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This study investigates an energy-inefficient council housing tower block in London, due for retrofit, by exploring the correlations between occupancy and energy consumption patterns, thermal comfort and building energy performance in the winter. The aim of this study is to evaluate the building performance and develop a reliable building simulation model to be employed in the second phase of the study for developing an energy-efficient and cost-effective retrofit strategy to support the council's plans. The research seeks to demonstrate the significance of using dominant occupancy and energy use profiles as opposed to relying on standardised profiles when calculating building energy consumption using building simulation software. The paper reports on the results from the first phase of the study where a quantitative methodology; including a questionnaire, structured interviews, indoor monitoring, and building simulation modelling was adopted. The results provide evidence that occupants’ socio-demographic characteristics have a considerable impact on household energy consumption and fuel bills. The results also show that indoor environmental issues experienced in many flats are partly attributed to the thermally inefficient building envelope and partly due to occupants’ patterns of operating their homes with evidence of excessive heating energy use in attempts to alleviate the indoor issues experienced. [ABSTRACT FROM AUTHOR]

This paper presents the application of multi-objective genetic algorithms for holistic building design that considers multiple criteria; building energy use, capital cost, daylight distribution and thermal indoor environment. The optimization focus is related to building envelope parameters. To obtain relevant feedback from multi-objective optimizations in early design stages, evaluation speed is a key concern. The paper presents a fast evaluation method fit for the early design stages. It uses a combination of two different quasi-steady-state methods for energy and indoor environment evaluations, a Radiance implementation for daylight simulations and a scripted algorithm for capital cost evaluations. The application of the method is developed around an integrated dynamic model which allows visual design feedback from all evaluations to be an integrated part of the design tool experience. It is concluded, that quasi-steady-state methods implemented as part of integrated dynamic models are fast and flexible enough to support building energy-, indoor environment- and cost-optimization the early design stages. [ABSTRACT FROM AUTHOR]

The selection of a thermal comfort model for establishing indoor optimal hygrothermal conditions during the hot period has a major impact on energy consumption of Net Zero Energy Buildings in hot climates. The objective of this paper is to compare the influence of using different thermal comfort models for zero energy buildings in hot climates. The paper compares the impact of applying Fanger's model, Givoni's model, the ASHRAE 55 adaptive comfort model and the EN 15251 adaptive comfort model on energy consumption and comfort performance. Using both the building performance simulation tools ZEBO and EnergyPlus for energy simulation, an existing prototype of a residential apartment module is used to evaluate energy performance and thermal comfort in two parametric series. The first one is the result of coupling natural ventilation and mechanical cooling and the second one is guided coupling natural ventilation, mechanical cooling and ceiling fans. This study shows that the percentage of energy consumption difference meeting the comfort criteria according to ISO 7730 in comparison to EN 15251, ASHRAE 55 or Givoni's model varied up to 16%, 21% and 24.7%, respectively for the presented case study. More energy savings can be expected for buildings in hot climates with greater cooling demands. [ABSTRACT FROM AUTHOR]

Social housing sector is very important in Brazil, due to the necessity of expansion and investments being placed through a substantial government program. Residential buildings are expected to last at least 50 years according to Brazilian standards. Many residential projects in the sector already perform medium or poorly in terms of energy efficiency and thermal comfort today, and their designs are not analysed considering climate change. Therefore, the aim of this paper is to investigate the result of analysing the thermal and energy performance of social housing projects considering climate change, and to assess the impact on the operational phase of introducing energy efficiency measures in the sector, and exploring methods of adaptation to climate change. A representative project of the lower income sector housing was used as case study with the evaluation of measures through thermal and energy simulation with current and future weather files for the cities of São Paulo and Salvador. Results were compared using predicted energy consumption and cooling and heating degree-hours as indicators. The results highlighted some differences related to the climate scenarios and indicator analysed, and showed that the incorporation of energy efficiency measures in current social housing projects is of fundamental importance to minimize the effects of climate change in the coming decades. [ABSTRACT FROM AUTHOR]

This paper uses an example of an architect designed and occupied suburban house in the temperate climate of Perth, Western Australia to demonstrate how climatic design and low-technology active systems can deliver thermal comfort in average climatic conditions. However when thermal conditions are more extreme acceptable temperature ranges may not be met. Thermal monitoring in the house over eight days of extreme temperatures in summer and winter shows that acceptable temperature ranges may not be met in winter. During extreme winter conditions south facing rooms fall below comfort conditions by up to 3 K in the late night and early morning. The conclusion drawn is that in naturally ventilated buildings personal and psychological behavioral adaptation must go hand-in-hand with climatic design. This behavioral adaptation may become more important in the future if current climatic extremes become the new normal. [ABSTRACT FROM AUTHOR]

Vernacular architecture is closely and traditionally linked to energy efficiency due to its adaptation to climate and location. The main purpose of this paper is to diagnose the hygrothermal behaviour inside the vernacular housings of the Jerte Valley ( Valle del Jerte) , located in the Spanish Central System mountain range ( Sistema Central ). This region is widely characterised by a Mediterranean continental mountain climate with medium-sized mountains and presents two distinguished six-month periods: one is warm and dry, whereas the other is cold and rainy. The objective of the aforementioned diagnosis is to promote the preservation of buildings and its energy refurbishment. As a starting point, a study that associates the region’s monthly climate data with the thermal comfort has been developed. Afterwards, a regional building type has been defined for further use by an energy simulation program in order to measure the hygrothermal behaviour of the envelope. Finally, these results have been related both to thermal comfort and bioclimatic strategies. The results suggest that, during the warm period, indoor conditions are comfortable without the need for an additional energy supply. Nevertheless, in the cold period, indoor conditions are warmer than outdoor conditions, but an additional external energy supply will be required to achieve the comfort zone. Accordingly, it is determined that the refurbishment solutions used for those constructions must maintain intact the bioclimatic strategies that benefit summer conditions. However, strategies that give rise to winter conditions without changing its summer behaviour must be improved. [ABSTRACT FROM AUTHOR]

Energy consumption in buildings is a key factor when accomplishing national and global CO 2 emission goals. The economic savings per building are limited and are difficult to argue. However, the efforts can be aggregated on district or city level: the approach described in this paper is a large scale co-simulation environment that helps to leverage efficiency by providing quantitative information about the efficiency impact on large scale, while minimizing the efforts in modeling single buildings. It addresses the challenge of modeling thermal behavior of a large neighborhood of buildings in order to calculate energy demands, regarding weather conditions, shading and room temperature settings with a time resolution below one hour. A proof of concept applies the method to a demonstration site of residential buildings and shows the heating demand and CO 2 footprint of the neighborhood. [ABSTRACT FROM AUTHOR]

Passive Houses are buildings which provide comfortable indoor conditions at an extremely low heating and cooling load. The peak daily average heating and cooling loads are typically below 10 W/m 2 and annual useful energy demands are below 15 kW h/(m 2 a). The Passive House standard was originally developed in Germany. In this paper we show by hygro-thermal dynamic simulation that it is possible to realize residential Passive Houses in all of the world's relevant climate zones, represented here by Yekaterinburg, Tokyo, Shanghai, Las Vegas, Abu Dhabi, and Singapore. The window quality, insulation levels, and mechanical services all depend on the climate as well as on the building's shape and orientation. The resulting annual energy demand for space conditioning of the Passive Houses is 75 to 95% lower than that of a traditionally insulated building of the same geometry. In humid climates like Shanghai or Singapore, special attention must be paid to humidity aspects. In climates which are hot and humid all year long, the total useful energy demand for sensible and latent cooling may exceed 70 kW h/(m 2 a) even in a Passive House. Finally, it is shown that the architectural quality is not compromised by the Passive House requirements. [ABSTRACT FROM AUTHOR]

Occupancy-Centric Controls (OCC) are specialized control sequences which modulate building operation as a function of the sensed occupancy status, thereby leading to increased energy savings, while maintaining thermal comfort. However, occupancy sensor nonidealities, such as bias, latency, random noise, or misdetection, can degrade the performance of OCCs. In this paper, we perform a systematic simulation-based investigation to understand the impacts of nonidealities from both occupancy counting and presence sensors on OCCs. We use a prototype medium office EnergyPlus-based building model, with a detailed zoning layout, as our evaluation testbed. Subsequently, we evaluate the effectiveness of rule-based, occupancy-centric HVAC, lighting and equipment control strategies on an annualized basis. Furthermore, we systematically characterize occupancy sensor nonidealities. Our results indicate that for counting sensors, although the effects of random noise on energy consumption and thermal comfort are minimal, sensor bias and latency can increase HVAC and whole building energy consumption by up to 3.3 % and 4.9 %, respectively. Additionally, noting that an enumeration approach to understand the sensor impact evaluation map for all considered nonidealities may be resource- and time-intensive, we propose a Bayesian Optimization (BO)-based smart sampling approach to efficiently identify the most impactful sensor nonideality sets. Our results indicate that the proposed BO-based approach is able to increase the computational efficiency by 60-fold, when compared to an exhaustive grid-search (enumeration) method. For presence sensors, we observed that higher false positive rates could have a direct impact on HVAC and whole building energy consumption. A low-grade presence sensor could lead to the increase of HVAC and whole building energy consumption by 12.5 % and 8.1 % on average. [ABSTRACT FROM AUTHOR]

The recast version of the Energy Performance of Buildings Directive (2010/31/EU) proposes a comparative methodology aimed at defining the energy performance of buildings “with a view to achieving cost-optimal levels”. Really, how can the cost-optimal technologies be detected? Moreover, how can the most proper packages of energy efficiency measures be chosen in order to obtain the cost-optimality? This paper would provide answers to these questions, by proposing a new methodology for the evaluation of the cost-optimality, by means of the multi-objective optimization of energy performance of buildings and indoor thermal comfort. The optimization procedure is developed by means of the coupling between MatLab and EnergyPlus, by implementing a genetic algorithm, and it allows the evaluation of profitable and feasible packages of energy efficiency measures applied to buildings. Then, following the adoption of these packages, the global cost over the lifecycle of the building is calculated, in order to identify the cost-optimal solution. After the presentation of the methodology, the developed method is proposed for the optimization of the energy retrofit of an existing building. Furthermore, the method can be applied also for new architectures, by considering reference buildings. [ABSTRACT FROM AUTHOR]

Retrofitting of existing buildings offers significant opportunities for improving occupants’ comfort and well-being, reducing global energy consumption and greenhouse gas emissions. This is being considered as one of the main approaches to achieve sustainability in the built environment at relatively low cost and high uptake rates. Although a wide range of retrofit technologies is readily available, methods to identify the most suitable set of retrofit actions for particular projects are still a major technical and methodological challenge. This paper presents a multi-objective optimization model using genetic algorithm (GA) and artificial neural network (ANN) to quantitatively assess technology choices in a building retrofit project. This model combines the rapidity of evaluation of ANNs with the optimization power of GAs. A school building is used as a case study to demonstrate the practicability of the proposed approach and highlight potential problems that may arise. The study starts with the individual optimization of objective functions focusing on building's characteristics and performance: energy consumption, retrofit cost, and thermal discomfort hours. Then a multi-objective optimization model is developed to study the interaction between these conflicting objectives and assess their trade-offs. [ABSTRACT FROM AUTHOR]

Abstract: This paper aims to explore how and where phase change materials (PCMs) are used in passive latent heat thermal energy storage (LHTES) systems, and to present an overview of how these construction solutions are related to building''s energy performance. A survey on research trends are firstly presented followed by the discussion of some physical and theoretical considerations about the building and the potential of integrating PCMs in construction elements. The different types of PCMs and main criteria that govern their selection are reviewed, as well as the main methods to measure PCMs’ thermal properties, and the techniques to incorporate PCMs into building elements. The numerical modeling of heat transfer with phase-change and heat transfer enhanced techniques are discussed, followed by a review of several passive LHTES systems with PCMs. Studies on dynamic simulation of energy in buildings (DSEB) incorporating PCMs are reviewed, mainly those supported by EnergyPlus, ESP-r and TRNSYS software tools. Lifecycle assessments, both environmental and economic are discussed. This review shows that passive construction solutions with PCMs provide the potential for reducing energy consumption for heating and cooling due to the load reduction/shifting, and for increasing indoor thermal comfort due to the reduced indoor temperature fluctuations. [Copyright &y& Elsevier]

Abstract: This paper investigates design features that can potentially reduce the energy consumed in attaining appropriate thermal comfort levels in typical residential buildings. A numerical model coupled with a PID controller is developed to predict the indoor air temperature that is adjusted via mechanical ventilation. The model is used to simulate and evaluate various scenarios of building wall layouts and materials. From the various simulation runs, the wall configurations and materials were refined to combinations that rendered the mechanical ventilation a feasible option for attainment of comfort for the largest number of hours per year. The runs were conducted for a typical residential apartment located in the city of Beirut, Lebanon, which is characterized by mild coastal climatic conditions. Different wall configurations were assumed for each of the living zone and the bedroom zone of the apartment. The simulation results suggest an optimal wall configuration comprised of a 5cm layer of insulating strawboard sandwiched between a 2cm×10cm wall made of masonry units consisting of Hempcrete (mixture of Portland cement, aggregates, and industrial hemp fibers) for the living zone, whereas the wall for the bedroom zone consists of a 10cm of Hempcrete. [Copyright &y& Elsevier]

• The method is based on the bidimensional temperature matrix. • Temperatures were captured using infrared thermography. • Firstly, a distortion comparison due to the measurement surface was done. • The temperature measurements were done using a non-continuous surface. • The measuring error was reduced a 42% by using the non-continuous surface. The energy consumption in buildings is still very high despite its reduction in recent years. Buildings' conditioning is the main cause of this energy consumption and, in this sense, air infiltration has a great impact. The control of air infiltration is essential to achieve thermal comfort and energy efficiency. The evaluation of the global airtightness of the building envelope based on pressurization tests has been broadly used to determine the airtightness of buildings, but it cannot define the shape of air leakages. The use of thermography in combination with pressurization tools could be very useful. This paper presents the laboratory experimental measurements to obtain a three-dimensional definition of the air temperature when passing through a controlled envelope gap. The method is based on the bidimensional temperature matrix, captured by infrared (IR) thermography, that the air leakeage produces close to the gap, and depending on the configuration of the air inlet and airflow. The temperature measurement was done using a non-continuous rendering surface in order to avoid the Coanda effect that opaque surfaces cause, achieving in this way a 42% increase in the measuring accuracy. [ABSTRACT FROM AUTHOR]