Energy Balance Of Building Research Articles

Modified Thermocouple Sensor and External Reference Junction Enhance Accuracy in Indoor Air Temperature Measurements.

Indoor air temperature belongs to the most important climatic variables in indoor climate research, affecting thermal comfort, energy balance, and air movement in buildings. This paper focuses on measurement errors when using thermocouples in indoor temperature measurements, with special attention on measurements of air temperature. We briefly discuss errors in thermocouple measurements, noting that, for temperatures restricted to indoor temperature ranges, a thermocouple Type T performs much better than stated in “standards”. When thermocouples are described in the literature, industrial applications are primarily considered, involving temperatures up to several hundred degrees and with moderate demands on accuracy. In indoor applications, the temperature difference between the measuring and the reference junction is often only a few degrees. Thus, the error contribution from the thermocouple itself is almost immeasurable, while the dominant error source is in the internal reference temperature compensation in the measuring instrument. It was shown that using an external reference junction can decrease the measurement error substantially (i.e., down to a few hundredths of a degree) in room temperature measurements. One example of how such a device may be assembled is provided. A special application of room temperature measurements involves measuring indoor air temperature. Here, errors, due to radiation influence on the sensor from surrounding surfaces, were surprisingly high. The means to estimate the radiative influence on typical thermocouples are presented, along with suggestions for modification of thermocouple sensors to lower the radiation impact and thereby improve the measurement accuracy.

Impact of weather data and climate change projections in the refurbishment design of residential buildings in cooling dominated climate

The methodology, the site and the dataset as well as the emissions scenario considered in the weather file definition influence the numerical evaluation of efficiency measures resilience. With a complete statistical and critical approach, the paper analyzes the importance of these aspects by means of a residential case study simulated in Benevento, a city of south Italy.Using data monitored from 2015 to 2020, a current weather file is built with different methodologies. The comparison indicates that there is not repeatability of the year chosen as a reference for the various months and thus the resolution of the building energy balance could bring different results. Some future climate projections are also generated on medium (2050 s) and long (2080 s) term considering different emission scenarios. With long term projection, the heating degree days are reduced also of − 21% meanwhile the cooling degree days are more than double compared with the current condition. This suggests a remarked transition towards a dominant cooling climate for Benevento.Moreover, when the climate change is considered, the insulation intervention and the installation of double glazed low emissive window is not resilient because the heating energy need decreases also of −56%, but the cooling energy need increases of + 62% (2080 s). If the efficiency measures include also the cool roof and the external shadings, the cooling demand could be reduced until –33% in some scenarios (e.g. RCP 4.5-50th percentile) and increased (+31%) in some others (e.g. 2080 s).

RETRACTED: Optimization of zero-energy building by multi-criteria optimization method: A case study

Many subjects and objects are included into the zero-energy building investigation while the conventional optimal approach is suffering from its limitations. The boundary of energy balance and physic of zero-energy buildings in various regions highlighted with various architectural attributions require to be more investigated and assured. As reported by the statistics, it needs further integrating materials and installing costs in zero-energy buildings. In this paper, due to the increasing energy consumption in buildings, a new global multiple-criteria optimization model for zero-energy buildings, combining this model with the comprehensive assessment approach is conducted. The optimization design approaches for renewable energy structures included here are the multiple-criteria optimization by Enhanced Red Fox Optimization Algorithm on the initial design as concerns energy optimum models and costs, and the integration of Grey Multiple-Level Complete Assessment approach is employed to optimum model, which are the energy-conserving, solar energy application effectiveness, social and economic aspects. The optimum solution is proposed based on the chosen decision according to the global optimum model. This solution can help the engineer to design practical constructions. Finally, a multiple-objective optimal model for a case study placed in Beijing, China, is proposed to achieve an optimum design effect. Based on the study, efficient decisions can be made by designers with utilization of the proposed method. This design can easily be used in the considered real applications.

Building indoor model in PALM-4U: indoor climate, energy demand, and the interaction between buildings and the urban microclimate

Abstract. There is a strong interaction between the urban atmospheric canopy layer and the building energy balance. The urban atmospheric conditions affect the heat transfer through exterior walls, the long-wave heat transfer between the building surfaces and the surroundings, the short-wave solar heat gains, and the heat transport by ventilation. Considering also the internal heat gains and the heat capacity of the building structure, the energy demand for heating and cooling and the indoor thermal environment can be calculated based on the urban microclimatic conditions. According to the building energy concept, the energy demand results in an (anthropogenic) waste heat; this is directly transferred to the urban environment. Furthermore, the indoor temperature is re-coupled via the building envelope to the urban environment and affects indirectly the urban microclimate with a temporally lagged and damped temperature fluctuation. We developed a holistic building model for the combined calculation of indoor climate and energy demand based on an analytic solution of Fourier's equation and implemented this model into the PALM model.

Impact of green walls occultation on energy balance: Development of a TRNSYS model on a brick masonry house

Most thermal simulations of buildings do not include green walls during thermal calculations. This study integrates and evaluates the effect of extensive green walls (GWs) on the energy balance of buildings using a global code of dynamic thermal simulation of buildings under TRNSYS. The first part presents the equations integrated in the model. A description of the dynamic thermal simulation software is carried out as well as the methods of integration of the developed model. Then, the modeling of the influence of GW (Ivy or Virginia Creeper) on a more global scale is detailed. It highlights the thermal and energy impact of GWs in winter and summer on a brick house located in Lille in France. This is a concrete case of representation of an existing residential building in an urban environment to help thermal design offices to take them into account in the simulations. It has been shown that the presence of vegetation protects the facades against summer overheating and therefore reduces the energy requirements for air conditioning. In winter, the use of deciduous plants on facades exposed to the sun makes it possible to benefit from solar radiation and limit the demand for energy for heating. Finally, the GWs technique is more suitable for the thermal renovation of weakly insulated buildings.

Estimating the influence of building and urban form on the thermal loads of urban dwellings in the Mediterranean climate using machine learning

ABSTRACT The paper presents a novel method of generating metamodels that can quantify the influence of urban form on the heating and cooling loads of dwellings for the Mediterranean climate. The goal of the metamodels is to inform the early urban design process with quick and accurate feedback on the energy demand of a given urban configuration. The proposed method generates training datasets through Monte Carlo dynamic energy simulations of a single thermal zone. The study focuses on the geometrical parameters that affect building energy balance at the urban scale, such as dwelling shape, compactness, adjacencies and shading, utilizing a set of morphological indicators to relate these parameters to heating and cooling loads. The study focuses on the Mediterranean climate of Thessaloniki, Greece and utilizes several open-source tools (Ladybug Tools, EnergyPlus and Scikit-learn) under a streamlined workflow. The metamodels, which are trained using the Random Forest algorithm are then validated on 12 real-world urban sites of Thessaloniki with a reported Mean Average Percentage Error (MAPE) of 12% and 15% for heating and cooling loads, respectively.

A review on behavioural propensity for building load and energy profile development – Model inadequacy and improved approach

To achieve building energy conservation goals, models for forecasting energy consumption with energy-related occupant behavior inclusive must be encompassed in energy performance efforts. Regardless of the efforts made in the residential building sector and building energy performance, the scientific community still lacks a reliable and simple instrument that can instantaneously address and solve the energy and environmental balance of buildings. This study attempts to give a chronological review of both AI-based and conventional models employed in energy consumption prediction, based on the model type, forecasting accuracy, and applied areas. And also to identify drivers of consumption and their implications in building energy performance as they have remained a challenging task, volatile and confusing. The applications, strengths, and disadvantages of such approaches are contrasted and linked, while suitable recommendations are made on future directions of the research. This review offers valuable suggestions for researchers in choosing an appropriate model for forecasting energy consumption.

Cool roof coating impact on roof-mounted photovoltaic solar modules at texas green power microgrid

Cool-roofing is effective in reducing cooling load and increasing the energy balance of buildings with high solar reflectance throughout the cooling season. This article proposed a large-scale of a resilient Microgrid, along with comprehensive thermal analyses for residential building, focused on cool roof-mounted solar photovoltaic system. This project boosts generated power while circumventing a voided warranty issue with the roof temperatures. A white silicone coating on the metal roof with 186 solar photovoltaic 330-W modules were applied to supply solar energy, utilizing a DC-coupled system that features nine 5 kW inverters each with a maximum system input of 600Vdc and 92 batteries with 225.216 kWh energy storage. Upon the completion of the project, the input and output voltages produced by the inverters daily/monthly, along with the battery energy storage, were monitored and authenticated with thermal modeling calculations. Moreover, cool-roof benefit to reduce the solar cell thermal voltage and module/roof heat flux based on the conductive coefficient was evaluated. As a result, solar power efficiency was improved by 10.4%, producing 294.6 kWh of solar energy despite system losses, and the roof temperature was reduced by 3.82°F, increasing 1.91% of output power. Lastly, the comparison study of cool/hot solar power systems proved that cool-roof application significantly enhances safety, sustainable energy development, and building comfort when globally applied.

Numerical analysis of phase change materials for optimizing the energy balance of a nearly zero energy building

Phase change materials receive increasing attention for their potential to make building environmentally sustainable and to reduce the overheating problem. Quantitative results are needed for understanding the incidence on the energy balance of low consumption buildings and for estimating the possible increment of renewable energy self-consumptions.With this aim, by means of a multi-stage approach, the optimal configuration for microencapsulated materials integration in term of melting properties, thickness and position is discussed. It is considered the application of different management strategies for the heating and cooling system and the variability of weather conditions. The influence of insulation type and back wall technology is also explored.The results for the case study, a single-family home already certified as nearly zero energy building, highlights the potentialities in term of reduction of the cooling demand for Mediterranean and Continental climate but also the penalty due to reduction of solar gain during the winter.

Urban Building Energy Modeling: an hourly energy balance model of residential buildings at a district scale

The energy consumption of buildings is related to several factors, such as the construction and geometric characteristics, occupancy, climate and microclimate conditions, solar exposure, and urban morphology. However, the interaction between buildings and the surrounding urban context should also be taken into consideration in energy consumption models. The aim of this work has been to create a bottom-up model in order to evaluate the energy balance of residential buildings at an urban scale, starting from the hourly energy consumption data. This modeling approach considers the building characteristics together with urban variables to describe the energy balance of the built environment; it can therefore be used to manage heterogeneous types of data at different scales and it can offer accurate spatial-temporal information on the energy performance of buildings. Detailed heat balance methods can be used at a building scale to estimate heating loads, but this urban-scale simplified model can also be used as a decision tool to support urban design explorations and for policy purposes. This urban energy consumption model was verified for a case study of a district in Turin, Italy, with the support of a GIS tool, considering hourly energy consumption data of about 50 residential users for two or three consecutive heating seasons. The results show that a simplified model, based on low quality and quantity data, which are typical of an urban scale, can be a powerful tool for the evaluation and spatial representation of the energy needs of buildings at an urban scale.

The Use of Ground Source Heat Pump to Achieve a Net Zero Energy Building

Currently, ground source heat pump (GSHP) technology is being studied, as the use of the ground as a source of renewable energy allows significant energy savings to be obtained. Therefore, it is useful to quantify how these savings help to achieve the energy balance of a Net Zero Energy Building (NZEB) compared to an air source heat pump or a condensing boiler coupled to a chiller. This paper assesses how these savings affect the number of photovoltaic panels installed on the roof of a building to obtain the NZEB target. The study is conducted by dynamic simulation for a building used as a bed and breakfast, virtually placed in two Italian towns. The energy savings and reduction of CO2 emissions, the percentage of renewable energy used, and the photovoltaic surface needed are assessed. Finally, the discounted payback period is calculated. The results show that the GSHP, unlike the systems to which it is compared, allows an NZEB to be obtained by balancing yearly energy consumption with energy production systems which only use on-site renewable energy sources (by exploiting the surface available on the roof) for both of the climatic conditions considered. GSHP also allows primary energy requests equal to or less than 57 kWh/m2 to be obtained.

The Challenge for Building Integration of Highly Transparent Photovoltaics and Photoelectrochromic Devices

This paper holds a critical review of current research activities dealing with smart architectural glazing worldwide. Hereafter, the main trends are analyzed and critically reported, with open issues, challenges, and opportunities, providing an accurate description of technological evolution of devices in time. This manuscript deals with some well-known, highly performing technologies, such as semitransparent photovoltaics and novel photoelectrochromic devices, the readiest, probably, to reach the final stage of development, to disclose the manifold advantages of multifunctional, smart glazing. The complex, overall effects of their building integration are also reported, especially regarding energy balance and indoor visual comfort in buildings.

The Control of Venetian Blinds: A Solution for Reduction of Energy Consumption Preserving Visual Comfort

Glazing surfaces strongly affect the building energy balance considering heat losses, solar gains and daylighting. Appropriate operation of the screens is required to control the transmitted solar radiation, preventing internal overheating while assuring visual comfort. Consequently, in the building design phase, solar control systems have become crucial devices to achieve high energy standards. An operation based on well-defined control strategies can help to reduce cooling energy consumption and ensure appropriate levels of natural lighting. The present study aims at investigating the effect of smart screening strategies on the energy consumption of a test building designed in the Mediterranean climate. With the aim of automatically setting the inclination of venetian blind slats, the necessary equations are analytically found out and applied. Equations obtained are based on the position of the sun with respect to the wall orientation. In the case of a cloudy day or an unlit surface, empirical laws are determined to optimize the shielding. These are extrapolated through energy simulations conducted with the EnergyPlus software. Finally, using the same software, the actual benefits obtained by the method used are assessed, in terms of energy and CO2 emissions saved in a test environment.

Thermal Comfort Aspects of Solar Gains during the Heating Season

Glazing plays a key role in the energy balance of buildings. The aim of this paper is to enlighten the thermal discomfort caused by large glazed areas in the heating season and to point out a possible solution that can provide proper thermal comfort with low energy use. It is unusual to discuss the negative effects of solar gains on thermal comfort during the heating season. However, there are cases when glazing may lead to unforeseen indoor thermal discomfort conditions. Laboratory and on site measurements were performed in order to assess thermal discomfort caused by direct and diffuse radiation. It was shown that the WBGT (Wet Bulb Globe Temperature) index may exceed even 30 °C in the winter season in a room having large glazed area oriented to east. Laboratory tests performed in climate chamber have shown that the high PMV values cannot be reduced below 1.0, increasing the air change rate in the room. Using opaque drapes, the WBGT index was reduced by 2 °C, but the daylighting decreased substantially. It was demonstrated that by using advanced personalized ventilation systems, the appropriate thermal comfort can be provided avoiding the reduction of daylighting.

Effect of skylight–roof ratio on warehouse building energy balance and thermal–visual comfort in hot-humid climate area

Skylight–roofs installation on low-rise commercial/industrial building has the potentials to reduce energy consumption through the use of daylighting, yet it may also lead to an increase in room temperature and thermal discomfort for the occupants. The purpose of this numerical study is to evaluate the effect of the skylights ratios on the roof to the energy efficiency for artificial lighting, indoor daylight illuminance level and thermal discomfort in a warehousing building in the tropics. The simulations of low-rise warehouse building are performed using different simulation tools such as TRNSYS©, CONTAM©, and Velux daylight Visualizer©. Furthermore, the optimal skylight–roof ratio to this type of buildings will be figured out by considering the aspects of energy consumption and thermal comfort of occupants. The numerical simulation results show that the ratio of the area of the skylights designed between 2.5 and 5% of the whole roof can provide lighting energy efficiency to buildings in the tropics more than 50% during the day with a reasonable increase in the degree hour thermal discomfort.

Comparison between cork-based and conventional green roof solutions

Green roofs are increasingly being used to improve the energy balance and stormwater management of buildings. This work examines the thermal behaviour, water drainage and vegetation growth of two green roof systems: a conventional system containing extruded polystyrene and polyethylene, and an alternative cork-based system. In the new system, an eco-friendly expanded cork layer is used to provide thermal resistance and water storage capacity in a more sustainable way, as cork is a natural material. This material can also be used as an uncoated finishing layer for architectural purposes.The main goal of this work was to see if the new system is reliable in real environmental conditions and to compare its behaviour to that of the conventional system for a full year. This work presents the results of a fully functioning prototype built in Portugal with a technical substrate 10 cm thick and planted with a variety of vegetation. The reference and proposed systems were installed side by side and monitored under spring, summer, autumn and winter conditions.The thermal insulation and the water drainage and storage capacity provided by the cork-based green roof were found to be similar to those of the reference solution, with the expanded cork layer showing a more marked temperature delay and a more effective management of rainfall events under dry conditions. Additionally, it was found that the growth and health of plants in the cork-based green roof were comparable to those of the reference solution, indicating the good performance of the cork system.

Methodology for Comparison of Building Daylighting Systems

The energy balance of buildings depends greatly on the type of external fencing, including translucent. The article presents a brief description of different types of daylighting systems that have different optical, geometric and thermal characteristics. The change in these characteristics affects the quality of lighting in the room, as well as determines the operating costs associated with losses and heat flows into the building through translucent fences. The task of comparing and choosing the optimal daylighting system should take into account all of the above factors. The authors propose a complex comparison criterion that takes into account thermal, optical, operational properties and capital costs. The structure of the proposed criterion allows you to add new indicators or remove irrelevant for a particular consumer comparison parameters. The method is composed and the calculated dependences for determining the numerical value of individual indicators included in the complex criterion are given. All parameters included in the proposed criterion have no dimension. This makes it possible to reduce the dependence of the calculations on changes in current energy prices.

The influence of heat loss from pipes in an unheated basement on the heating energy consumption of an entire typical apartment building

The majority of old apartment buildings were designed with an unheated basement. Building service systems such as district heating heat exchangers and pipes for domestic hot water and for space heating are usually located in this unheated basement. In addition, these locations are connected with shafts. All these pipe’s heat losses increase air temperature in the basement. If these losses are included into the building energy balance, then they decrease heat loss through the basement ceiling. The basement’s heat balance is also dependent on heat loss from the basement envelope and outdoor air exchange in the basement. In early stages of design, designers and energy auditors need rough models to make decisions in limited information conditions. Once the effects of heat losses from pipes become apparent, they need to be factored into the buildings energy balance, and their effects on heat loss through the basement ceiling needs to be calculated. In this paper we analyse the effect these heat losses have on the service system’s heat gains and heat loss through an uninsulated basement ceiling at different basement insulation levels and with different thicknesses of pipe insulation. From our study we found that pipe losses in the basement increase the building energy performance value by at least 4 kWh/(m²∙a) and their impact on a renovated apartment building is very important.

Modelling drivers of variance and adaptation for the prediction of thermal perception and energy use in zero energy buildings

As thermal perception is a subjective “condition of mind”, a high variance in observed thermal sensation votes does not come to a surprise. Literature reviews show a large number of individual and contextual influences. However, the quantification of the effect of individual drivers on thermal perception as well as thermal adaptation and their integration into thermal comfort models is still an open field of research. Still, analyses of the energy balance of zero-energy buildings (ZEB) are using assumptions related to the user’s needs e.g. in terms of thermal comfort. First, this paper explores a novel combination of a biophysical model and an adaptive framework (called the ATHB*TNZ approach) and discusses the applicability of such approach to model individual differences in thermal perception. Second, results of an implementation of these individualized comfort prediction on the energy balance of a zero energy building are presented together with the resulting discomfort hours. Results show that the consideration of physiological differences and adaptive processes in the modelling approach can replicate observed variations in thermal perception. The energy balance of a ZEB is hardly affected by set point adjustments due to individual requirements, but discomfort hours strongly depend on individual characteristics of occupants.

Artificial Neural Networks to assess energy and environmental performance of buildings: An Italian case study

Abstract Approximately 40% of the European energy consumption and a large proportion of environmental impacts are related to the building sector. However, the selection of adequate and correct designs can provide considerable energy savings and reduce environmental impacts. To achieve this objective, a simultaneous energy and environmental assessment of a building's life cycle is necessary. To date, the resolution of this complex problem is entrusted to numerous software and calculation algorithms that are often complex to use. They involve long diagnosis phases and are characterised by the lack of a common language. Despite the efforts by the scientific community in the building sector, there is no simple and reliable tool that simultaneously solves the energy and environmental balance of buildings. In this work, the authors address this challenge by proposing the application of an Artificial Neural Network. Due to the high reliability of learning algorithms in the resolution of complex and non-linear problems, it was possible to simultaneously solve two different but strongly dependent aspects after a deep training phase. In previous researches, the authors applied several topologies of neural networks, which were trained on a large and representative database and developed for the Italian building stock. The database, characterised by several building models simulated in different climatic conditions, collects 29 inputs (13 energy data and 16 environmental data) and provides 7 outputs, 1 for heating energy demand and 6 of the most used indicators in life cycle assessment of buildings. A statistical analysis of the results confirmed that the proposed method is appropriate to achieve the goal of the study. The best artificial neural network for each output presented low Root Mean Square Error, Mean Absolute Error lower than 5%, and determination coefficient close to 1. The excellent results confirmed that this methodology can be extended in any context and to any condition (other countries and building stocks). Furthermore, the implementation of this solution algorithm in a software program can enable the development of a suitable decision support tool, which is simple, reliable, and easy to use even for a non-expert user. The possibility to use an instrument to predict a building's performance in its design and planning phase, represent an important result to support decision-making processes toward more sustainable choices.