Increase Building Energy Efficiency Research Articles

City Logistics Solutions for CO2 Emission Reduction and Energy Efficiency: A Comparative Study of Vitoria-Gasteiz, Tartu, and Sønderborg

Modern cities face the challenge of reconciling dynamic development with environmental protection, as well as ensuring a high quality of life for their residents. In a time of continuous urbanization, with more than half of the world’s population living in cities, city logistics plays a crucial role in managing complex urban environments. As part of the concept of sustainable development, city logistics aims to minimize the negative impact of transport on the environment, while increasing operational efficiency and improving the comfort of life of residents in urban agglomerations. This article presents the results of a comparative analysis of the intensity of sustainable urban logistics development in selected cities of the European Union. It examines various strategies that reduce CO2 emissions, improve air quality, and increase building energy efficiency. The analysis demonstrates that cities investing in sustainable urban logistics not only improve their environmental performance but also increase their attractiveness and competitiveness as desirable places to live and work.

Challenges to energy retrofitting of existing office buildings in high-rise high-density cities: The case of Hong Kong

Achieving carbon neutrality by 2050 has become a global goal, sparking concerns regarding energy consumption and carbon emissions in building operations. Office buildings in high-rise high-density cities serve as central business districts, contributing significantly to the city’s economic activity and consuming a lot of energy. The process of retrofitting existing office buildings for energy efficiency in high-rise high-density cities tends to be challenging. However, there is a lack of comprehensive understanding of the challenges involved in office buildings’ energy retrofitting, as they have not been thoroughly explored. This study aims to investigate the challenges to the existing office building energy retrofitting (EOBER) in high-rise high-density cities with real cases in Hong Kong. Initially, a systematic literature review was undertaken to identify 49 potential EOBER challenges and categorized into seven groups: technical, financial, institutional, social, environmental, regulatory, and other categories. Afterward, 23 EOBER challenges were identified through 24 semi-structured interviews with 36 real office building energy retrofitting cases in Hong Kong. Moreover, these challenges were quantified by the Z-numbers-based Delphi survey and analysis. Results show that regulatory challenges are the primary challenges, followed by financial challenges. The lack of government incentives, policies, legislation and regulations significantly hinders practitioners’ ability to engage in energy retrofitting initiatives. The long payback period of building energy retrofitting poses a critical financial concern for practitioners embracing such initiatives. In the end, this research proposed integrated strategies to tackle these challenges and increase building energy efficiency, including launching financial and regulatory incentives, shortening the interval for mandatory energy audits, disseminating knowledge, and diversifying finance channels of building energy retrofitting. The findings contribute to the body of knowledge by employing systems thinking to identify and evaluate EOBER challenges in high-rise high-density cities through empirical methodologies. Moreover, this study provides valuable references for practitioners in navigating these challenges and minimizing risks associated with the retrofitting process.

Heating load prediction in buildings using decision tree machine learning method

In recent years, the burgeoning imperative of energy-efficient building management practices has surged dramatically, underscoring an urgent mandate for comprehensive studies that integrate cutting-edge optimization algorithms with precise heating load forecasting techniques. These studies are not merely endeavors; they represent concerted efforts to increase building energy efficiency and address mounting concerns regarding sustainability and resource utilization. In the intricate domain of heating, ventilation, and air conditioning (HVAC) systems, energy optimization challenges are being meticulously confronted through rigorous exploration and the application of innovative problem-solving methodologies. This pioneering study introduces groundbreaking methodologies by seamlessly integrating two state-of-the-art optimization algorithms— the Red Fox Optimization and the Golden Eagle Optimizer— with the Decision Tree model. This fusion is aimed at enhancing the accuracy of heating load predictions and streamlining HVAC system optimization processes, marking a significant leap toward achieving heightened energy efficiency and operational efficacy in building management practices. The study emphasizes the significance of precise heating load prediction in advancing energy efficiency, realizing cost savings, and fostering environmental sustainability in building management. Furthermore, it delves into the multifaceted impact of various building features on heating load, encompassing variables such as glazing area, orientation, height, relative compactness, roof area, surface area, and wall area. These insights furnish actionable intelligence for refined decision-making processes in both building design and operation. Based on the results, the DT single model experienced the weakest performance among the three models, with R2 = 0.975 and RMSE = 1.608. The model DTFO (DT + FOX) achieves an extraordinary R2 value of 0.996 and RMSE value of 0.961 for heating load prediction, surpassing the performance benchmarks set by other models. This achievement holds considerable promise for aiding engineers in crafting energy-efficient buildings, particularly within the swiftly evolving landscape of smart home technologies.

Investigation of Evaporation Rate for Covered and Uncovered (using recycled materials) Conditions in UiTM Shah Alam

The evaporation rate varies according to temperature, humidity, and wind. The evaporation rate tends to be higher in the hot, dry months and lower in the wetter ones. This may affect the nation’s energy use, indoor air quality, and water availability. This study conducted experiments under three conditions—uncovered, partially, and fully covered to ascertain the evaporation rate at UiTM Shah Alam, Malaysia. Recycled materials such as bottle caps were used in the experiment. The study examined the evaporation rate at UiTM Shah Alam in Selangor. The study discovered that the uncovered surface area evaporated at the highest rates in the morning, noon, and afternoon due to direct solar exposure. As some or all of the surface was shielded from the sun’s rays, partially covered and fully covered surface areas had lower evaporation rates. It shows the evaporation rate for fully covered condition reduced 22 – 50 percent from uncovered condition. Meanwhile, evaporation rate for partially covered condition decreased by 10 – 17 percent compared to uncovered condition. The study offers important information about the variables influencing evaporation rate, which can be used to enhance understanding of evaporation processes and optimize evaporation in various applications. The findings may shed important light on the evaporation process and the variables that influence it, such as temperature, humidity, and cover material. The research results can be used to enhance building design and construction methods, increase building energy efficiency, and guide water management and conservation policies.

Budget constraints in critical scenarios: A position paper on the challenges to improving building performance

This position paper aims to pave the way for a debate on a few under-explored, at least, perhaps even neglected, challenges we face when trying to improve building overall performance. Specifically, we suggest focusing on how the efforts to increase building energy efficiency, building safety, the home and workplace healthiness, and the comfort perceived by the users can be impaired by budget constraints, especially while operating in critical scenarios. On the one hand, restraints on capital expenditures by property owners and other investors affect the decision-making processes for the construction of new buildings or the renovation of existing ones. More beyond, rapidly developing demographic and other anthropological changes, as well as frequently occurred natural disasters, pose extra burdens on the players in the building industry and the real estate market. It has been a fact that the need to adapt to both budget constraints and challenging situations is seldom fully embedded in the studies focusing on improving building performance. Therefore, we call for attentions in research and publications to advocate for complementing the need.

The effectiveness of climate change regulations in the commercial real estate market

Legislation to increase building energy efficiency is a key climate change policy instrument in many countries. Although most of these regulations concern the housing stock, office buildings are also a considerable source of greenhouse gas emissions. Office markets face fewer pricing regulations than the residential market and may thus provide a clearer pricing signal of any policy impacts. This paper focusses on the introduction of Minimum Energy Efficiency Standards (MEES) in England and Wales. Applying machine-learning methods, Difference in Differences (DiD) and Fixed Effects (FE) panel data estimation to a comprehensive database of the London office market, our results suggest that the MEES policy has had a measurable and significant impact and lowered the rents of the combined group of affected office units by 6–8% following the announcement of MEES and in the run-up to implementation. A weakly significant 4.4% rental discount is detected for the bordering but unaffected class of EPC E-rated office buildings relative to the A–C EPC group, perhaps due to market expectations of a further expansion of MEES.

Numerical and experimental estimation of building wall heat flux in presence of moisture transfer

Insulating building envelope is an efficient way to increase building energy efficiency and minimize greenhouse gas emissions related to heating. After building refurbishment, on-site measurements are suitable for verifying the actual thermal transmission properties of plane building components. For instance, the standard ISO 9869-1 describes a HFM method based on the measurement of surface heat flux with heat flow sensor (HFS). This method has been extensively investigated in the literature and successfully applied on vapor tight building walls. Nevertheless, hygroscopic building insulation materials (like biobased materials) are increasingly used, and heat transfer are coupled to moisture transfer within the wall. In this case, the HFS acts as a vapor barrier: it modifies the local moisture transfer and the associated latent heat flux. In this view, this study aims to clarify what it is measured with HFS in presence of moisture transfer. The question is first treated by numerical simulation of heat and moisture transfer within hygroscopic building wall. Then, experiments are carried out on hygroscopic building insulation where the moisture effects are exaggerated.

SmartBuild RecSys: A Recommendation System Based on the Smart Readiness Indicator for Energy Efficiency in Buildings

The Smart Readiness Indicator (SRI) is a newly developed framework that measures a building’s technological readiness to improve its energy efficiency. The integration of data obtained from this framework with data derived from Building Information Modeling (BIM) has the potential to yield compelling results. This research proposes an algorithm for a Recommendation System (RS) that uses SRI and BIM data to advise on building energy-efficiency improvements. Following a modular programming approach, the proposed system is split into two algorithmic approaches linked with two distinct use cases. In the first use case, BIM data are utilized to provide thermal envelope enhancement recommendations. A hybrid Machine Learning (ML) (Random Forest–Decision Tree) algorithm is trained using an Industry Foundation Class (IFC) BIM model of CERTH’S nZEB Smart Home in Greece and Passive House database data. In the second use case, SRI data are utilized to develop an RS for Heating, Ventilation, and Air Conditioning (HVAC) system improvement, in which a process utilizes a filtering function and KNN algorithm to suggest automation levels for building service improvements. Considering the results from both use cases, this paper provides a solid framework that exploits more possibilities for coupling SRI with BIM data. It presents a novel algorithm that exploits these data to facilitate the development of an RS system for increasing building energy efficiency.

Modeling the impacts of building energy efficiency on the thermal microclimate in a midsize German city

Increasing building energy efficiency (BEE) is an established mitigation measure against climate change. However, it is currently less understood, if the implementation of increased BEE could have an impact on urban microclimate and therefore potentially interferes with adaptation efforts to climate change. In this modeling study, we tested the hypothesis that decreased thermal diffusivities of building facades due to building retrofitting will increase sensible heat fluxes at the facade surfaces and can therefore lead to an increase in urban heat exposure. Our modeling results conducted with the urban microclimate model ENVI-met for two different neighborhoods in the mid-sized city of Braunschweig, Germany indicate that retrofitting complete neighborhoods might lead to an increase in urban temperatures by up to 2.5 K locally and 1 K when spatially averaged at daytime. However, at night-time a cooling effect of almost the same magnitude is noted that could reduce the maximum of the urban heat island. Overall, it can be expected that a necessary increase in BEE standards due to their role in climate change mitigation lead to an increase in daytime outdoor heat exposure. Methods to alleviate this trade-off between climate change mitigation and adaptation should be studied in the future.

Do natural resources impact economic growth: An investigation of P5 + 1 countries under sustainable management

Natural resources represent the base of our living and the entire economic activity. Their depletion is a major challenge for the economic development of both developed and developing economies. Their efficient use is an indispensable requirement and must be the aim of the public policies designed by the authorities worldwide. In this research, we have investigated the impact of the natural resources rent on the economic growth in some major wealthy economies of the world (P5 + 1 countries namely: US, UK, France, China, Russia, and Germany). We have applied a quantile-on-quantile regression to analyse this impact on different quantiles and a cross-sectional autoregressive distributed lag (CS-ARDL) approach for the panel of these six countries. The Dumitrescu-Hurlin panel causality test was also used to check the causality between natural resource rents and economic growth in these countries. Results show a negative relationship between natural resources rent and economic growth for the panel but a different impact on quantiles in each country. Only for China and the US, a positive effect can be noticed for both lower and higher quantiles of natural resources and economic growth. The Dumitrescu-Hurlin causality test shows that natural resources can predict economic growth only in China, the U.S., and the panel. In contrast, no causality was found for the other four countries included in the panel. We suggest that nations invest in wind and solar projects, use biofuels and nuclear energy, introduce a temporary profit tax to protect consumers from escalating energy prices, and increase energy efficiency in buildings and industry. Businesses would benefit from a regulatory framework that is uniform and exhaustive, as well as easier to traverse and more receptive to innovation and creativity. Public-private partnership investments in innovation, innovation incentives, and environmental sector opportunities may foster long-term economic growth.

A Review on Optimal Energy Management in Commercial Buildings

The rising cost and demand for energy have prompted the need to devise innovative methods for energy monitoring, control, and conservation. In addition, statistics show that 20% of energy losses are due to the mismanagement of energy. Therefore, the utilization of energy management can make a substantial contribution to reducing the unnecessary usage of energy consumption. In line with that, the intelligent control and optimization of energy management systems integrated with renewable energy resources and energy storage systems are required to increase building energy efficiency while considering the reduction in the cost of energy bills, dependability of the grid, and mitigating carbon emissions. Even though a variety of optimization and control tactics are being utilized to reduce energy consumption in buildings nowadays, several issues remain unsolved. Therefore, this paper presents a critical review of energy management in commercial buildings and a comparative discussion to improve building energy efficiency using both active and passive solutions, which could lead to net-zero energy buildings. This work also explores different optimum energy management controller objectives and constraints concerning user comfort, energy policy, data privacy, and security. In addition, the review depicts prospective future trends and issues for developing an effective building energy management system, which may play an unavoidable part in fulfilling the United Nations Sustainable Development Goals.

Dual-function smart windows with dynamic and fast thermal response for building energy-saving/storage

Thermochromic smart windows are considered an important element for increasing building energy efficiency. However, the phase transition of conventional devices only depends on the surrounding temperature with solar irradiation, which limits their application under different conditions. Here, a thermoelectrochromic dual response device has been designed by combining thermochromic hydroxypropyl cellulose/potassium chloride (HPC/KCl) hydrogel electrolyte and optothermal electrochromic polyaniline (PANI) films. The thermoelectrochromic device (T-ECD) exhibits electrochromic switchable colour tones (light yellow to purple), visible luminous transmittance (15.70–75.53%), and high solar modulation efficiency (60.89%) when this electrochromic switching is combined with thermochromic phenomenon arising from the electrolyte. Further, since PANI is able to store charge reversibly during the electrochromic transition, this device may also be used as a photovoltaic energy storage. Under solar irradiation, the photothermal effect of PANI films can drive the fast phase transition of HPC/KCl hydrogel. The phase transition time of T-ECD is 30 s which is much faster than 3 min of conventional TCD. In addition, a field test further demonstrates that the house model equipped with the T-ECD can reduce the indoor temperature by 13.3 °C compared with that using a traditional glass window. Thus, it is a valuable device to be used in buildings for energy-saving/storage situations. • An innovative T-ECD was designed and shows a wide range of T lum (15.70–75.53%), high ΔT sol (60.89%), low LCST (30 °C). • The T-ECD exhibited photothermal property to drive the fast phase transition (30 s). • Simulating real building-based T-ECD is 13.3 °C lower than that of using a traditional glass window.

Utilization of Solar Energy for Water Heating Application to Improve Building Energy Efficiency: An Experimental Study

The manuscript is written for flow escalation based on an experimental data for a Solar Assisted Heat Pump Water Heater (SAHPWH) increasing building energy efficiency. For the investigation, a Solar Assisted Heat Pump (SAHP) was conceived, manufactured, and tested in real time. The findings of the experiments shows that single glazing with average sun radiation of 600–750 W/m2, COP of approx. 6 can be obtained with identical heat gains. This study shows that when a flat plate collector of area 1.83 m (L) × 1.22 m (W) × 0.1 m (T) with a 0.5-mm-thick black copper plate absorber with clear glazing as a cover receives average radiation of 700 W/m2, then setup can supply 60 litres of water for residential use from 15 °C to 45 °C in approx. 70 min. In addition, the study finds that the collector efficiency factor F’ is likewise shown to have a direct connection with the absorber and an inverse relationship of tube spacing. The findings indicated that the technology has significant commercial potential, particularly in sectors such as with solar resources for improving building energy efficiency.

Improving residential building energy simulations through occupancy data derived from commercial off-the-shelf Wi-Fi sensing technology

One of the main required actions for moving forward in zero-carbon cities’ mission is to increase building energy efficiency. Building energy simulations are key tools for HVAC control, building energy management, testing different building energy efficiency scenarios, and providing feedback to the occupants. Unfortunately, these tools have a significant weakness in occupant behavior modeling and prediction. Several recent studies used different occupancy measurements and methods to predict occupant behavior. However, they suffer from threatening the occupant's privacy and the high cost of their infrastructure and deployment. This paper aims to leverage passive WiFi sensing methods for occupant behavior estimation using commercial off-the-shelf WiFi devices, for which the infrastructure is already available in many buildings. Passive and device-free WiFi sensing does not threaten the occupant's privacy, and its deployment cost is low. Therefore, this method of occupancy measurement has the potential to be used on an urban scale and to play an essential role in zero carbon and smart cities in the future.Different machine learning algorithms have been applied to the collected, denoised, and preprocessed Channel State Information (CSI) data to estimate the occupant behavior. Five schedules of occupancy, occupant activity, lighting, electrical equipment usage, and thermostat set point temperature could be extracted and estimated from CSI data. In the last step, all estimated schedules were fed into EnergyPlus, an energy simulation software, along with other required data for accurate energy demand calculation to estimate heating and cooling demand, which can be used for HVAC control and occupancy feedback.

A Case Study of Refined Building Climate Zoning under Complicated Terrain Conditions in China.

In this study, we first found that the few and sparse meteorological stations used in earlier comprehensive studies of building climate zoning in a complicated terrain area like Chongqing, China, may lead to the inapplicability of building energy efficiency standards in some areas. To address this issue, the study used daily data from 1908 extremely dense surface meteorological stations from 2011 to 2020 in Chongqing, China. In order to conduct fine zoning of building climate in Chongqing, China, GB50176-2016 and ASHRAE standard 169-2021 were employed, respectively. The findings indicated that by using the ASHRAE standard, the entire Chongqing region was classified into five climate zones. The Chongqing region was categorized into three different climate zones using China GB50176-2016: cold zone (CZ), hot summer and cold winter zone (HSCWZ), and mild zone (MZ). Not to be overlooked is the MZ (China’s GB50176-2016)/mixed-humid zone (ASHRAE standard), which is primarily situated at higher elevations in the southeast and northeast of Chongqing. In comparison to the HSCWZ/warm-humid zone, these zones have drastically different building energy efficiency regulations and approaches. According to preliminary projections, improved building climate zoning will to some extent increase building energy efficiency and reduce emissions in Chongqing. Finally, this study case can be replicated in different regions with complicated terrain.

Smart Thermostats for a Campus Microgrid: Demand Control and Improving Air Quality

Achieving nearly zero-energy buildings (nZEB) is one of the main objectives defined by the European Union for achieving carbon neutrality in buildings. nZEBs are heavily reliant on distributed renewable generation energy sources, which create new challenges associated with their inherent intermittency. To achieve nZEB levels, demand management plays an essential role to balance supply and demand. Since up to two-thirds of the total consumed energy in buildings is dispended for Heating, Ventilation and Air Conditioning (HVAC) operations, intelligent control of HVAC loads is of utmost importance. The present work aims to offer a solution to improve a building microgrids’ flexibility by shifting thermal loads and taking advantage of room thermal inertia. Innovation is present in using the internet of things to link several decentralized local microcontrollers with the microgrid and in the applicability of different control algorithms, such as the pre-emptive heating/cooling of a room. The developed solution relies on smart thermostats, which can be integrated into a building management system, or in a microgrid, and are capable of fulfilling the occupants’ need for comfort while complementing the building with needed power flexibility. The equipment is capable of controlling several HVAC systems to guarantee thermal and air quality comfort, as well as coordinate with a building/microgrid operator to reduce energy costs by shifting thermal loads and enacting demand control strategies. The smart thermostat uses an algorithm to calculate room inertia and to pre-emptively heat/cool a room to the desired temperature, avoiding peak hours, taking advantage of variable tariffs for electricity, or periods of solar generation surplus. The smart thermostat was integrated into a university campus microgrid and tested in live classrooms. Since the work was developed during the COVID-19 pandemic, special attention was given to the air quality features. Results show that smart HVAC control is a viable way to provide occupant comfort, as well as contribute to the integration of renewable generation and increase energy efficiency in buildings and microgrids.

Heat Flux and Thermal Characteristics of Electrically Heated Windows: A Case Study

Energy loss through windows can be high relatively compared to other opaque surfaces because insulation performance of fenestration parts is lower in the building envelope. Electrically heated window systems are used to improve the indoor environment, prevent condensation, and increase building energy efficiency. The purpose of this study is to analyze the thermal behaviors of a heated window under a field experiment condition. Experiments were conducted during the winter season (i.e., January and February) with the energy-efficient house that residents occupy. To collect measured data from the experimental house, temperature and heat flux meter sensors were used for the analysis of heat flow patterns. Such measured data were used to calculate heat gain ratios and compare temperature and dew point distribution profiles of heated windows with input power values under the changed condition in the operating temperature of the heated glazing. Results from this study indicated that the input average heat gain ratio was analyzed to be 75.2% in the south-facing and 83.8% in the north-facing at nighttime. Additionally, compared to January, reducing the operating temperature of the heated glazing by 3 °C decreased the input energy in February by 44% and 41% for the south-facing and north-facing windows, respectively. Through such field measurement study, various interesting results that could not be found in controlled laboratory chamber conditions were captured, indicating that the necessity of establishing various control strategies should be considered for the development and commercialization of heated windows.

A Comparison of Energy and Daylighting Performances of Different Window Glazing Types Used in the Traditional Harput House

A review of the history of glass that dates back to the mid-2000 BC pursuant to the archaeological data suggests that the effects of the thermophysical properties of window glass on building energy performance could have been understood only over time. Today, the optimum combinations of thermophysical parameters help significantly reduce the energy demand of the buildings. Furthermore, the energy sustainability is also achieved by increasing building energy efficiency during the early design phase, using building simulation tools. The present study was aimed to comprehensively review the improvements in glazing technologies from past to present. Furthermore, the energy and daylighting performances of the retrofitted traditional Harput house in Turkey were analyzed using a building simulation tool. The results indicated that the use of retrofit measure, i.e., the triple-glazed window with low-e coating filled with Argon gas combined with daylighting control system improved the annual primary energy performance of the building in question located in a cold climatic region of Turkey by %8.20. In addition, it was found that the illuminance of indoors increased by means of higher visible transmittance ensured by the retrofit measure.

ENERGY PERFORMANCE OF BUILDINGS USING ELECTROCHROMIC SMART WINDOWS WITH DIFFERENT WINDOW-WALL RATIOS

ABSTRACT The electrochromic (EC) smart window is a promising intelligent technology for improving the energy performance of a building. When applying a new glazing material, the window-wall ratio (WWR) is regarded as a significant factor related to daylight and building energy losses. However, there have not been any studies examining the relationship between the efficiency of the EC smart window and the WWR. The aim of this study is to provide strategies for mitigating energy losses and environmental impacts from window elements in an office building. It focuses on optimizing the WWR of EC smart windows to increase building energy efficiency. Double EC, low-emissivity (low-E), and clear glazing materials are simulated combined with five WWRs from 0% to 80% with an interval of 20%, four window orientations, and humid subtropical and Mediterranean climates. The results show that a 40% WWR in a southern-facing building façade using a humid subtropical climate setting provides the optimum energy performance of EC glazing among all the configurations tested. Since it was also found that EC glazing reduces the cooling load, it is more suitable for climate conditions characterized by a hotter temperature with greater solar irradiation. Future research should consider the impact of WWR when balancing thermal, lighting and ventilation requirements, and the properties of EC glazing.

ENERGY PERFORMANCE OF BUILDINGS USING ELECTROCHROMIC SMART WINDOWS WITH DIFFERENT WINDOW-WALL RATIOS

ABSTRACT The electrochromic (EC) smart window is a promising intelligent technology for improving the energy performance of a building. When applying a new glazing material, the window-wall ratio (WWR) is regarded as a significant factor related to daylight and building energy losses. However, there have not been any studies examining the relationship between the efficiency of the EC smart window and the WWR. The aim of this study is to provide strategies for mitigating energy losses and environmental impacts from window elements in an office building. It focuses on optimizing the WWR of EC smart windows to increase building energy efficiency. Double EC, low-emissivity (low-E), and clear glazing materials are simulated combined with five WWRs from 0% to 80% with an interval of 20%, four window orientations, and humid subtropical and Mediterranean climates. The results show that a 40% WWR in a southern-facing building façade using a humid subtropical climate setting provides the optimum energy performance of EC glazing among all the configurations tested. Since it was also found that EC glazing reduces the cooling load, it is more suitable for climate conditions characterized by a hotter temperature with greater solar irradiation. Future research should consider the impact of WWR when balancing thermal, lighting and ventilation requirements, and the properties of EC glazing.