tall buildings with resisting systems of partial shear walls and a variety of brace shapes in the seismic area of Malang City, Indonesia, by using the partial shear wall against braces of reinforced concrete in the shapes of V, inverted V (Ʌ) and X (on two floors). The mechanical properties of the materials utilized in the models are determined from laboratory testing results. They consist of 30 MPa compressive strength concrete, 250 MPa yield strength steel, and 410 MPa ultimate strength steel. To overcome the lack of bracing, position the braces on the outer side of the building and the number resisting. The several outputs reviewed are stiffness, displacement, drift, ductility, vibration period, and natural frequency. In this study, structural analysis using SAP 2000 v.20 software is used in the four models of the eight-story existing structure in Malang City. The results showed that the inverted V (Ʌ) reinforced concrete brace is the most suitable design as an alternative design for the building, compared to the partial shear wall and the other bracing shapes. The results of the study that in the X-direction the stiffness, displacement, drift, ductility, vibration period, and natural frequency respectively as follows 4.92865E+12 N/mm, 144.53 mm, 127.73 mm, 0.339, 1.12 s and 0.893 Hz. Whereas the displacement and drift in the Y-direction are 127.97 mm and 113.63mm. For practical implication, using a fully shear wall and the inverted V(Ʌ) brace creates a better performance of the structure in seismic areas.

Adaptive neural network control of a centrifugal chiller system

In this paper, a neuro-adaptive PI control strategy for a water-cooled centrifugal chiller system is developed, and its control performance is examined. The system model consists of a flooded evaporator, a flooded condenser, a centrifugal compressor, and an electronic expansion valve. The overall system consists of three control loops: a compressor speed control loop, an inlet guide vane (IGV) control loop, and a condenser liquid level control loop. A neuro-adaptive control strategy for compressor speed control was designed. The control performance of the chiller was tested by carrying out simulation runs using an integrated building and HVAC (IB-HVAC) system model. The major details of the IB-HVAC model are described in this paper. Results show that the neuro-adaptive controller can adapt to new system dynamics of the IB-HVAC system and give good setpoint tracking responses under a wide range of operating conditions. The results show that the neuro-adaptive controller performs better than the constant gain PI controller in terms of speed of response and setpoint tracking properties.

Identifying untraced faults associated with high return temperatures from heating systems in buildings connected to district heating networks

The district heating (DH) system is in its transition towards the 4th generation district heating (4GDH), and the high DH return temperatures need to be addressed during the process. In the existing building heating systems, many faults, malfunctions, or sub-optimal operations can lead to high DH return temperatures. However, the field of fault detection and diagnostics (FDD) within heating systems is notably under-researched in contrast to their counterparts in ventilation and air conditioning in building HVAC systems. This divergence can be attributed to several factors, including limited digital integration, a scarcity of data, and the non-obvious nature of faults in heating systems. In this study, we utilized heat cost allocators (HCA) and energy meters to investigate the features and potential impacts of four untraced faults that can lead to high district heating (DH) return temperatures in both space heating and domestic hot water systems in large buildings. We identified component-level faults, including heat exchanger overflow, space heating temperature controller failures, and excessive operating temperatures due to bypass, as well as system-level issues such as non-uniform heat distribution in buildings and its impacts. This exploration provides new, critical insights for advancing FDD research in HVAC and DH systems.

Comprehensive performance evaluation of HVAC systems integrated with direct air capture of CO2 in various climate zones

Direct Air Capture (DAC) is a rapidly evolving technology that extracts CO2 directly from ambient air. This study presents a comprehensive performance evaluation of integrating DAC in HVAC systems, which can reduce indoor CO2 concentration and improve energy efficiency of HVAC systems. The DAC equipment is modeled in Modelica based on isotherm and thermodynamic equations, and pressure drop curves of the CO2 sorbent described in literature. The model is validated with data from the literature, and then integrated into a typical HVAC system available in Modelica Buildings library. The HVAC system is a Variable Air Volume (VAV) with reheater system for a one-floor office building with standard ASHRAE 2006 control sequences. Demand control ventilation strategies are designed to reduce the outdoor air flowrates when indoor CO2 concentrations are lower than the threshold, which is to maximize the benefits of integrating DAC. Four cases are proposed to assess the impacts of integrating DAC and DCV in HVAC systems in 8 different ASHRAE climate zones in the USA. The results show that by integrating DAC unit into the HVAC system, the average indoor CO2 concentration can be significantly reduced by over 45 % against the baseline without a DAC unit. By integrating DCV, 0.39–21.66 % of annual energy savings and 226–9539 kg carbon emissions reduction are observed across different climate zones. The highest energy savings are found to be achieved with cold climatic conditions while the lowest energy savings occur with favorable weather.

Systematic screening and evaluation for an optimal adsorbent in a facade-integrated adsorption-based solar cooling system for high-rise buildings

Solar-powered adsorption chillers are a climate-friendly solution for building cooling, but costs and space requirements limit their widespread adoption. Recently developed adsorption cooling facade systems (ACFS) save installation space and further reduce CO2 emissions. The performance of ACFS depends on the implemented adsorbent. To achieve low costs and high performance of ACFS, this study systematically screened and scored adsorbents using the analytic hierarchy process (AHP) method, focusing on price, stability, driving temperature and adsorption capacity. This method narrowed down 293 adsorbents to top 10 scored adsorbents including 4 silica gels, 4 active carbons and 2 molecular sieves. The adsorbent-specific performance is evaluated by numerical simulation, revealing silica gel Type A++, Type 2560, Siogel and molecular sieve AQSOA-FAM-Z02 have peak adsorber temperatures 1.5–9.3 °C lower and increase solar cooling efficiency (SCE) by 25–27 % compared to reference adsorbent Zeolite 13X. A sensitivity analysis of the Dubinin-Astakhov equation shows increasing E and decreasing V leads to an only minor adsorber temperature decrease and minor system efficiency increase. Lower temperatures and higher capacity cannot guarantee better system performance. This underscores that improving system performance cannot be achieved solely through adsorbent optimization but requires system optimization in parallel.

Framework for assessing the smart buildings intelligence degree

Assessing the intelligence degree of smart buildings is a complex challenge that has aroused researchers’ interest. In the researched literature, many indicators and factors used to assess building intelligence are generic and give rise to different interpretations. Furthermore, few studies establish criteria for measuring indicators, most of which are difficult to measure. Aiming to contribute to filling this gap, we proposed a framework for evaluating the intelligence degree of smart buildings and their systems, formed by indicators identified from extensive and detailed bibliographical research, which meets the premises of being easy to use, reducing the complexity of the evaluation process and enable a single interpretation by evaluators. The framework was organized by considering 91 indicators grouped into 11 sets relating to smart building systems, and it allows for the evaluation of the intelligence degree of four types of buildings: commercial, corporate, office, and apartment. We also propose a way to operate the framework through an electronic spreadsheet, mainly because electronic spreadsheets are commonly used and because the framework’s table format was easily translatable into an electronic spreadsheet. The results showed that all indicators were assessed as relevant, corroborating the view of the researchers who published on the topic. Also, the indicators were considered most relevant for commercial buildings, followed by corporate buildings, office buildings, and apartment buildings. They also show that the respondents considered the instrument adequate.

Evolutionary method of digital twin model for building physics mechanism

ABSTRACT Building digital twin (BDT) realizes real-time monitoring, prediction, and optimization control of the building system through the synchronization between the real world and the virtual platform, and improves the efficiency of building operation and maintenance. However, the changes in physical laws caused by the decline and aging of buildings make it difficult for the BDT models to depict the dynamic evolution mechanism of buildings and improve decision-making, which brings great challenges to the prediction and maintenance of buildings. To this end, an evolutionary method of digital twin model for building physics mechanisms is proposed, which integrates the internet of things (IoT), building information physical model (BIPM), and machine learning algorithms to build a self-evolution framework of digital twins for building physics mechanism, and supports high-precision modeling of BDTs. The advanced prediction (AP) model and autonomous decision-making (ADM) model for building physics mechanisms with self-evolution capability are designed, which support the autonomous correction of model parameters and the dynamic updating of the model driven by real-time data, and the ability to learn optimal control actions through interactive trial and error with the environment. The experimental results based on the settlement prediction and control case of underground engineering show that this evolutionary method can dynamically simulate the future evolution trend of the settlement law of underground engineering, and adjust the physical parameters to the ideal range to guide the evolution of underground engineering in a better direction. Compared with the existing methods, it has better prediction accuracy, interpretability, and generalization performance.

Effective Utilization of Pre Engineering building (PEB) construction for Development of Rapid Healthcare facilitates in Medical Emergency

World is developing at a faster pace in all spheres of technology. The parameters whichdetermine the development have changed a lot in the recent past and will keep changing in future too.Rapid rise in levels of education, high rates of technological innovations and applications, ever faster andcheaper communication that dissolves physical and social barriers both within countries andinternationally, greater availability and easier access to information, and the further opening up of globalmarkets are the set of catalytic forces that is accelerating the speed of social change throughout theworld.Pre Engiering building is one of the best application of fast track construction Pre-Engineered Buildingconcept involves the steel building systems which are predesigned and prefabricated .The presentconstruction methodology calls for the best aesthetic look, high quality fast construction, costeffective innovative touch. One has to think for alternative construction system like pre-engineeredsteel buildings. In recent years, the introduction of Pre Engineered Building (PEB) concept in the designof structures has helped in optimizing design. In this report the detail explore of pre engineering as afast tack construction’s application discuss . As the world battles the ongoing COVID-19 pandemic, ithas become very clear that societies depend on functioning healthcare facilities. The sufficientavailability of hospital beds, healthcare staff, protective gear or ventilators can make all the differencebetween a situation that is still manageable and a severe crisis. for this infrastructure facilities should beprepare in short time ,For this EPS Pannel and UPVC panels will be use for rapid construction ofhealthcare facilities

Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings

Installing photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based systems, necessitating innovative solutions. The research proposes a deep learning-based optimal energy management system designed specifically for home micro-grids that incorporate PV systems with battery energy storage, Enhanced Long Short-Term Memory (LSTM)-Based Optimal Home Micro-Grid Energy Management (OHM-GEM). Integrating an improved type of LSTM neural network called LSTM into the energy management system improves the reliability of PV power output predictions. The dependability of PV power production forecasts is increased by including a refined version of the LSTM neural network in the energy management system. The efficiency of the OHM-GEM system in maximizing PV system integration into buildings is shown by the authors using simulated data. With considerable gains in energy efficiency, cost savings, and decreased reliance on non-renewable energy sources, the results highlight the possibility of this approach to forward sustainable energy practices.

A dynamic simulation model for building cooling and heating energy considering climate-building system-occupant interactions

Residential buildings have a significant potential for energy conservation. The building energy consumption process is a complex system influenced by several factors at climate, building system, and occupant levels. This study introduces a novel model based on a multi-agent system to systematically integrate these multiple influencing factors, simulate their interactions, and estimate the resultant cooling and heating energy with dynamic variations over years considered. The automatic dynamic energy simulation was conducted over 30 years considering four temporal parameters (i.e., outdoor temperature, heat transfer coefficient of the building envelope, household type, and behavior pattern of occupants). A case building was used to validate the model, and the dynamic annual results were quite different from the static ones. The dynamic cumulative cooling energy consumption during 31 years was 0.69 % lower than the static one, whereas dynamic cumulative heating energy was 7.53 % higher compared with static energy. It highlighted the importance of considering dynamic multi-agent interactions. Besides, the roles of multiple energy influencing factors and dynamic parameters were compared and discussed. This study provides critical insights into improving building energy performance and offers a rapid and automatic approach for dynamic energy simulation.

Integration of Air Conditioning Systems in Intelligent Buildings to Increase Efficiency

Heating, ventilation, air conditioning, and cooling, collectively known as HVAC, account for more than 40% of the electricity consumed in buildings. Global climatic factors, referring to comfort and factors related to health, dictate that there is an increasing need for the application of HVAC/R systems. Therefore, it is increasingly compelling to investigate various approaches to enhance the effectiveness of air treatment systems. The automation of buildings has facilitated the integration of air treatment systems with “other existing” systems that can impact the indoor climatic conditions, such as automated windows and curtains, etc. In order to achieve this, it is essential to employ calculation techniques for air handling systems and for the heat transfer between buildings and the external environment. By integrating these systems, it becomes possible to maintain a comfortable environment while actively minimizing the electricity consumption of the heat pump. This article focuses on the integration of air conditioning systems in intelligent buildings to enhance efficiency.

Towards standalone commercial buildings in the Mediterranean climate using a hybrid metal hydride and battery energy storage system

Given the critical role of hybrid energy storage systems in the building sector for enhancing renewable energy reliability and integration, this study examines the techno-economic feasibility of adopting a dual-level energy storage system for a PV-driven commercial building in the Mediterranean climate. The proposed system encompasses both hydrogen metal hydride and battery storage units. Aimed at off-grid electrification, the optimal component sizing of the hybrid system is identified by establishing a statistical optimization framework using the response surface methodology. Dynamic simulations of the hybrid system are performed through a TRNSYS model coupled with a numerical code that simulates the metal hydride system. Regarding optimal net-zero solutions, it is shown that the share of the direct PV electricity supply to end-use fluctuates within a limited range for all scenarios, namely between 57.7 and 60.5 %, while the share of each storage system varies distinctively in each solution. The results indicate a striking difference between scenarios in terms of economic aspects; differences of $ 19,791 and $ 32,621 are observed between the minimum and maximum values of the initial investment and life cycle cost, respectively. The levelized cost of electricity varies between 0.354 and 0.403 $/kWh, in which the case having the lowest payback period (10.8 years) demonstrates the lowest levelized cost of electricity too. Furthermore, an inverse relationship between the levelized cost of hydrogen and production rate is observed; the lowest levelized cost and the highest annual production are achieved in the scenario with the lowest BESS capacity and the highest electrolyzer power and hydrogen storage volume, which are equal to 5.77 $/kg and 304.7 kg H2/yr, respectively.

Design and modeling of PV-integrated Double Skin Facades and application to retrofit buildings

Double Skin Façade (DSF) system comprises two glazing layers with a ventilated cavity. Integrating photovoltaic (PV) modules within the outer layer of DSFs offers an efficient method for electricity generation. Current tools for modeling and analyzing DSF systems are complex and resource-intensive, lacking the capability to evaluate the performance of innovative PV-DSF systems during the early design stage. This study develops a mathematical model to evaluate the electrical and thermal performance of PV-DSF systems, considering architectural design elements such as PV color and relative orientation. Based on an energy balance approach, the model is particularly suited for designing PV-DSF systems in heritage buildings, which often have color and relative orientation constraints. The model is applied to assess the performance of PV-DSF systems with conventional clear glass PV and colored front glass PV modules under the climatic conditions of Montreal, Canada. Results indicated that conventional clear glass PV module exhibit higher PV cell temperature than colored PV modules due to greater transmissivity, with peak temperature differences at noon of 5.5 °C, 6.2 °C, and 6.5 °C for orange, blue, and gray PV modules, respectively. On the contrary, the influence of PV's color front glass on room air temperature is non-significant. Furthermore, the optimal orientation for maximum energy yield is not always south-facing; it depends on the hourly distribution of the beam, diffuse solar irradiation, and ambient air temperature. For Montreal, west-facing DSFs produce more electrical and thermal energy on a summer design day because the hourly distribution of beam radiation is skewed towards afternoon hours.

Integrated Supervisory Control and Data Acquisition System for Optimized Energy Management: Leveraging Photovoltaic and Phase Change Material Thermal Storage

ABSTRACTReliable energy sources are crucial for both economic growth and quality of life. In developing countries, where expensive fuels are often the primary energy source, governments are exploring innovative solutions like small‐scale, IoT‐based projects to achieve energy independence in buildings. This research investigates the integration of renewable energy technologies, statistical modeling, cloud computing, and IoT to develop a self‐managing energy system for buildings. The system prioritizes renewable sources, specifically monocrystalline solar cells with 20% efficiency for photovoltaic (PV) energy and flat plate collectors with 90% efficiency and minimal energy loss for thermal energy. Thermal energy is stored in paraffin wax, chosen for its high storage efficiency and thermal properties. The system also utilizes an absorption chiller with a high coefficient of performance (COP) to provide cooling using solar thermal energy. The building's energy loads are categorized as A, B, C, and D, each utilizing both PV and thermal energy. A SCADA system oversees the operation, monitoring the on–off status of these loads. The system is designed for continuous operation, with simulations conducted using Anaconda Jupyter Notebook and Python. This model aims to offer a sustainable and efficient energy solution for buildings, meeting energy demands while optimizing energy use.