Energy Consumption Simulation Research Articles

Evaluating the Performance of Fixed 3D-Printed and Dynamic Fabric Modules in a Second-Skin Façade System: A Residential Case Study in Southern Italy at Building and District Scales

The building sector accounts for 30% of worldwide final energy usage and 26% of global energy-linked emissions. In construction, innovative materials and systems can offer flexible, lightweight, energy-efficient solutions to achieve more efficient buildings. This study addresses the energy analysis and environmental impacts of retrofitting residential buildings in Monterusciello, Italy, using an innovative second-skin façade system design that incorporates 3D-printed and fabric modules. The purpose is to enhance energy efficiency and reduce the environmental impact of residential buildings originally constructed with prefabricated elements that have degraded over time. This research employed TRNSYS modelling to simulate energy consumption and environmental impacts at the single-building and whole-district levels, analysing the system’s effectiveness in reducing cooling and heating demands and using different materials for optimal performance. The results show that retrofitting with the second-skin façade system significantly reduces cooling energy demand by 30.2% and thermal energy demand by 3.84%, reaching a primary energy saving of 16.4% and 285 tons of CO2 emissions reduction for the whole district. The results highlight the potential of second-skin façade systems in improving energy efficiency and environmental sustainability, suggesting future research directions in material innovation and adaptive system development for district-wide applications.

COMPARATIVE STUDY OF SUPERMARKET BUILDING PERFORMANCE UNDER CURRENT AND FUTURE WEATHER CONDITIONS IN ABUJA MUNICIPAL COUNCIL (AMAC), ABUJA-NIGERIA

This study investigates the energy performance and carbon emissions of LIDL supermarket buildings in Abuja, Nigeria, under current and future climate conditions. Using a multi-methodological approach, the research evaluates three construction models—Model P1 (steel columns with cladding panels), Model P2 (Poroton blocks), and Model P3 (precast concrete columns with glulam beams)—to understand the impacts of construction techniques and materials on building energy efficiency and sustainability. The study employs Thermal Analysis Software (TAS) v9.5.0 to simulate energy consumption and emissions under different scenarios, utilizing dynamic weather data from the Chartered Institution of Building Services Engineers (CIBSE) for both present and future climate projections (2050s and 2080s). The methodology integrates critical building elements, including floor area, thermal properties, and heating, cooling, and lighting systems, and incorporates site-specific data from Jabi, Abuja, to analyze regional climate effects. Key simulation assumptions include construction details, U-values, and infiltration rates, while databases from ASHRAE are used to model thermal properties and heat transfer. Results highlight the energy demand changes and carbon emissions associated with heating and cooling across seasonal extremes. This research provides actionable insights into optimizing supermarket energy performance and sustainability in response to climate change, offering valuable guidance for building designs in urbanizing and climate-vulnerable regions like Nigeria.

VECTOR-LOGIC FAULT SIMULATION

Context. The technological trends of Design&Test computing for the IT industry and academic science are determined by the following directions: in-memory computing, immersive computing, AI computing, focused on energy saving and reduction of computing time when providing services. A mechanism for simulating faults as addresses on smart data structures is proposed, which eliminates the algorithm for simulating input test sets to obtain a test map for logic functionality. The proposed mechanism is focused on the service of SoC IP-cores under the control of the IEEE 1500 standard, which can be perceived positively by engineers in the EDA market. Objective. The purpose of the research is time- and energy-saving mechanisms for simulating malfunctions, such as addresses, by using read-write transactions of in-memory computing to build a test map of any functionality on smart data structures. Method. Smart data structures are represented by a logical vector and its derivatives in the form of truth tables and matrices. The test map is a matrix whose coordinates are determined by the combinations of all logical faults that are tested on the binary sets of the comprehensive test. The construction of the test map is focused on the architecture of in-memory computing based on read-write transactions, which makes the simulation mechanism economical in terms of simulation time and energy consumption due to the absence of a central processor. A logical vector as a single component of input data does not require synthesis into a technologically permitted structure of elements. Synthesis of smart data structures based on four matrix operations creates a fault test map like addresses for any logic. Results. Deductive matrix vectors are effectively used to model faults as addresses in digital structures of any configuration, including convergent branches and feedback loops. The resulting test map is used to find the minimum fault-checking test of the input variables. The proposed fault simulation mechanism technologically easily fits into the architecture of in-memory computing and uses only read-write transactions. The vector logic engine can also be used to test graph structures that are described by a truth table or a logical vector. The truth table addresses used for fault simulation are effectively used for processorless processing of large data in the in-memory computing architecture. Conclusions. Scientific novelty – a vector-logic in-memory computing mechanism for building a test map is proposed, characterized by the construction of intelligent data structures that reset the fault modeling algorithm. The proposed mechanism has no analogues in the design & test industry in terms of simplicity and predictability of data structure sizes and the absence of a test set modeling algorithm. The practical significance is determined by the application of the mechanism for testing logical functionalities of any complexity to solve verification tasks. Prospects of the research – increasing the object of diagnosis to the scheme, i.e. building a test map of the scheme logical structure.

A Study on the Exploration of the Development Process of Regenerative Applications of Energy Technologies in Industrial Warehouse Buildings: Bibliometric Research from 2004 to 2024

Due to the high energy consumption characteristics of industrial warehouse buildings, the demand for energy regeneration technology is increasingly urgent. In recent years, with the rapid development of building energy technology, warehouse building energy regeneration technology has made remarkable progress in energy conservation and sustainable development. A deep understanding of the previous research progress and trends can provide the scientific basis for guiding subsequent in-depth research. Through the bibliometric analysis of 145 journal articles collected from the Web of Science (WoS) database between 2004 and 2024, this research has studied the research trends and progress on the application of energy regeneration in industrial warehouse buildings. This study first revealed the overall development trend of energy regeneration technology in warehouse buildings through quantitative analysis, indicating that related research is growing rapidly. Core scholars in the field such as Lund H. and Mathiesen B.V., as well as major journals such as Energy and Sustainability, have been identified through the analysis of the literature. Five core research themes, including energy efficiency improvement and regeneration technology, renewable energy system design, life cycle sustainable technology, renewable energy utility assessment, and policy support and energy consumption simulation, were identified through cluster analysis. Through evolutionary analysis, this study demonstrates the development process of energy regeneration in warehouse buildings and the critical role played by advances in new energy technologies in the field of warehouse construction. On this basis, this study proposes current key research directions, including energy life cycle assessment, energy regeneration environment optimization, and energy system management. The research on the energy regeneration of warehouse buildings has gradually become an important cross-subject of architecture and energy technology, providing technical support for the transformation of low-carbon storage buildings. The analysis of the current research status, evolutionary logic, and research trends can provide scientific references for further in-depth research and technological applications in this field.

The application of predictive stochastic model based on Monte Carlo method in building energy saving renovation

Abstract: This research has established an energy consumption prediction model based on the Monte Carlo method to resolve the energy-saving transformation problem. First, simplify the building to construct the proposed model. Second, through the principle of building energy balance and Monte Carlo method, the cooling and heat demand model of regional buildings and the energy consumption prediction model of regional buildings are built. Finally, the energy consumption simulation and energy consumption prediction of the regional building complex after energy-saving renovation are carried out. The experiment shows that the building energy consumption in July and August was relatively high, reaching 2.36E+14 and 2.4E+14, respectively. The energy consumption in April and November was relatively low, reaching 1.2E+14 and 1.4E+14, respectively. The highest prediction error was in November, reaching 12%. The lowest prediction error was in January and February, only about 2%. The error of monthly energy consumption predicted by Monte Carlo method is less than 12%, the Root-mean-square deviation is 5%, and the error between predicted and actual annual total energy consumption is only about 2%. By comparing the predicted energy consumption after energy-saving renovation with before, the energy-saving rate reached about 20%. The research results indicate that the proposed Monte Carlo based predictive stochastic model exhibits good predictive performance in building energy-saving renovation, providing theoretical guidance and reference for feasibility studies, planning, prediction, decision-making, and optimization of building energy-saving renovation.

A quantitative comparison of different methods for air conditioning energy consumption prediction in residential buildings

Accurate evaluation of energy consumption of air conditioning (AC) is crucial to energy efficiency in residential buildings, while few studies evaluate quantitatively the differences of the currently used methods. This study aimed to assess two common methods for AC energy consumption evaluation, namely, top-down total energy disaggregation and bottom-up energy simulation, through comparing to field measurement. A longitudinal investigation was conducted in residences in Chongqing, a typical city in the Hot Summer and Cold Winter(HSCW) zone. The yearly daily electricity consumption of 18 residences were collected and wireless sensors and smart sockets were used for onsite measurement. The AC energy consumption was obtained by splitting the total electricity consumption and measurements. Moreover, three typical reference buildings were built for predicting the annual AC energy consumption. Results showed that the simulated AC energy consumption was about 2.76 times of the measured value; while it was about 2.89 times for the top-down disaggregation method. Some key factors influencing AC energy consumption (e.g., indoor temperature distribution, opening duration, AC usage frequency) were identified for different methods. The work quantified the limitations of the top-down and bottom-up methods, contributing to the improvement of AC energy consumption evaluation methods and management of heating and cooling energy in residential buildings.

Energy management strategy for extended range electric logistics vehicle based on type-2 fuzzy control

To overcome the limitations of fuzzy energy management strategy (EMS) in describing uncertainty, this paper proposes an EMS based on type-2 fuzzy (T2F), which optimizes energy consumption for extended range electric logistics vehicle (ERELV). Firstly, establish an energy consumption simulation model for ERELV. Then, an EMS based on T2F controller is designed. The strategy takes the state of charge (SOC) and the demand power as the input, and the range extender power as the output. This paper analyses the influence of T2F control strategy on the energy consumption of the ERELV, and uses the model-based design method to verify the EMS in the Hardware-in-the-loop (HIL) simulation test. The test results show that compared with the traditional fuzzy control strategy, the T2F strategy can reduce the engine’s energy loss by 12.58%. Finally, actual fuel consumption tests were conducted on the established ERELV model. By comparing the results of C-WTVC and CHTC-HT operating conditions, the model was verified to meet the research requirements of EMSs in this paper and has practical significance.

Investigation on the overall performance of hydrogel-based thermochromic windows with various structures

Thermochromic (TC) windows have attracted extensive attention due to their potential for improving building performance through the variation of optical properties in response to temperature. However, past studies on TC windows at the building scale primarily focused on optimizing and evaluating the properties of TC materials, with little attention paid to the varying window structures frequently encountered in engineering applications. In this study, the building performance of hydrogel-based TC windows was investigated from the structural perspective. A comprehensive simulation framework was developed, integrating overall performance simulations of energy consumption and indoor comfort. Using a self-fabricated hydrogel TC glass and an office building as the case study, the impact of the optical properties of the substrate glass on single, double, vacuum, and ventilation TC windows was analyzed. The results indicated that the optimal extinction coefficients for the studied windows range from 55 to 105 m−1 for visible irradiation and from 155 to 255 m−1 for near-infrared irradiation. Subsequently, the overall performance improvements of these types of TC windows relative to corresponding static versions were calculated. It was found that the impacts of TC glass on these four windows varied significantly. The electricity usage was reduced by 33 ∼ 53 %, and the thermal comfort and visual comfort were enhanced by –22 ∼ 20 % and 72 ∼ 100 %, respectively. This study reveals in detail how the TC window structure affects various aspects of building performance, aiming to inspire and guide the consideration of window structure in the practical applications of TC glass.

Characterizing Rock-Breaking Performance of PDC Cutters via Stability Metrics and Energy consumption in FDEM Simulations

As oil production increasingly transitions from shallow to deep formation, the need for efficient PDC cutters to drill through deep hard rock becomes paramount. Currently, there is a lack of effective methods for optimizing cutter shapes and their cutting parameters. This study addresses this gap by developing a rock-breaking mechanism model for PDC cutters and proposing a Stability Index (SI) based on cutting force variations during the cutting process. Using the FDEM method, we simulated the rock-breaking processes of planar, stinger, and machete cutters under various cutting depths and angles. SI and Mechanical Specific Energy (MSE) were employed as evaluation metrics to analyze the rock-breaking characteristics and determine the optimal cutting parameters for each cutter type. The results indicate that at shallow cutting depths, cutting force changes are minimal, predominantly causing plastic damage to the rock, resulting in lower stress and reduced wear on the PDC cutters. Conversely, at greater cutting depths, significant fluctuations in cutting force occur, leading to brittle failure and the generation of large cuttings. This sudden increase in cutting force can accelerate rock breaking but also increases the risk of cutter wear. Our findings suggest that the planar cutter offers stable performance with high cutting force requirements, optimal at a cutting depth of 1.5 mm and an angle of less than 20°. The stinger cutter, requiring lower cutting forces, performs best at a cutting depth of 2 mm and an angle of 20°. The machete cutter exhibits characteristics similar to the stinger cutter at shallow depths and the planar cutter at deeper depths, making it suitable for drilling at a depth of 2 mm and an angle of less than 10°. By balancing SI and MSE, this study provides a comprehensive approach to optimizing PDC cutter performance, enhancing drilling efficiency while minimizing cutter wear.

AERODYNAMIC AND ROLLING RESISTANCES OF HEAVY DUTY VEHICLE. SIMULATION OF ENERGY CONSUMPTION

The main objective of the work was to develop a comprehensive model of energy consumption simulation of heavy duty vehicles using the VECTO simulation tool. The research issue was the impact of aerodynamic drag and rolling resistance on fuel consumption and emissions under various driving conditions described in four driving cycles: Urban Delivery, Regional Delivery, Urban, and Suburban. Each cycle differed in driving time, distance and average speed to represent different operational scenarios. The methodology involved defining vehicle parameters such as weight, aerodynamic coefficients and tyre rolling resistance. The main findings show that the impact of both aerodynamic drag and rolling resistance on fuel consumption can be efficiently modelled. It has been proven that the proposed modifications to aerodynamic drag and rolling resistance can reduce fuel consumption by more than 8%. The lowest fuel consumption was achieved in the Regional Delivery cycle, while the Urban cycle had the highest fuel consumption due to frequent vehicle stops. The results show that optimization of vehicle design and its performance can significantly improve energy efficiency and reduce emissions. A computational modelling tool such as VECTO can contribute to sustainable transport solutions and improve the efficiency of heavy duty vehicle.

Simulation of Energy Consumption for Different Types of Walls and Colour for A Residential Building, Case Study: Phnom Penh City, Cambodia

The residential building sector in Cambodia is growing rapidly, with the number of flats increasing by more than 34% from 2020 to 2021. This growth is putting a strain on the country's energy resources, as air conditioning (HVAC) systems account for a significant portion of energy consumption in buildings. This study used EnergyPlusTM with OpenStudio SketchUp Plug-In to simulate the annual energy consumption of a flat in Phnom Penh, Cambodia. The calculated annual energy consumption agrees well with actual electricity consumption accumulated from monthly electricity bills, with error of 1.78%. The results showed that the selection of colour paint and additional insulation on the existing wall can reduce annual energy consumption by 3.20% and 19.68%, respectively. These findings suggest that energy efficiency measures can play a significant role in reducing energy consumption in the residential building sector of Cambodia. However, it is important to note that the results may vary depending on the specific building design, occupancy behaviours and climate conditions.

In-Memory modelling and simulations

A mechanism for modeling faults as addresses on smart data structures is proposed, which excludes the algorithm for modeling input test sets to obtain a test map of logical functionality. Smart data structures are represented by a logical vector and its derivatives in the form of truth tables and matrices. The test map is a matrix whose coordinates are defined by the combinations of all logical faults that are tested on the binary sets of the exhaustive test. The construction of the test map is focused on the architecture of in- memory computing based on read-write transactions, which makes the simulation mechanism economical in terms of simulation time and energy consumption due to the absence of a central processor. A logical vector as a single component of input data does not require synthesis into a technologically permitted structure of elements. Synthesis of smart data structures based on four matrix operations creates a fault test map like addresses for any logic. The proposed mechanism is focused on the service of SoC IP-cores under the control of the IEEE 1500 standard. The proposed mechanism has no analogues in the design and test industry in terms of simplicity and predictability of data structure sizes and the absence of a test set modeling algorithm.

Optimization of optical properties of nanocomposite films incorporating CWO and ITO nanoparticles for energy-saving window applications

Cesium tungsten oxide (CWO) and indium tin oxide (ITO) nanoparticles are potential candidates for application in energy-saving windows. However, most optical studies on these nanocomposite films lack systematic evaluation and design methods. In this work, the optical properties of spherical and cylindrical CWO and ITO nanoparticles under different geometric parameters based on the Lorenz–Mie and T-matrix theories are investigated, and spectral responses of CWO-PDMS and ITO-PDMS windows are calculated by solving the radiative transfer equation (RTE) using the Monte Carlo method. By evaluating and optimizing the geometric parameters of the nanocomposite films, energy-saving windows exhibit excellent optical performance, with a visible light transmittance that meets the indoor needs of the human eye (Tlum is about 0.6), and can shield most near-infrared light, especially CWO-PDMS windows (TNIR=0.04). Finally, a building energy consumption simulation analysis based on Energy Plus is conducted in three different cities: Jinan, Hong Kong, and Singapore. The results indicate that by adjusting the geometric parameters of nanoparticles, energy-saving windows can effectively reduce energy consumption in tropical and subtropical regions. This work provides guidance for the subsequent commercialization and experimental analysis of spectral selective composite films.

BIM and orthogonal test methods to optimize the energy consumption of green buildings

The construction industry’s rapid growth significantly impacts energy consumption and environmental health. It is crucial to develop optimization strategies to enhance green building energy efficiency and encompass comprehensive analysis methods. This study aims to introduce and validate a novel framework for optimizing energy efficiency design in green buildings by integrating Building Information Modeling (BIM) technology, Life Cycle Cost (LCC) analysis, and orthogonal testing methods, focusing on enhancing energy efficiency and reducing life cycle costs. The optimization parameters for the building envelope are identified by analyzing energy consumption components and key green building factors. The orthogonal testing method was applied to streamline design options. Building Energy Consumption Simulation (BECS) software and LCC analysis tools were employed to calculate each optimized option’s total annual energy consumption and the current life cycle costs. Using the efficiency coefficient method, each optimization scheme’s energy consumption and economic indicators were thoroughly analyzed. The framework’s validity and applicability were confirmed through an empirical analysis of a campus green building case in Fujian Province, demonstrating that the optimized framework could reduce energy consumption by 4.85 kWh/m2 per year and lower costs by 38.89 Yuan/m2 compared to the reference building. The case study highlights the framework’s significant benefits in enhancing environmental performance and economic gains. The results provide critical parameter selection and offer scientific and technological support for the design of building energy efficiency, promoting optimization techniques and sustainable development within the construction industry.

Nanotechnology for thermal comfort and energy efficiency in educational buildings with a simulation and measurement approach in BSh climate

Educational buildings have a large share and impact on urban development. While research shows a significant portion of non-industrial energy consumption in these buildings, obtaining optimal thermal comfort in educational buildings remains one of the main concerns in achieving the grounds to promote students’ best performance and efficiency. Extensive research has been done in this field, however, this research presents a new approach to the diverse use of nanotechnology techniques which improve its properties and components in the buildings, aiming to reduce energy consumption and increase thermal comfort. In this paper, thermal comfort and energy consumption are evaluated in a 12-class elementary school located in Shiraz City. Aeropan and nano-Phase change materials (nano-PCMs) is used in the window glass and walls of the studied case. This evaluation presents the simulation and experimental analysis of thermal comfort (PMV) and energy consumption of three classroom alignments in the school building including the Linear-shape (LS), the Integrated Linear-shape (ILS), and the U-shaped (US) alignment. The simulation was performed using EnergyPlus 9.6 software, while the experimental data was collected using TESTO 425 device. The result of this research shows that after applying nano-PCM and Aeropan techniques in window glass and walls, the US alignment has the highest reduction in energy consumption (monthly average of 11.80%) compared to LS and ILS alignments. This alignment includes an energy consumption reduction of 12.03% in the coldest, and, 11.66% in the hottest day of the year in addition to increasing the monthly average thermal comfort of school by the use of nanomaterials.

Thermophysical properties and energy-saving efficiency of phase change microcapsule foamed cement composite insulation materials

The addition of phase change materials (PCMs) to building envelopes can improve building thermal stability and reduce energy consumption. In this study, phase change paraffin microcapsules are combined with foamed cement to create composite thermal insulation materials with varying mass ratios of microcapsules. A heat transfer characterization experimental platform was established to investigate the heat transfer laws. The incorporation of phase change microcapsules (MPCMs) into foamed cement resulted in a reduction in thermal conductivity. The thermal conductivity of the test blocks exhibited a linear relationship with the mass ratio of MPCMs, with an average thermal conductivity of 0.053 W/(m-K) observed for 20 % MPCMs. The impact of foamed cement containing MPCMs on building energy consumption was analyzed in five different climate zones in China using EnergyPlus. The results show that energy savings are more significant in cities with higher heating demand. In non-cold regions, energy savings are highest when the phase change temperature is close to the local annual average temperature. The optimal energy saving program is evaluated by energy consumption simulation. The results show that it achieves the highest energy savings in Harbin, which saves a total of 1074,007 kWh. Additionally, it has the highest energy saving rate in Beijing, with a rate of 14.66 %.

Research on the coordinate regulation behavior of window opening and split air conditioners usage during summer in mixed-cooling houses in hot-humid regions

In the hot-humid regions of South China, it is common for residents to utilize a combination of window opening and split air conditioners to cool their houses during summer. However, existing research focuses on investigating either window opening behavior or air conditioner usage behavior respectively, lacking a linkage study between these two approaches. Addressing this research gap, a novel coordinated regulation behavior model was developed by integrating both window opening and air conditioner usage behaviors. Due to different coordinate regulation modes, the tolerance temperature range in summer varies in mixed-cooling houses. Additionally, a degree of coordination is introduced to signify the level of overlap between window opening and air conditioner usage behaviors, indicating the uncertainty involved in choosing between these two actions. Moreover, residents exhibit a dynamic approach to switching between cooling methods, characterized by a transition range of approximately 2 °C rather than relying on a fixed temperature value. Notably, the simulated energy consumption results demonstrate a significant energy consumption disparity of up to 71 % among different behavior patterns. This study contributes to the academic understanding of the complex interactions between window opening and air conditioner usage and lays the foundation for achieving precise energy consumption simulation of mixed-cooling houses.

Energy Efficient Design of Building Based on Building Information Modelling (BIM)

Building energy analysis is rarely carried out due to the complexity of building shape and materials. On the other hand, the urgency of environmentally friendly construction is increasing through the vision of the SDGs and Architecture 2030. The development of BIM technology is expected to provide accurate estimates of building energy consumption for projects undertaken, as well as recommendations for alternative designs and specifications to increase the energy efficiency of a building. The use of BIM technology for energy analysis during building design helps to implement green building sustainable design based on the analysis of BIM energy simulation software. Data of three-dimensional BIM model with the attributes of materials, project schedule and location are used in building energy consumption simulation analysis. Several scenarios of different materials and layout are carried out to determine the most efficient scenario for energy consumption and followed by its cost estimation. The results of this study are expected to be able to provide the energy value that can be saved through predetermined scenarios as well as the value of the costs required to run a more energy-friendly design scenario in a comprehensive manner.

Energy saving and carbon reduction of the application of phase change materials in rammed earth heritage buildings

ABSTRACT The combination of conventional thermal insulation materials and phase change materials (PCMs) was proposed without damaging the appearance of REHBs, the internal insulation measures of four types of expanded polystyrene (EPS) and six kinds of PCM boards combinations were investigated, and 19 retrofit cases were obtained. By conducting detailed simulations of energy consumption and indoor temperature for different cases at different locations, and comprehensively comparing multi-objects (energy-saving, economic and low-carbon), the energy consumption, cost recovery period and carbon reduction of these cases are compared and analyzed. The results show that Case I (only EPS) has the best energy-saving performance, economy and carbon emission reduction, Case III (EPS and PCM) is the second and Case II (only PCM) is the worst. The energy-saving rate of Case I and Case III (16 ℃) differs by 5.65%, while the cost, incremental benefit and payback period differ by 9.34%, 10.2%, and 1.57 years, respectively. Case III is a new and better passive retrofit measure of the REHB. Its energy-saving, cost and carbon reduction are only about 10% lower than that of Case I, but it has better indoor comfort. The outcomes can provide a reference for the innovative energy-saving retrofit cases for REHBs.

Fabrication of passive cooling fabric as thermal management curtain for building energy-saving

In the past years, a great deal of attention has been paid to passive cooling envelope materials or smart windows to cope with the increase in building energy consumption due to global warming. However, combining curtains with passive cooling could enable on-demand thermal management based on its dynamically adjustable characteristics. Herein, a superhydrophobic passive cooling cotton fabric with low thermal conductivity (0.0342 W/mK), high solar reflectivity (0.9280) and high infrared emissivity (0.9698) was obtained by wrapping the cotton fabric with a porous SiO2/poly(vinylidene fluoride-hexafluoropropylene) composite coating via solvent exchange phase separation and sanding. The superhydrophobic passive cooling fabrics realized an average of 10.3 °C cooling during the daytime and showed impressive passive cooling performance relative to the pristine cotton. Notably, the superhydrophobic passive cooling fabric demonstrated superior daytime cooling and nighttime insulation performance during outdoor testing and energy consumption simulations compared to commercial curtains. Therefore, superhydrophobic passive cooling cotton fabrics as curtains allow for reducing the energy consumption in building thermal management and broadening the practical application of radiative cooling materials.