Building Energy Cost Research Articles

Selecting suitable passive design strategies for residential high-rise buildings in tropical climates to minimize building energy demand

Passive design strategies (PDS) are a fitting solution to reduce the ever-growing energy cost of residential high-rise buildings in tropical regions. However, PDSs’ building energy saving potential significantly varies with local climate conditions, but it has been sparsely investigated. Hence, this study investigated the energy-saving efficiency of eight common PDSs integrated into a typical residential high-rise building in three sub-climates: extremely hot humid (0 A), very hot humid (1 A), and warm humid (3 A) defined by ASHRAE for the tropical climate. This study developed a Building Performance Analysis (BPA) workflow with a BIM-based simulation framework and local and global sensitivity analyses for the building energy analysis. The global sensitivity analysis revealed that low e-coating on glasses is the most influential PDS for 0 A and 1 A climates, but it has a negative effect in the sub-climate zone 3 A. The low-conducting exterior walls are the most effective PDS in the sub-climate zone 3 A, but they are poorly performed in the other two sub-climate zones. Based on the energy calculation and sensitivity analysis, this study proposes the best PDS groups, saving up to 40.1 %, 63.5 %, and 31.7 % of average annual building consumption in the sub-climate zones, 0 A, 1 A, and 3 A climates.

Photovoltaic cells with transparency for glass coverage: case study in party space

Sustainable energy and technological development in electricity generation processes offer opportunities for the development and utilization of new photovoltaic technologies in construction. Photovoltaic cells for glazed surfaces, known as double glass or double-skin, have been applied in modern buildings due to their attributed characteristics that can enhance thermal comfort, provide natural lighting for internal areas, ensure privacy in external environments, and reduce energy consumption. The objective of this study is to investigate the viability of using double glass in the glazed roof of a family party venue. The qualitative method, a case study, was employed to assess the demand for electrical energy in the building and the potential use of double glass photovoltaic technologies. Market research was initially conducted with technology suppliers, enabling the evaluation of characteristics for the technological and economic feasibility of the project. The results show that the installation of double glass photovoltaic technology offers 40% transparency to solar radiation through the roof, resulting in thermal and luminous comfort. In terms of economic viability, the study demonstrates the possibility of return on investment in 4.6 years, considering energy generation, reduced building energy costs, and installation expenses. The installation of double glass technology, according to market research, is economically viable and generates local electrical energy for residents, providing comfort in the environment and enhancing the quality of life for occupants.

Feasibility study with EnergyPlus simulation for solar chemical heat pump unit introduced into building as next-generation energy supply system

From the viewpoint of rising energy demand and energy costs in buildings, there is an urgent need to develop next generation building energy supply systems characterized by improved resource efficiency and environmental friendliness. The solar chemical heat pump (SCHP) unit can provide heating and cooling in buildings with high efficiency and sustainability, positioning it as a potential candidate. A feasibility study is conducted to introduce the SCHP units into a building in Chiba, Japan, to evaluate the operating characteristics and energy-saving potentials. The building and its HVAC (Heating, Ventilation, and Air Conditioning) system featuring the SCHP unit are introduced into the building energy simulation through EnergyPlus software for the first-step examination. 3E (energy, environment, economy) analysis of the distinctions among conventional, chemical heat pump (CHP), and SCHP systems is conducted to enhance the efficiency of building energy supply systems. Furthermore, the effects of different climate zones and heat and electricity storage equipment on operation characteristics are studied. The study reveals that the SCHP system demonstrates a 75% lower energy consumption, 72% decreased CO2 emissions, and 73% reduced running costs than the conventional system in Chiba City. Moreover, it is shown that integrating the heat storage tank and the electricity storage battery into the SCHP system can reduce reliance on external energy, significantly enhancing the system efficiency.

Comparative study of univariate and multivariate strategy for short-term forecasting of heat demand density: Exploring single and hybrid deep learning models

Accurate short-term forecasting of heating energy demand is needed for achieving optimal building energy management, cost savings, environmental sustainability, and responsible energy consumption. Furthermore, short-term heating energy prediction contributes to zero-energy building performance in cold climates. Given the critical importance of short-term forecasting in heating energy management, this study evaluated six prevalent deep-learning algorithms to predict energy load, including single and hybrid models. The overall best-performing predictors were hybrid models using Convolutional Neural Networks, regardless of whether they were multivariate or univariate. Nevertheless, while the multivariate models performed better in the first hour, the univariate models often were more accurate in the final 24 h. Thus, the best-performing predictor of the first timestep was a multivariate hybrid Convolutional Neural Network–Recurrent Neural Network model with a coefficient of determination (R²) of 0.98 and the lowest mean absolute error. Yet, the best-performing predictor of the final timestep was the univariate hybrid model Convolutional Neural Network–Long Short-Term Memory with an R² of 0.80. Also, the prediction accuracy of the best-performing multivariate hybrid models reduced faster per hour compared to the univariate models. These findings suggest that multivariate models may be better suited for early timestep predictions, while univariate models may be better suited for later time steps. Hence, combining the models can enhance accuracy at various timesteps for achieving high fidelity in forecasting and offering a comprehensive tool for energy management.

Methods of optimization energy consumption in residential and public buildings with the availability of alternative sources of energy supply

The article is devoted to the analysis of the potential for increasing the efficiency of electricity consumption in residential and administrative buildings in the presence of various energy sources and storage systems. This task is relevant in view of the spread of renewable energy sources both in centralized power supply systems and at local facilities and the significant impact of unstable generation on the cost of electricity in the market. In particular, the main consumers of electricity, which can be used as "consumers-regulators", as well as storage systems available for use in buildings, are considered. Taking into account that a significant amount of electricity is used or can be used in building air-conditioning systems, as well as for the needs of hot water supply, the construction of mathematical models of such systems for existing buildings will allow the creation of effective electrical load management systems to optimize energy costs for traditional buildings and ensure autonomy for buildings with close to zero energy consumption. The article describes the priority tasks to be solved to build an energy management system to minimize energy costs and increase the efficiency of the country's energy system and local energy systems of communities. The formulation of the tasks follows from the analysis of information on the actual consumption schedules of residential and public buildings and the analysis of their mutual correlation, which allows using these findings to develop algorithms for monitoring energy consumption and load management on the consumer side. Further stages of the study include additional measurements of actual energy consumption at the facilities with a discreteness of several seconds to an hour, while simultaneously recording potential influencing factors, which will allow creating a digital model of building energy consumption. A preliminary analysis of the research shows that the most promising mathematical apparatus for building such a model is the use of neural networks.

Air purifier or fresh air system? A comparison of energy consumption and cost in urban China residential buildings

Air purifier or fresh air system? A comparison of energy consumption and cost in urban China residential buildings

A review of the photothermal-photovoltaic energy supply system for building in solar energy enrichment zones

The application of solar PT-PV technology is an important way to achieve clean energy supply and energy conservation and emission reduction in building field. Simultaneously meeting the thermal and electric need of building is one of the main development directions of solar PT-PV energy supply system. The core objective is to build the efficient and stable energy supply system and effectively evaluate their benefit. The major objective of this study was to provide a comprehensive literature review to classify, analyze the performance and evaluate the benefit of different solar PT-PV energy supply system for building. This review summarized the latest research result on solar PT, solar PV, solar PT-PV comprehensive utilization, solar thermal/electric energy supply system based on HES, and the system composition, system characteristic, system optimization and technical innovation were also discussed. Additionally, a detailed discussion was conducted on the efficiency optimization of solar PT-PV energy supply system, as well as the current efficiency situation and the method for improving the efficiency. Sequentially, the economic and environmental benefit evaluation standard and calculation method of solar PT-PV energy supply system was summarized, specifically in terms of operating cost, energy cost, and carbon emission reduction in common building. Finally, the challenge of optimizing the performance for solar PT-PV energy supply system in solar energy enrichment zones was summarized, and the development direction and application prospect of the system in building field was proposed.

TECHNICAL AND ECONOMIC ANALYSIS OF THE SYSTEM LONG-WAVE INFRARED HEATING IN DIFFERENT TYPES OF BUILDINGS

The paper presents the calculation of energy costs for heating buildings with three different heating systems, in order to determine the feasibility of using long-wave radiant heaters. The current rules of energy certification of buildings and related state standards of Ukraine were used as the calculation method. A technical and economic analysis was carried out, thanks to which savings from the transition to a radiant heating system in residential, public and industrial buildings located in the same weather environment were determined. The feasibility of radiant heating systems beyond the usual scope of use, namely in residential buildings, which make up the majority of all heating structures in Ukraine, and small architectural forms, such as, for example, modular buildings of retail establishments, public catering, etc., has been studied and provided. Bilux electric infrared long-wave heaters were chosen as the main research system. Competing systems are a water two-pipe system with free-flowing radiators and electric wall convectors. The key difference between traditional water heating systems, from the point of view of calculating energy consumption, is determined, which is the absence of losses in pipelines. It is justified that radiant heating systems are more appropriate in buildings with a floor height of more than 4 meters. It has been proven that in buildings of smaller volume, the cost reduction is also quite significant.

A Case Study in Building Energy Passportization

The operating energy costs of buildings account for approximately 70-80% of the total costs throughout the entire life cycle of a building. From the moment putting the building into operation, it begins to consume energy, mechanical, electrical, and natural resources. In buildings, all construction and technical systems naturally degrade over time, both in terms of performance and efficiency, i.e. operating and maintenance building costs are rising, energy consumption is increasing, and microclimate quality is declining. As a solution to this issue, it is possible to consider building energy passport, as a tool to control the optimal building operation according to the indicators of the building passport and as an encouragement way of cities' sustainability. The building passport by its energy efficiency (BEP) and rational use of material resources is a special document- a certificate that contains information about the geometric and technical parameters of the building, its functional purpose, design solutions, thermal characteristics, and energy performance. This paper discusses the current state of the building passportization process in Azerbaijan, and analyzes the existing shortcomings. Categories and component parts of BEP, types and levels of building information and data, scheme of inputs and extractions data during the building life cycle, key tasks of BEP, and strategic actions for the successful development of BEP are given. Building energy efficiency rating classes are calculated, and the main procedures to enhance the energy efficiency class are given. The requirements for experts who carry out the buildings` passportization are systematized. Received: 1 August 2023 | Revised: 13 September 2023 | Accepted: 20 September 2023 Conflicts of Interest The author declares that she has no conflicts of interest to this work. Data Availability Statement Data available on request from the corresponding author upon reasonable request. Author Contribution Statement Samira Akbarova: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Project administration.

Optimization of building demand flexibility using reinforcement learning and rule-based expert systems

The increasing use of renewable energy in buildings requires optimization of building demand flexibility to reduce energy costs and carbon emissions. Nevertheless, the optimization process is generally challenging that needs to consider the on-site intermittent energy supply, dynamic building energy demand, and proper utilization of energy storage systems. Leveraging the growing availability of operational data in buildings, data-driven strategies such as reinforcement learning (RL) have emerged as effective approaches to optimizing building demand flexibility. However, training a reliable RL agent is practically data-demanding and time-consuming, limiting its practical applicability. This study proposes a new strategy that integrates a rule-based expert system (RBES) and RL agents into the decision-making process to jointly reduce building energy costs, minimize the peak-to-average ratio (PAR) of grid power, and maximize PV self-consumption. In this strategy, the RBES determines system operation directly in less complex decision-making scenarios, while, in more intricate decision-making environments, it provides a reference decision for RL to explore optimal solutions further. This integration empowers RL agents to avoid unnecessary exploration and significantly enhance learning efficiency. The proposed strategy was tested using PV generation data and energy consumption data of a low energy office building. The results demonstrated an 85.7% improvement in RL learning efficiency and this strategy can successfully avoid sub-optimal convergence during policy learning. Compared to relying solely on the RBES, the proposed strategy led to 5.4% and 19.2% reductions in the electricity costs and daily PAR of grid power at peak hours, respectively. The strategy also achieved a satisfying PV self-consumption ratio of 62.4%, which is merely 0.4% lower than the optimal value determined by the RBES strategy that prioritized maximizing PV self-consumption. Additionally, compared with a model predictive control method developed for cost reduction, the strategy achieved similar cost savings while significantly reducing the decision time.

Optimization and dynamic techno-economic assessment of integrated combined ejector cooling, heating, and power system

Solar energy systems have been extensively studied for their potential to reduce greenhouse gas emissions and their economic feasibility in buildings. However, due to the high initial cost, the implementation of these systems has been limited. This study proposes an innovative energy system, incorporating Photovoltaic Thermal (PVT) technology without batteries and heaters, and ejector cooling for smart buildings that can interact with the power grid. The proposed system aims to offset the energy costs of buildings by selling excess electricity to the grid. Both thermodynamic and economic analyses were conducted using TRNSYS software, and optimization was applied to meet maximum exergy efficiency and minimum cost objectives. Results indicate that the maximum annual exergy efficiency of the system can reach 21.98%, while the minimum total production cost unit is $22.48/MWh. Operating conditions yield an annual exergy efficiency of 14.18%, with a total production cost unit of $34.01/MWh. Overall, findings demonstrate that this proposed system can efficiently provide electricity to the building while offering surplus energy for sale to the grid.

Thermodynamic analyses and performance improvement on a novel cascade-coupling-heating heat pump system for high efficiency hot water production

In the background of global warming and reducing carbon emission, air-source heat pump water heater is used as an energy efficient technology to improve the efficiency of building hot water production, which may account for 21–41% of building energy cost. However, there are still space for the energy efficiency improvement of heat pump water heater, as there is large temperature difference between water and refrigerant, which may limit the energy performance (especially at low ambient temperature) but receives little attention. Therefore, a novel cascade-coupling-heating heat pump system with less water-refrigerant temperature different is proposed in this paper, where part of the heat is first provided at the low-temperature stage, reducing the heat load at the high-temperature stage and the high-temperature stage compressor power, and increasing system energy efficiency. To study the system, a theoretical model was established and verified through experiments. Experimental and theoretical results show that: in the ambient temperature range of 243.15 K ∼ 323.15 K, the average and maximum improvement in the coefficient of performance of the new system reach 34.8% and 107.7%, respectively, comparing with cascade heat pump; and in the ambient temperature range of 248.15 K ∼ 323.15 K, when comparing with single-stage heat pump, the new system reveals average and maximum improvement in the coefficient of performance as high as 25.8% and 55.6%, respectively. This study provide a promising potential technology for efficiency water heating, and lay the basis for further study and application of the new system.

Enhancing Building Energy Efficiency with Aluminum Composite Material Facade: A Performance Simulation Study using Building Energy Modeling and Building Information Modeling

Building facade is an integral piece to the overall design of a building, which not only ensures adequate interior thermal comfort, minimizing cooling load rate but also lowering overall building energy consumption. In recent years, aluminum composite material wall (ACM) is a new decorative material that is increasingly being used by developers, designers, and architects, which led to many innovative building facade designs. It is a straightforward and versatile product that provides a weather-resistant, sound-insulation, heat-insulation, earthquake-resistant, and shock-resistant façade that is simple to install. As a result, this study proposes a perfomance of energy simulation with ACM material applied in building design using Building Energy Modeling (BEM). Energy simulation in buildings using a Building Information Modeling (BIM) system is proposed to reduce the Energy Use Intensity (EUI) and energy cost of building in its construction process. The results of this study are expected to assist architects and building managers in improving and enhancing the energy efficiency of buildings. These significant findings demonstrate the potential of using ACM wall to improve building energy efficiency.

Exploring the Benefits and Limitations of Digital Twin Technology in Building Energy

Buildings consume a significant amount of energy throughout their lifecycle; Thus, sustainable energy management is crucial for all buildings, and controlling energy consumption has become increasingly important for achieving sustainable construction. Digital twin (DT) technology, which lies at the core of Industry 4.0, has gained widespread adoption in various fields, including building energy analysis. With the ability to monitor, optimize, and predict building energy consumption in real time. DT technology has enabled sustainable building energy management and cost reduction. This paper provides a comprehensive review of the development and application of DT technology in building energy. Specifically, it discusses the background of building information modeling (BIM) and DT technology and their application in energy optimization in buildings. Additionally, this article reviews the application of DT technology in building energy management, indoor environmental monitoring, and building energy efficiency evaluation. It also examines the benefits and challenges of implementing DT technology in building energy analysis and highlights recent case studies. Furthermore, this review emphasizes emerging trends and opportunities for future research, including integrating machine learning techniques with DT technology. The use of DT technology in the energy sector is gaining momentum as efforts to optimize energy efficiency and reduce carbon emissions continue. The advancement of building energy analysis and machine learning technologies is expected to enhance prediction accuracy, optimize energy efficiency, and improve management processes. These advancements have become the focal point of current literature and have the potential to facilitate the transition to clean energy, ultimately achieving sustainable development goals.

Analysis of Operational Energy between Adaptive Reuse Historic Buildings (ARHB) and Modern Office Buildings: A Case Study in Sri Lanka

Adaptive Reuse of Historic Buildings (ARHB) is a new concept in developing countries like Sri Lanka. One of the main concerns for the intendancy of decision makers to ARHB is the operational energy. This paper analyzes the research gap of reusing historical buildings as office spaces by utilizing their structural and architectural designs and preserving the buildings’ authenticity for the future. It further aims to protect energy-efficient historical buildings from getting demolished and replaced with new modern buildings. A set of operational energy variables of modern office buildings and the potential historic buildings that can be reused as office spaces was established. During the early 1990s, old Dutch-era buildings in the country were mainly used as government office buildings. Three Dutch-era buildings in Galle Fort and three modern buildings in Colombo City have been selected as the case studies. Design-Builder (DB) software was used to comprehensively analyze sets of operational energy consumption variables. Selected historic buildings in Galle consumed 143.74 kWh/m2, 156.34 kWh/m2, and 209.39 kWh/m2 while modern buildings consumed 337.29 kWh/m2, 210.99 kWh/m2, and 382.57 kWh/m2 as operational energy, respectively. According to the analysis, the operational energy requirement of ARHB is comparatively lesser than that of modern buildings. This study, therefore, mainly concludes that the historical buildings saved more operational energy than the modern building envelopes while considerably reducing environmental impacts and saving the building energy cost.

Predicting an energy use intensity and cost of residential energy-efficient buildings using various parameters: ANN analysis

Predicting an energy use intensity and cost of residential energy-efficient buildings using various parameters: ANN analysis

High-Performance Glazing for Enhancing Sustainable Environment in Arid Region’s Healthcare Projects

The integration of sustainability rating systems in healthcare projects and healthcare building envelope specifications is a growing concern in the construction industry, especially in the arid region. The external facade of healthcare buildings is one of the most significant contributors to the energy cost and comfort level of healthcare buildings in such a region. This study undertook a comprehensive comparison analysis of an adaptive model of high-performance glazing (HPG) specifications for patient rooms in a case study inside Saudi Arabia based on multi-criteria, including the LEED Healthcare rating system. The study used a technical comparative analysis for three onsite glazing models with HAB software v6.0 based on specifications of specialist manufacturer organizations for glazing window performance, climatic conditions, and the region’s culture. Significant results in the case study project were achieved in energy saving and sustainability ranking in the healthcare rating system, providing new specification guidelines for HPG applications in healthcare buildings located in an arid region, and cultural environment considerations.

Energy cost and consumption reduction of an office building by Chaotic Satin Bowerbird Optimization Algorithm with model predictive control and artificial neural network: A case study

Energy cost and consumption reduction of an office building by Chaotic Satin Bowerbird Optimization Algorithm with model predictive control and artificial neural network: A case study

The impact of the wall insulation material and variable refrigerant flow system on building energy consumption and cost

The use of VRF system and insulation in building envelope are both considered as promising option to reduce energy consumption of a building. This study analysis energy saving potential of VRF system and building insulation using modelling and simulation of a typical office building. The model office building is simulated with the weather of Hyderabad, Sindh, Pakistan using EnergyPlus building simulation software. The simulation cases include conventional and VRF air conditioning systems with and without insulation to evaluate and compare the annual cooling and energy savings and payback period. Results showed that by replacing conventional air conditioner with VRF AC electrical power can be reduced by 42-45%. It is also noted that Cellulose, expanded polystyrene, extruded polystyrene and polyurethane insulations can save around 49.5, 51.4, 51.6, and 54.54% of electricity, respectively. In the case VRF air conditioner used with Cellulose, expanded polystyrene, extruded polystyrene and polyurethane insulation may reduce electricity consumption by 66.5, 67.4, 67.5 and 68.9 %, respectively. The payback period varies from 7 to 15 months. However, cellulose with VRF air conditioner has the least payback period of around 7 months. The longest payback period of around 15 months was noted for the un-insulated office building with VRF air conditioner. Despite having longer payback period, the combination of polyurethane insulation with VRF air conditioning system is the most efficient combination.

Assessment of Energy, Environmental and Economic Costs of Buildings’ Thermal Insulation–Influence of Type of Use and Climate

Among the aspects with major impacts on the energy and environmental performance of a building, the thermal insulation of the opaque elements of its envelope stands out. This work assesses the influence of the application of thermal insulation to the opaque elements of the building’s envelope on the thermal comfort conditions indoors; moreover, the influence of the thermal insulation on the energy, environmental, and economic costs over the building’s complete life cycle is evaluated. For this purpose, the three most commonly used thermal insulating materials (expanded polystyrene—EPS, extruded polystyrene—XPS, and mineral wool—MW), thicknesses between 0 (without insulation) and 40 cm, five climates (hot, warm, moderate, cold, and very cold), and six types of use (apartment, housing, clinic, school, bank branch, and supermarket) were considered. EPS reveals itself to be the most promising thermal insulation material, both in economic and environmental terms, so it was selected for this study. The EPS’ optimal thickness depends on the building’s type of use, the climate, and the perspective from which the assessment is carried out (energy, environmental, or economic). The results show that the economically optimal thicknesses of thermal insulation are significantly lower than the corresponding ones in environmental terms. Furthermore, the application of thermal insulation to the opaque building’s envelope is more beneficial in energy and environmental terms than from an economic perspective.