Building Energy Consumption Research Articles

Quantum Genetic Algorithm-Driven Optimization of Triple-Glazed Window Thickness for Enhanced Light Reduction

Abstract. Glass, a common construction material, generally lacks significant thermal properties. As technology rapidly advances, the demand for glass materials with superior heat preservation and thermal insulation capabilities increases, driven by the need to reduce building energy consumption. Multi-objective optimization problems, particularly in complex multilayered systems, require advanced numerical optimization algorithms. The quantum-inspired genetic algorithm (QIGA) offers advantages such as fast solving speed and high precision, utilizing quantum coding, variation, rotation gates, and crossing techniques. This study focuses on designing the optimal thickness of triple-layer glass to minimize sunlight penetration through windows, using QIGA to achieve this goal. The results demonstrate that triple glazing effectively reduces solar radiation entering a room, though different layer combinations lead to significant variations in total energy reduction. The study also emphasizes the importance of concurrent research in glass layer splicing technology, coating film techniques, and new glass materials to enhance overall performance. These findings contribute to the development of energy-efficient building materials that meet modern standards for thermal insulation and light control.

Building Thermal Insulation Performance and economic benefits

Three different insulating scenarios were investigated using Energy-plus software, to study the effect of using expanded polystyrene boards on building energy consumption at the Libyan Center for Solar Energy Research and Studies. The three insulation scenarios with different polystyrene insulation thicknesses and densities were investigated. Polystyrene total cost, Payback period, total and net money saving using insulation, as well as the percentage gain were calculated for each case in the three investigated scenarios for 50 years. The most money saving scenarios after 50 years is by insulating the building roof and external walls with an average insulation thickness of 7 cm, reaching about 78000 L.D and a tariff of 0.9261 L.D /kWh. While the least money saving is the roof scenario with an insulation thickness of 2.5 cm, reaching more than 29000 L.D and the same tariff. The highest percentage gain values are 76 %, 103 % and1090 % at the roof scenario, 2.5 cm insulation thickness and energy tariffs of 0.15 L.D /kWh, 0.1732 L.D/kWh and 0.9261 L.D/kWh, respectively. While the lowest percentage gain values are about 17.5 %, 35.7 % and 725 % at the wall scenario 10 cm insulation thickness and energy tariffs of 0.15 L.D/kWh, 0.1732 L.D/kWh and 0.9261 L.D/kWh, respectively. the payback period of total insulation cost is significantly dependent on insulation thickness and energy tariff. These results show that low energy tariff (current energy tariff) values economically are not cost effective regarding the payback period. Consequently, prices do not motivate residents to save energy with the use of thermal insulation unless actual energy prices are considered.

Occupancy-based Energy Management System in Campus Building: A Case Study in Electrical Engineering Department Building, ITN Malang

Building energy management systems provide an effective method for energy saving. An occupancy-based energy management system considers the occupants' behavior that affects energy consumption. This paper presents the investigation of different scenarios based on the occupancy to control the energy consumption in the Electrical Engineering Department Building, ITN Malang. The results show that switching off the appliances when the occupants go home in the afternoon reduces the monthly energy consumption by 33.95%. The result indicates that the occupants' awareness regarding energy saving has recently been low. Thus, the occupancy sensor and automatic time scheduling for the appliance control are suggested to be installed.

Interactive Kinetic Facade with Design for Disassembly (DfD) strategy: improving energy efficiency and circularity of building materials in tropical climate

ABSTRACT Building is a significant contributor to energy and material consumption. In tropical countries, the primary energy consumer in buildings is Air Conditioning (AC), driven by the cooling load from solar radiation. Interactive Kinetic Facade (IKF) can reduce building energy consumption by mitigating solar radiation. Furthermore, IKF has drawbacks in maintenance and disassembly. Therefore, this study proposed a Design for Disassembly (DfD) strategy that allows building components to easily disassemble for reuse. The objective of this study was to investigate the application of IKF with DfD strategy in the Engineering Center (EC) building facade. This study proposed a combination of on-site measurements, simulations, and calculations to comprehend the impact of IKF with DfD strategy implementation on energy consumption and material reusability. This research found that implementing IKF with the DfD strategy can significantly reduce solar radiation through building facade. The reduction can be indicated by a decrease of several parameters, Overall Thermal Transfer Value (OTTV) by 59%, annual operative temperature by 2.53°C and Energy Use Intensity (EUI) by 47.43%. In addition, the facade disassembly process is simpler with only 1 tool and 4 stages. This study could serve as a reference to improve energy efficiency and material reusability in building sector.

Multi-Timescale Energy Consumption Management in Smart Buildings Using Hybrid Deep Artificial Neural Networks

Demand side management is a critical issue in the energy sector. Recent events such as the global energy crisis, costs, the necessity to reduce greenhouse emissions, and extreme weather conditions have increased the need for energy efficiency. Thus, accurately predicting energy consumption is one of the key steps in addressing inefficiency in energy consumption and its optimization. In this regard, accurate predictions on a daily, hourly, and minute-by-minute basis would not only minimize wastage but would also help to save costs. In this article, we propose intelligent models using ensembles of convolutional neural network (CNN), long-short-term memory (LSTM), bi-directional LSTM and gated recurrent units (GRUs) neural network models for daily, hourly, and minute-by-minute predictions of energy consumptions in smart buildings. The proposed models outperform state-of-the-art deep neural network models for predicting minute-by-minute energy consumption, with a mean square error of 0.109. The evaluated hybrid models also capture more latent trends in the data than traditional single models. The results highlight the potential of using hybrid deep learning models for improved energy efficiency management in smart buildings.

Historical Evolution and Current Developments in Building Thermal Insulation Materials—A Review

The European Climate Law mandates a 55% reduction in CO2 emissions by 2030, intending to achieve climate neutrality by 2050. To meet these targets, there is a strong focus on reducing energy consumption in buildings, particularly for heating and cooling, which are the primary drivers of energy use and greenhouse gas emissions. As a result, the demand for energy-efficient and sustainable buildings is increasing, and thermal insulation plays a crucial role in minimizing energy consumption for both winter heating and summer cooling. This review explores the historical development of thermal insulation materials, beginning with natural options such as straw, wool, and clay, progressing to materials like cork, asbestos, and mineral wool, and culminating in synthetic insulators such as fiberglass and polystyrene. The review also examines innovative materials like polyurethane foam, vacuum insulation panels, and cement foams enhanced with phase change materials. Additionally, it highlights the renewed interest in environmentally friendly materials like cellulose, hemp, and sheep wool. The current challenges in developing sustainable, high-performance building solutions are discussed, including the implementation of the 6R principles for insulating materials. Finally, the review not only traces the historical evolution of insulation materials but also provides various classifications and summarizes emerging aspects in the field.

Research on the design and thermal performance of vacuum insulation panel composite insulation materials

This study introduces a novel design methodology for composite insulation material aimed at reducing the operational energy consumption of buildings. Vacuum Insulation Panels (VIPs) are recognized for their excellent insulating properties due to their vacuum-sealed nature that minimizes thermal transmittance. However, VIPs are susceptible to damage from temperature stress and abrasion, which can compromise vacuum integrity and degrade performance over time. To mitigate this, a protective layer of rock wool board is adhered to the exterior of the VIP to create a composite insulation material. The thermal conductivity characteristics of the composite insulation materials are experimentally measured and then corroborated with simulations using ANSYS software to affirm the precision of finite element analysis methods. A composite Insulation wall model is constructed using ANSYS to analyze the impact of varying the thickness of the composite insulation materials and the pressure within the VIP on thermal performance. The findings demonstrate that the thermal transmittance coefficient of the composite insulated wall diminishes with increased insulation material thickness and rises with increased pressure within the VIP. Additionally, rock wool boards significantly enhance the durability of the composite insulation material.

Hygrothermal behavior of hemp concrete and conventional concrete: a comparative analysis

This study presents an in-depth comparative analysis of the hygrothermal behavior of hemp concrete and conventional concrete, with a focus on their energy-saving potential and moisture regulation capabilities. Through detailed numerical simulations, the research examines how these two materials perform under identical climatic conditions, highlighting key differences in their ability to retain heat and manage moisture. The results reveal that hemp concrete provides up to 80% less thermal energy dissipation through building walls compared to conventional concrete, making it a far superior material for thermal insulation. In addition, hemp concrete exhibits improved moisture regulation, which not only enhances indoor comfort but also promotes healthier living environments by preventing excessive humidity. The study emphasizes hemp concrete's potential in significantly reducing energy consumption in buildings, thus promoting its application in sustainable construction. While hemp concrete lacks the mechanical strength required for load-bearing applications, its numerous environmental benefits, cost-effectiveness, and suitability for non-structural components make it an attractive choice for eco-friendly construction projects. This research also paves the way for future exploration of innovative uses for hemp-based materials in green building practices.

Research on Temporal–Spatial Partition Control Strategies for Luminous and Thermal Environment in High Space of Gymnasiums

The lighting design of large-space buildings in gymnasiums can impact the indoor luminous and thermal environment, resulting in an uneven light and thermal distribution. This paper investigates the luminous and thermal environment control strategies for high spaces in gymnasiums, by simulating the luminous and thermal environment under different lighting forms and establishing a comprehensive evaluation model. The results show that the weights of the indoor luminous environment, thermal environment, and comprehensive energy consumption change with season and time under different lighting forms, which provides a basis for developing a temporal–spatial partition control strategy. The temporal–spatial partition control strategy is proposed for summer and winter, including the shading angle control under the lighting forms of south-facing side windows, west-facing side windows, and top skylights. Under summer conditions, the south-facing side windows have no shading from 8:00 to 10:00 and 14:00 to 16:00, and the shading angle is 0° from 10:00 to 14:00; the west-facing side windows have no shading from 8:00 to 14:00, the shading angle is 0° from 14:00 to 15:00, and the shading angle is 15° from 15:00 to 16:00; and the top skylight has a shade angle of 15° from 8:00 to 9:00, 30° from 9:00 to 11:00, 45° from 11:00 to 13:00, and no shade from 13:00 to 16:00. Under winter conditions, the south-facing side windows have no shading all day; the west-facing side windows have no shading from 8:00 to 14:00, and the shading angle is 30° from 14:00 to 16:00; and the top skylight has no shading from 8:00 to 13:00, a shading angle of 45° from 13:00 to 15:00, and a shading angle of 75° from 15:00 to 16:00. This paper provides a set of scientific and reasonable luminous and thermal environment regulation strategies for large-space buildings, which can help optimize the building energy consumption and improve the indoor environment quality.

Thermal-Hydraulic Characteristics of an Earth Air Heat Exchanger: An experimental analysis

The pipe layout design has a great effect on the thermal-hydraulic characteristics of earth air heat exchanger (EAHE) systems. So, in the current study proposed four new buried pipe design configurations; low to high to low, high to low to high, spiral, and circular, in addition to the straight or uniform for comparison. These five configurations are tested and analyzed experimentally depending on the thermo-hydraulic performance for summer cooling requirements with variation of Re in the range of 18041 – 40843. The results show that changing the uniform design of the EAHE with fixed pipe length enhances both the heat transfer process and pressure loss values. At the same operating conditions, the circular design has the best performance compared to the other ones. For all pipe shapes, the cooling effect increases with the increase of air Re. The thermal- hydraulic performance of the circular design pipe is higher than that of the other pipe designs. The highest coefficient of performance (COP) average values that can be obtained at Re = 18041 is 3.05 for circular shape and enhances by 48.08 % compared to uniform shape. The effectiveness of EAHE with circular shape is improved by about 3.52 % compared to uniform shape at Re = 18041. Spiral design is optimum design based on the Nu value which reaches about 48 with enhancement 12.56% and 0.34 % compared to uniform and circular shapes respectively, at Re = 40843. The hydrothermal performance factor is highest in the case of circular shape with value about 21.9 at Re = 21257. By increasing Re, the drawbacks of the increasing in the total entropy generation are reflected negatively on the exergy efficiency. The specific cost of the circular shape at Re = 40843 is the optimum value by about 0.7 $/W. Spiral and circular shapes have a decrease of CO2 emissions less than uniform shape by percentage varied from 2.93 % to 13.84% for decrease in the Re from 21257 to 40843. It is concluded that using EAHE with four new shapes is highly efficient in increasing cooling capacity and energy consumption in buildings.

Urban heat islands’ effects on the thermo-energy performance of buildings according to their socio-economic factors

Urban areas experience the urban heat island (UHI) effect, which affects the thermal comfort and energy consumption of buildings. These consequences could vary depending on the socio-economic status of the neighbourhoods. Few studies have investigated how UHI affects socio-economically contrasting districts in thermal comfort and energy performance. Therefore, the primary goal of this research is to evaluate and compare the energy efficiency and thermal comfort conditions of residential buildings in the same city (Temuco, Chile) but located in socio-economically contrasting neighbourhoods. Urban weather files were first modelled in four urban zones using UWG software. Also, EnergyPlus building simulations were conducted to evaluate discomfort hours in adaptive comfort models and energy performance. The results showed annual average UHI intensities between 1.5 and 2.5 K. Urban–rural cooling energy load differences ranged between 12.47% and 38.92%, while heating energy load differences ranged between -20.47% and -81.95%. These distinctions depended on the urban zone, residence model analysed, or energy building standard applied. Similarly, urban-rural differences in thermal comfort times varied from 0.5% to 100%. Results illustrate that the risk of overheating could increase in socio-economically vulnerable areas. This issue could worsen if urban segregation continues to generate poor urban design in low-income districts.

Natural fibers as promising core materials of vacuum insulation panels

To reduce energy consumption in buildings, this paper investigates the feasibility of using natural fibers as cost-effective, environmentally sustainable core materials for vacuum insulation panels (VIPs). First, a comprehensive experimental study was conducted for 10 potential natural fiber candidates. The thermal conductivities of the 10 natural fiber mats at various vacuum pressures were measured; their compression and morphology properties were quantified. In addition, an analytical model was used to explore the major factors that influence the thermal conductivity of natural fibers as a function of internal air pressure. Results show that recycled cotton, kapok, and bamboo fibers are ideal candidates for VIP core materials; at <0.05 Pa, their thermal conductivities varied between 2 and 4 mW/(m⋅K). Furthermore, for some fibers, thermal conductivity was inversely proportional to fiber density. For the selection of fiber materials for VIP cores, the ideal fiber candidate has a small fiber diameter and a low fiber mat density. Based on thermal measurements, even though the internal air pressure of 5 Pa was enough to attain the minimum thermal conductivity, obtaining internal air pressure below 5 Pa is recommended for prolonged service life, considering small leaks of VIP package barrier films and potential off-gassing from fibers. The simulation results predicting the effective thermal conductivities matched the experimental results well. These findings indicate that natural fiber–based VIPs have the potential to be a sustainable, inexpensive alternative to the current technologies in building insulation materials.

A novel blockchain-based system for improving information integrity in building projects from the perspective of building energy performance

Global population growth has long been intertwined with environmental concerns and sustainable development. The building sector, a significant energy consumer worldwide, contributes substantially to total energy consumption and greenhouse gas emissions. With the projected global population projected to reach 9.7 billion by 2050, building energy consumption is expected to rise continuously, emphasizing the need to optimize energy performance for environmental sustainability. Despite efforts by many countries to formulate energy conservation objectives and strategies, empirical evidence reveals a substantial disparity between designed and actual building energy consumption, known as the building energy performance gap (BEPG). This gap poses a significant challenge to energy conservation efforts, and the lack of information integrity is a significant contributor to this gap. To address the challenge of inadequate information integrity in building energy projects, this research proposes an innovative solution based on blockchain technology. By utilizing blockchain's decentralized, transparent, and tamper-resistant nature, the proposed model aims to enhance information transmission mechanisms among stakeholders. Ten key energy-related stakeholders and various information flows within building projects are identified. Based on this, an exploratory architectural information management model incorporating blockchain technology is developed. The model features functionalities such as data recording, retrieval, transmission, and incentive mechanisms to ensure data immutability and reliable access security. Through a case study, the model's performance is evaluated in terms of storage cost, latency, and privacy, demonstrating significant time savings in uploading and transferring files. The proposed blockchain-based model offers a feasible solution to the challenges of inadequate information integrity in building energy projects, promoting collaboration and accurate information transmission. This model contributes to improving project outcomes and advancing sustainable development in the construction industry.

Redefining realistic and stochastic occupancy schedules and patterns for residential buildings in Jordan

Occupant behavior significantly influences building energy consumption, underscoring the importance of understanding the interplay between energy usage and occupant behavior. This integration is vital for evaluating how occupants and their interactions impact building energy consumption patterns. Despite widespread recognition of the importance of behavior-centric approaches in achieving sustainable architecture, there remains a gap in understanding human behavior, particularly in performance-based design. This study presents realistic and stochastic occupancy schedules for residential buildings in Jordan. This was achieved using a mixed-method approach involving a survey, data classification, clustering processes, and a co-simulation approach combining Rhino Grasshopper and Python. The results contributed to refining the general characteristics of each cluster within different age groups, encompassing various patterns of interaction, tolerance levels or levels of sensing, energy conservation consciousness, and occupancy patterns. A significant correlation was also observed between age groups, occupancy schedules, and energy consumption behaviors. The simulation also evaluated the effects of stochastic behavior patterns on the prediction of the energy performance of residential buildings. The results confirm the significant variation in energy use intensity levels between realistic occupancy schedules and fixed schedules for residential buildings. The results also prove that using realistic occupancy schedules for each age group significantly affects energy consumption behavior through occupant-based behaviors. This confirms the pivotal role of dynamic schedules and occupant behaviors in understanding and shaping energy consumption patterns and realistically determining the efficiency of building systems.

Thermal performance of a double-layer pipe-embedded phase change wall system in wood structures coupled with solar energy

In this study, we propose a dual-layer, pipe-embedded phase change wall system for wooden structures that integrates sky radiation cooling and solar heat collection for cross-seasonal operation. This system harnesses renewable energy and reduces the operational energy consumption of buildings. The primary focus of this study is the performance improving of the system during winter conditions. In winter, the system captures solar energy for daytime indoor heating and load reduction and stores excess heat in phase-change material (PCM) embedded within the wooden wallboard. The stored heat is then released at night to further reduce building loads. To assess the thermal performance of the proposed wall system under winter conditions, experiments were conducted across four different scenarios and a reference system was established for comparative analysis. The results indicate that the proposed wall system significantly improves the indoor thermal environment. Specifically, this integration increased the average indoor air temperature by 6.0 °C compared to the reference system and substantially increased the temperature of the wallboard. The inclusion of PCM notably enhanced the thermal performance by reducing nighttime heat loss. Consequently, the average indoor temperature in systems equipped with PCM-enhanced wallboards was 3.0 °C higher than that in the reference system.

Thermal and mechanical analysis of thermal break structure in balcony with basalt fiber reinforced polymer

Thermal break structure is an effective design to reduce building energy consumption in balcony. The traditional stainless-steel bars or other FRP components reinforced thermal break structures can't enable both mechanical performance and thermal insulation concurrently because these materials are difficult to have low thermal conductivity and high mechanical properties at the same time. This paper proposes to use basalt fiber reinforced polymer (BFRP) to construct the thermal break structure due to the high load-bearing capacity and thermal insultation of BFRP. The thermal performance of the structure is systematically verified through three-dimensional simulation. Influence of thermal break widths, loading point positions, shear reinforcement forms and reinforcement types on the mechanical properties of the structure is investigated. The results show that BFRP can significantly reduce the linear heat transfer transmittance while ensuring structural mechanical properties. A larger thermal break width leads to the low load-bearing capacity of the structure. Lower BFRP compressive reinforcements need enough diameter to provide compressive strength and shear reinforcement forms can significantly increase the mechanical properties of the thermal break. Upper tensile reinforcements can be selected depending on the stiffness and insulation requirements in practical engineering. Based on experimental results, force transfer mechanism is analyzed and the rationality of the structural design is identified. The maximum length of the cantilever slab without shear reinforcement forms is approximately 2.94 m when meets the serviceability limit state. The results suggest that newly designed BFRP thermal break structure can effectively solve thermal bridge problems in balcony.

GWO-ANFIS-RD3PG: A reinforcement learning approach with dynamic adjustment and dual replay mechanism for building energy forecasting

Reliable prediction of building energy consumption is essential for effective and sustainable energy management. Traditional forecasting methods, however, face challenges when dealing with sudden changes in energy consumption. To address the above-mentioned issue, we introduce the GWO-ANFIS-RD3PG prediction model in this paper. This model aims to ensure global forecasting accuracy while minimizing prediction errors at sudden change points. A Grey Wolf Optimization (GWO) algorithm with the Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed to predict the energy consumption type and its fluctuation magnitude for the next time step. Within the Recurrent Dual Experience Replay Buffer DDPG (RD3PG) prediction module, we employ Long Short-Term Memory (LSTM), as the actor network in the Deep Deterministic Policy Gradient (DDPG), to account for long-term dependencies in time series data. Notably, we introduce an adaptive action modification mechanism that allows the agent to optimize actions based on the output of the aforementioned ANFIS, enabling real-time adjustments during sudden change. To further enhance the model’s performance, we adopt a dual experience replay mechanism to store data samples from sudden change points, capturing insight information during these anomalies. Experimental results on two real-world datasets demonstrate that this method reduces MAE by 5.81% and 13.47%, and RMSE by 5.69% and 15.21% compared to the state-of-art models, showing the significance of the proposed method for energy efficiency improvement in real-world building operations.

Transfer learning and source domain restructuring-based BiLSTM approach for building energy consumption prediction

ABSTRACT Currently, building energy consumption prediction typically relies on vast amounts of historical data. However, for newly constructed buildings, the scarcity of data leads to reduced prediction accuracy. To address this challenge, this paper proposes a novel approach that integrates transfer learning with a source domain reconstruction-based BiLSTM model for building energy consumption prediction. In the first stage, both source and target domains are clustered into profile types using k-means. For each profile type in the target domain, the most similar profiles in the source domain are identified using Maximum Mean Discrepancy and Dynamic Time Warping. The source domain is then reconstructed by combining these identified profiles based on their proportions in the target domain. Subsequently, a feature extraction method based on EMD-CWT-Conv is introduced. Empirical Mode Decomposition is first applied to decompose and filter the source domain data. Continuous Wavelet Transform is then employed to extract distinctive frequency-domain and time-domain features from both the reconstructed source domain and the target domain. Final predictions are made using transfer learning and fine-tuning. Experiments on a grocery shop and a school show that the proposed approach reduces Mean Absolute Percentage Error by at least 13.19% and 17.67%, respectively.

A Comparative Study of Building Energy Consumption Prediction Methods

Continued usage of fossil fuel-based electricity generation is one of the main factors for the greenhouse effect. As the greenhouse effect increase, the ambient temperature of the earth will also increase. As the temperature increase, the usage of air conditioning in buildings is also expected to increase. Since that more than 50 % of building energy consumption goes to air conditioning, it is utterly important to look into the methods that can be used to predict the impact of variations in temperature towards building energy consumption. This paper hence tries to perform a conceptual review on the prevalent methods that have been used for prediction of energy consumption, grouped in the category known as the white box, grey box and black box. The comparison of the different methods used in forecasting of energy consumption is discussed in terms of application, input, specific approach, advantage and disadvantage. It is hoped that the work carried out in this paper will be the reference to jump start the research work of others in this field of study.

Incorporating PCMs and thermal insulation into building walls and their competition in building energy consumption reduction

To diminish the 30 % share of buildings in final energy consumption, in this study, phase change material (PCM) and insulation are incorporated into the walls of the building. The primary goal is to determine whether insulation or PCM is more effective in reducing heat exchange through walls. Defining the parameters of the indoor setpoint (7 cases), the type of material (9 cases of PCM and one thermal insulation), the thickness of PCM or insulation (2 cases), and their location (3 cases: L1, L2, and L3), energy consumption (output parameter) was investigated in 420 cases. Because the geographic location of the building has a significant effect on energy consumption, in four different climate regions (ASHRAE index: 3B, 2B, 4B, and 4B), the competition between PCM and insulation in reducing energy consumption was investigated running 1680 cases. In the first climate zone, a layer of PCMs (3 cm thickness) with a melting range of 22–25 °C must installed at the L2 location to achieve the 61.8 % reduction in annual energy demand. If the thickness reaches 6 cm, the optimal material (PCM) should be installed at L3. If the indoor temperature is set higher than 27 °C, insulation should be installed instead of PCM. In the second and third zones, in all cases, it is better to install insulation than PCM. In the fourth zone, at a thickness of 3 cm, PCM can compete with insulation, but at a thickness of 6 cm, insulation is almost a better option. Numerical results affirm that in 71.4 % of cases, thermal insulation is superior to PCM. Genarally it is not recommended to install insulation/PCM in layers close to the building interior.