Multi-family Buildings Research Articles

Simulation of thermal comfort and energy demand in buildings of sub-Himalayan eastern India - Impact of climate change at mid (2050) and distant (2080) future

The global warming associated with climate change predicted by the Intergovernmental Panel on Climate Change (IPCC) is expected to deteriorate the indoor climate of free-running buildings. Features like proper orientation and wall thickness are important for the design of a building that is resilient to the impact of climate change. However, the implementation of these features is sometimes difficult, especially in a rugged hilly location. A whole building simulation was performed using DesignBuilder for an existing 3-storey free running multi-family concrete building located in the sub-Himalayan region of eastern India, for thermal comfort and energy demand during the present and the climate change scenarios of 2050 and 2080. The results show an increasing trend in the indoor operative temperature during the future climatic scenario, with the condition inside the top roof-exposed floor deteriorating the most. A decrease of 59.8% and 81.2% in the annual heating energy and an increase of 221.9% and 467.0% in the annual cooling energy were predicted for the future climate of 2050 and 2080 compared to the present. Parametric analysis performed considering orientation, wall U-value, infiltration rate and window-to-wall ratios revealed that the east/south-east facing orientation would perform the best with regard to overheating due to climate change. Further, the use of autoclaved aerated concrete (AAC) brick is recommended along with the decrease in air infiltration rate and window-to-wall ratio to improve the thermal performance of the indoor environment. In addition, we have also proposed a method to assess the under-cooling of an indoor environment.

Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil

The shape and orientation of a building influence the energy demand, therefore optimal decisions should only be made rigorously supported by energy evaluation programs, which allow for measuring the energy demand of a building more precisely. The main purpose of this research is to evaluate the shape and orientation of massive residential social housing multifamily buildings to find the best solar positioning to minimize cooling and heating demands simultaneously in the bioclimatic zone 2 (Cfa) in the southern region of Brazil. To do this, this study utilizes multi-objective optimization with a genetic algorithm (NSGA-II) simulating the thermal behavior in EnergyPlus and performing the optimization with a Python language programming code, totalizing 80,000 simulations. The main results showed that solar orientation optimization could reduce the total demand by 4% for the “H” shape and 22% for linear buildings in the isolated scenario. For the condominium condition, the reduction is 2% for the “H” typology and 8% for the linear shape. The results presented can help engineers and architects to design more energy-efficient buildings and address the energetic vulnerability in the same building. Moreover, future work can be carried out to improve the constructive pattern replicated all over the country, improving the surroundings.

Evaluation of district heating patterns for Hungarian residential buildings: Case study of Budapest

The present study focuses on analysing the heat consumption of multifamily buildings. The study evaluates measured district heating consumption data in Budapest, Hungary. The examined 218 buildings were grouped into 11 building types based on their architectural characteristics and analysed separately. The study aims to answer the question: how the buildings' characteristics influence the energy demand of the buildings. In the buildings only the total energy consumption is measured, thus the domestic hot water energy demand was examined in the summer months, when there is no heating in the building. The domestic hot water heat loss was 37–54% of total heat consumption in the summer period. The specific total district heating consumption data [kWh/m3/day] has higher deviation in colder months. The length of heating period is 183 days in Hungary, however the average length of heating period was longer in the examined buildings and it was even longer in case of the uninsulated buildings. From the measured consumption data the energy signature curves were developed for each building type for both the insulated and uninsulated buildings separately and the results were compared and analysed in detail. The energy signature diagrams showed a significant gap between the insulated and uninsulated buildings’ total district heating consumption data in the heating period. Lines were fitted to the data and the slope of the lines fitted to uninsulated buildings’ data indicate higher decline for every building type. A separation method was also suggested to divide the data of heating and non-heating period if its term is unknown. The difference between the average slope values of the fitted lines were analysed compared to buildings’ characteristics. It aimed to examine if the consumption reduction is influenced by the buildings’ physical parameters. In conclusion, the buildings’ characteristics did not always influence the final results (e.g. domestic hot water heat loss). But uninsulated buildings tend to have longer heating periods and buildings with smaller cooling surface area per heated volume had a predominantly lower energy consumption reduction rate.

Libro del Edificio Electrónico (LdE-e): Advancing towards a Comprehensive Tool for the Management and Renovation of Multifamily Buildings in Spain

In 2018, the Energy Performance of Buildings Directive (EPBD) introduced Building Renovation Passports (BRP) to enable buildings to scale energy performance through a Scheduled Renovations Roadmap (SRR). The Digital Building Logbook (DBL) was introduced in 2021 as a repository of relevant building data to facilitate informed decision-making and information sharing among stakeholders. In Spain, both tools (DBL + SRR) have been studied separately in an incipient way. However, the interconnection of data in the tools come from the same document base. Evidence suggests that when building information is used in isolation, its value is diluted without stakeholder awareness. In this paper, we move towards unifying both tools (DBL+SRR) in a single comprehensive tool called the Libro del Edificio Electrónico (LdE-e), with the aim of producing a single building database to drive multi-building renovations. For this purpose, the data fields of existing building information, assessment and management tools in Spain were studied in detail and reinterpreted in a new interconnected data structure. To evaluate the formulation of the LdE-e proposal, 11 semi-structured interviews were held with a panel of 13 experts specialized in real estate, building and energy efficiency. After these sessions, the LdE-e was reformulated, and the model was strengthened by analyzing vectors such as governance, management, usability, data flows, stakeholders and the impact of including new technologies such as BIM and blockchain. The results suggest that the LdE-e would improve control of the operation and maintenance of (new or existing) buildings, the programming of renovation actions based on deficits identified in technical inspections, and other aspects.

Energy poverty, housing conditions, and self-assessed health: evidence from Poland

Energy poverty, i.e., inefficient heating and insufficient access to energy services, can turn a shelter into a health hazard. We find that substandard housing and ineffective heating is associated with a higher risk of poor health in an urban context. We surveyed people living in two middle-sized cities in a coal-dependent region of Poland and used objective and subjective indicators of energy poverty and self-assessed health status. We demonstrate that people who live in substandard housing are more likely to exhibit poor musculoskeletal and cardiovascular outcomes, by 10 and 6 pp, respectively than otherwise similar people living in suitable housing conditions. We show that energy-poor people who use coal or a wood stove have a 24 pp higher likelihood of respiratory disease than the energy-poor who live in flats connected to district heating. We also find that a significant amount of the explained variance in the probability of respiratory disease is attributable to energy poverty. To improve the housing conditions and reduce the risk of poor health outcomes, we recommend two policy instruments: 1) a full subsidy for thermal retrofits and connecting multi-family buildings to the district heating network and 2) a targeted energy voucher for clean heating.

Structureborne noise transmission from a sports court

The authors recently investigated a multifamily high-rise building that included a sports court. Noise from bouncing basketballs and similar sources generated undesirable noise transmission in adjacent units. While that was not surprising, the pattern of transmission throughout the building was not as expected. Vibration measurements taken in the building are compared to predicted impact flanking transmission to evaluate the vibration paths through the building. While sports courts are not that common, the results are also applicable to impacts from fitness center sources, and even to prediction of impact noise in lateral and diagonal directions.

Αn integrated life cycle assessment and life cycle costing approach towards sustainable building renovation via a dynamic online tool

Building stock retrofitting is essential to achieve the ambitious sustainability goals of the building sector due to its high energy consumption rates. The evaluation of the various building interventions shall be holistically assessed in terms of environmental and costing impact. The aim of this paper is twofold: First, it presents the innovative characteristics of a developed online tool (Virtual intEgrated platfoRm on LIfe cycle AnalYsis - VERIFY) able to perform dynamic life cycle analysis and global warming impact assessments by capitalizing on the well-known LCA and LCC methodologies, applicable in the case of building renovation. VERIFY is able to analyse dynamic life cycle inventories that consider the temporal profiles of energy consumption, and the time-dependent temperature changes, while being also interoperable in terms of exchanging data with other available energy simulation engines, or even using real-time monitoring data from sensors, processing any data time granulation. Second, the paper evaluates, from a life cycle perspective, the impact of specific energy retrofitting measures, meeting the Passive House Standard, for the case of a multi-family residential building in Athens, Greece. The proposed energy-retrofitting scenario examines actions related to the deep retrofitting of the building envelope and the upgrade of the thermal components as well as to the incorporation of clean electricity generation based on renewable energy systems; all aiming to drastically reduce the environmental impact of the building, rendering it almost near zero energy. Through the planned infrastructure installations, the primary energy needs and CO2eq emissions were reduced by 91 % and by 95 % respectively, while for a building operational lifespan of 25 years, savings up to 515 k€ compared to the baseline scenario, can be achieved.

Utilization of an Automatic Tool for Building Material Selection by Integrating Life Cycle Sustainability Assessment in the Early Design Stages in BIM

Recent international scientific studies have described the current situation regarding CO2 emissions and have provided evidence of its catastrophic short- and medium-term consequences. The implementation of solutions of a more sustainable nature to reduce and mitigate this situation is becoming increasingly urgent. To this end, the integration of multi-dimension and life cycle assessment into the design process of buildings can help and support decision making. Life Cycle Sustainability Assessment (LCSA) is one of the scientific community’s most widely recognized methodologies for this purpose, combining the evaluation of the social, economic, and social dimensions (Triple Bottom Line). One of the main obstacles to implementing this methodology lies in the difficulties in automatically comparing alternative design options for the selection of different materials. To overcome this limitation, the authors developed the BIM3LCA (Building Information Modelling Three Life Cycle Assessment) tool conceived to guide the decision-making process during the early design steps. This study introduces a Building Information Modelling (BIM) plug-in development and validates its application in a case study to support the multi-criteria building material selection based on the LCSA implementation at the early design stage. Three building material alternatives for the structural system of a multi-family residential building are employed to validate this plug-in. The results show the viability of using this tool during the early design stages and demonstrates the consistency of the results regarding the use of the BIM model to conduct the LCSA. The study discusses the benefits and limitations of the BIM3LCA tool. This research contributes towards the integration of multi-dimension real-time assessment in the building design process by using semantically rich BIM models.

On the Minimum and Maximum Variable Cost of Heating of the Flat in Multifamily Building

Heat cost allocation is commonly used in existing buildings supplied by centralized sources of heating/cooling and provided with individual metering systems. However, this process is not always fair for the users, since “fairness” strongly depends on the methods established to allocate variable and fixed costs among the dwellings. That is why unrealistic cost for heating may be allocated for specific flats. However, there is a lack of evidence about procedures as to how maximum and minimum variable cost of heating may be calculated for specific flats in multifamily building for a specific heating season. This paper presents different methods for estimation of maximum and minimum variable cost of heating of flat in multifamily buildings, the use of which depends of the availability of input data for specific buildings. Evaluation of the proposed methods is made on the example of a case study multifamily building located in Poland. It was shown that the maximum variable costs of heat purchase for specific flats in the analyzed building were in the range from 169% to 256% of the average unit cost of heat, depending on the method used. The recommendation about the accuracy of proposed methods is also provided by the authors.

Dynamic analysis of the heat theft issue for residential buildings

European Union is facing a dramatic energy crisis, due to the huge increase of the natural gas cost, due to the Russian-Ukrainian war. In this framework, the fair allocation of natural gas costs, used for space heating purposes in residential centralized heating systems, is becoming a crucial issue. These systems suffer for the heat theft phenomenon, where an unheated apartment may benefit of the heat transfer from the surrounding heated apartments. Unfortunately, there is no consensus regarding a suitable heat accounting method, implemented in order to limit heat thefts. In this work, two novel billing strategies are proposed. In the first one, the heating cost includes both a variable fee and a constant fee. The second one also considers a penalty for the unheated apartments. A case study is analyzed. It consists of a multifamily building including 4 floors and located in Naples. This building is equipped with a centralized heating system, coupled with radiators, variable speed pumps, thermostatic valves, and heat metering devices. A suitable dynamic simulation model is developed in TRNSYS 18 environment to analyze the energy and economic performance of the system. The comfort parameters of unheated users are also analyzed and discussed. The proposed billing strategies are able to smooth the heating bill increase for the heated apartments adjacent to the unheated user. The novel billing strategy proposed by this research can significantly mitigate the heat theft issue. In particular, results show that the penalty should be almost 2.5 times the constant fee for preventing the unheated user issue. Simulations also show that installing a suitable thermal insulation for the walls among adjacent apartments may dramatically limit the heat thefts. However, insulating such walls may result often unfeasible for the owners of the apartments, due to reduction of the floor area and to the major refurbishment required.

An ELECTRE TRI B-Based Decision Framework to Support the Energy Project Manager in Dealing with Retrofit Processes at District Scale

Cities represent the places with the highest environmental and energy impact in the world. Transforming them in a sustainable way has the potential to reduce the pressures of these areas. The building stock could be the driving force behind the energy transition of cities. With this in mind, understanding the priorities of undertaking a massive green regeneration operation becomes crucial to optimizing the use of public funds such as those of the National Recovery and Resilience Plans (NRRPs) that EU Member States have at their disposal. For this purpose, a multi-criteria ELECTRE TRI-B (ELimination Et Choix Traduisant La REalité TRI-B) model was used to provide useful information in prioritizing intervention on the existing building stock to achieve the sustainability targets set at European and international levels. The model was tested on a real case study located in Turin (Italy) to improve the management process by classifying intervention on a building stock characterized by different typologies and construction periods. Looking at the results, the retrofit operations with the highest priority relate to the apartment building sector from 1946 to 1970 and the multifamily building sector from 1919 to 1960. Despite the high initial investment requirements, an ecological transformation of this stock would result in significant reductions in health impacts, more green jobs, and lower resources consumption. The model is useful for managing public policies in this area by providing guidance to the project manager on how to proceed in the provision of ad hoc funds and could optimize the process of local community energy generation.

Influence of indoor environmental quality and dwelling satisfaction aspects on overall satisfaction: Findings from a Swedish national survey

The objective of this study is to contribute to the discussion on the impact of dwelling satisfaction aspects (size, standard, layout, appearance/aesthetics, well-being, cost and area/neighbourhood) and perceived indoor environmental quality (thermal comfort, air quality, satisfaction with daylight and acoustic comfort) on occupants’ overall satisfaction. This article uses data from the Swedish National Survey, BETSI (2007/08). The results are representative of adults living in multi-family and single-family buildings (1597 responses/955 buildings). Linear regression models are developed with overall satisfaction as the dependent variable and independent variables: seven satisfaction aspects, four indoor environmental quality factors and all combined (eleven). An all-model explained 54.7% of the results (best performed). All the retained variables (except satisfaction with daylight) are statistically significant predictors. Satisfaction with well-being (b = 0.286) and satisfaction with dwellings’ standard (b = 0.188) have the greatest effect on overall satisfaction. The model with the IEQ aspects explained only 35.5% of the results. Reliability statistics (Cronbach’s alpha) and confirmatory factor analysis have been implemented in the dataset. The responses can be categorized into two clusters. The two clusters were significantly different across living duration, dwelling type, age category and tenure status.

Beyond Well-Being: The Assessment of the Energy Renovation in Latvia by the Residents

Abstract Multi-family building renovation represents a key policy area at the same time, predominantly affects the daily life of residents. The paper tackles the energy renovations of multi-family buildings in Latvia. Specifically, it investigates how the renovation process affects the residents’ health and well-being, their perception, and their understanding of the renovation process. To evaluate the residents’ perception, a survey was conducted in thirteen buildings renovated using energy performance contracting to assess the preparation, execution, and impact of the renovation project. The survey revealed the lack of communication between the parties involved and co-design as the roadblocks to upscale the renovation process in Latvia using energy performance contracting. The paper shows aspects of the process that need to be improved to scale up the renovation in Latvia.

Smoke Control System Performance Analysis in Accordance with Floor Plan Configuration of High-rise Multi-family Residential Buildings

In Korea, the vestibule of a special escape stair and a fire service access elevator is typically used together. The floor plan configuration of high-rise multi-family residential buildings where occupant evacuation elevators are installed is of two types depending on the vestibule structure of the occupant evacuation elevators and fire service access elevators. In one type, the vestibules of an occupant evacuation elevator and a fire service access elevator face each other, and in the other type, each vestibule faces the corridor. As a result of analyzing the smoke control volume flow rate and pressure difference, air volume flow rate to form a pressure difference was used in the lower level of the neutral pressure plane in both the floor plan configurations. The pressure difference above the neutral pressure plane was confirmed to be formed sufficiently high to cause evacuation disturbances in the floor plan configuration without corridor.

Winds in Multi-Family Housing Buildings

Although there is progress regarding high-rise residential buildings, there is a need to know the pathologies caused by the absence of a bioclimatic design or a lack of knowledge regarding bioclimatic architecture, characteristics of the materials, simulation context and passive and active sustainability strategies that can be applied. The purpose of the present study was to apply a psychometric design for design techniques applied to housing complexes, the case study made up of 300 high-rise housing or horizontal property buildings built and inhabited to evaluate the comfort of users by calculating the sustainable characteristics of the materials and bioclimatic simulation using the design builder software. The results show that according to the calculation in the residential complex, a wind shadow is produced on the other buildings in the city of more than 800 meters (Z2), that is, it protects them from the wind or prevents other buildings from being ventilated. It is concluded that climate change, by affecting our environment, affects our cities and it is necessary to link new design and construction strategies.

A rule-based energy management strategy for a low-temperature solar/wind-driven heating system optimized by the machine learning-assisted grey wolf approach

This work presents an innovative, practical, and cost-effective solution for advancing state-of-the-art intelligent building energy systems and aiding the intended worldwide green transition with maximum renewable integration. The vanadium chloride cycle, electrolyzer unit, and Alkaline fuel cell are powered by the sun's and wind's energy to produce/store/use hydrogen. A rule-based control scheme is designed to provide a sophisticated interplay between the demand/supply sides, components, and local energy networks to reduce peak capacity, lower emissions, and save energy costs. TRNSYS is used to analyze and compare the techno-economic-environmental indicators of the conventional system and the suggested smart model for a multi-family building in Sweden. A grey wolf method is built in MATLAB with the help of machine learning to determine the optimum operating state with the maximum accuracy and the least amount of computational time. The results reveal that the suggested smart model considerably saves energy and money compared to the conventional system in Sweden while lowering CO2 emissions. According to the optimization results, the grey wolf optimizer and machine learning techniques enable greater total efficiency of 13 %, higher CO2 mitigation of 8 %, a larger cost saving of 38 %, and a reduced levelized energy cost of 41 $/MWh. The scatter distribution of important design parameters shows that altering the fuel cell current and electrode area considerably impacts the system's performance from all angles. The bidirectional connection of the proposed smart system with the heating and electrical networks through the rule-based controller demonstrates that it can supply the building's energy requirements for more than 300 days of the year. Eventually, the major contribution of the vanadium chloride cycle in the summer and the electrolyzer in the winter to the creation of hydrogen highlights the significance of renewable hybridization in reducing the dependence of buildings on energy networks.

Optimization of energetic refurbishment roadmaps for multi-family buildings utilizing heat pumps

A novel methodology for calculating optimized refurbishment roadmaps is developed in this paper. The aim of the roadmaps is to determine when and how should which component of the building envelope and heat generation system be refurbished to achieve the lowest net present value. The integrated optimization approach couples a particle swarm optimization algorithm with a dynamic building simulation of the building envelope and the heat supply system. Due to a free selection of implementation times and refurbishment depth, the optimization method achieves the lowest net present value and high CO2 reduction and is therefore an important contribution to achieve climate neutrality in the building stock.The method is exemplarily applied to a multi-family house built in 1970. In comparison to a standard refurbishment roadmap, cost savings of 6–16 % and CO2 savings of 6–59 % are possible. The sensitivity of the refurbishment roadmap measures is analyzed on the basis of a parametric analysis. Robust optimization results are obtained with a mean refurbishment level of approx. 50 kWh/m2/a of the building envelope. The preferred heat generation system is a bivalent brine-heat pump system with a share of 70 % of the heat load being covered by the electric heat pump.

Water-Sensitive Urban Plan for Lima Metropolitan Area (Peru) Based on Changes in the Urban Landscape from 1990 to 2021

Lima is the second-largest capital of the world located in a desert and already faces water scarcity. Here, more than 30% of the population is supplied by only 2.2% of the national water resources. The urbanization process has an informal nature and occurs at a very accelerated rate. These new settlements lack water infrastructure and access to other services. The objectives of this study are to quantify changes in the urban landscape of Lima Metropolitan Area from 1990 to 2021 to propose a water-sensitive urban plan by detecting changes, urbanization trends and identifying alternative water sources. The trend suggests a future constant increment of the urban areas, diversification of the landscape and more equally distributed land cover. Lima has more disconnected settlements and more complex shapes of urban patches nowadays. The landscape is also more mingled, but cracked. Overall, the trend is to become more disaggregated, demanding small and scattered water solutions. The WSUP includes the implementation of treatment plants in new multi-family buildings, hybrid desalination plants at the coast and parks with fog collectors on the hills. Additionally, these solutions will require the beneficiary community and the local authorities to work together in the planning and maintenance.

Demons of density do higher-density environments put people at greater risk of contagious disease?

We study the relationship between density and COVID during three distinct waves of the pandemic in New York City. Unlike prior work, our analysis uses individual Medicaid claims records, which include a rich array of demographic characteristics and pre-existing medical conditions and cover a near universe of low-income New Yorkers. In brief, our results suggest that living in higher density neighborhoods did not heighten the risk of COVID hospitalization. The size of a multifamily building made little difference either, and people living in public housing developments, which are typically highly dense environments, were less likely to be hospitalized for COVID. However, while neighborhood and building density do not seem to matter, we find significant, positive relationships between COVID hospitalization rates and household size. Specifically, we see that people living in large households or in neighborhoods with high levels of crowding were more likely to be hospitalized for COVID. In other words, our results suggest that crowded living quarters – which can occur at any level of population density – and not density itself, increase the risk of COVID hospitalization. We also see a strong correlation between being unstably housed or living in institutional settings and COVID hospitalizations.

A hybrid machine learning-assisted optimization and rule-based energy monitoring of a green concept based on low-temperature heating and high-temperature cooling system

This article aims to support the targeted worldwide green transition process by introducing and thoroughly analyzing a low-temperature heating and high-temperature cooling, smart building system. This concept allows for greater use of renewable energy while utilizing less input energy than conventional heating and cooling techniques. The proposed system consists of a reversible water-to-water heat pump driven by low-temperature geothermal energy. A rule-based control strategy is developed to establish an intelligent connection with the regional energy grids for peak shaving and compensating for the building's energy costs over the year. The dynamic simulation is carried out for a multi-family building complex in Stockholm, Sweden, using TRNSYS. The most favorable operating condition is determined via an artificial neural network-assisted tri-objective optimizer based on the grey wolf algorithm in MATLAB. The comparison of the proposed smart model with the conventional system in Sweden results in 332%, 203%, and 190% primary energy reduction, cost saving, and carbon dioxide emission mitigation, respectively. As indicated by the parametric results, the conflicting fluctuation between desirable and unfavorable indicators highlights the importance of multi-objective optimization. The grey wolf optimizer obtains 12% higher efficiency, 1.2 MWh lower annual bought energy, 24 $/MWh lower unit cost, and 5.1 MWh more yearly sold energy than the design condition. The scattered distribution reveals that tank volume and subcooling degree are sensitive parameters. According to the transient results, the suggested smart system can independently satisfy the building's heating, cooling, and electricity demands for more than 81% of the year, thanks to the two-way connection with the electricity and heating networks via the rule-based controller.