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With the goal to reach net zero carbon emission, countries around the world are expected to switch from fossil fuel to more eco-friendly alternatives. This suggests that heating, transport, and energy sectors will be more dependent on electricity. Heat pump technology is expected to be the most common and clean technology to be used for heating in buildings due to its Coefficient of Performance. Air-source heat pumps are the most common type due to their ease of installation. This paper investigates how different climates around the world would affect the air-source heat pump electricity consumption and its defrost cycles; and hence the potential overall effect on the grid. A novel heat pump simulation model has been developed to understand the behaviour of the heat pump in cold weather scenarios. An experimental validation has been implemented to ensure the accuracy of the simulation model. Global case studies of cities from around the world including Amsterdam, Copenhagen, Helsinki, Stockholm, Vancouver, Ruse, Moscow, Reykjavik, Harbin and Nottingham are selected to assess the defrost cycles of air source heat pumps. The innovation of this research is in the in-depth investigation of heat pump defrost cycles. Electrifying the heating sector is expected to increase electricity consumption significantly, especially in cold weather. A detailed case study of the UK is presented with heat pumps and the examination of the impact this would have on the electricity grid is presented. Heating demands for buildings in cold weather was also simulated to calculate the required heating demand. The results show that the wide implementation of heat pumps in the UK, for example, would increase the total daily demand of electricity by approximately 144% relative to the present level of grid energy demand. In addition, the average daily energy consumption would increase by roughly 106% over the cold season. The findings are critical, and the novel methodology is applicable to many countries on global level in relation to the future effect of heat pumps on the grid and predicting the power demand needed by the additional heat pumps based on geographical location, u-values of building elements, and heating demand. It is crucial for a household to improve the insulation of their dwelling as this could considerably reduce the power demand by the heat pump and therefore the overall electricity consumption. This paper aims to inform future technology developers and policy makers regarding the expected effect of heat pump technology on the grid and the possible sudden peaks in demand. [ABSTRACT FROM AUTHOR]

Abstract The current rollout of smart meters for gas and electricity, both in the UK and internationally, will help suppliers to better forecast demand and supply accurate bills to consumers. However, even with an in-home display (IHD), the benefits of a smart meter to a domestic customer are limited by the so-called 'double invisibility' of energy [1] and the standardisation of IHD design for an imagined home 'micro-resource manager' [2]. Furthermore, low-income households may be limited in the benefits they can reap from such systems; already living within a tight budget, suggestions for further energy-related cost savings may be detrimental to their health and wellbeing. This makes it important that the impact of actions taken to save energy is communicated. This can be done using indoor environmental measures, including carbon dioxide, relative humidity and temperature, as part of an integrated meter and sensor system (IMSS) and an associated IHD or digital application. Such a system gives users the ability to make informed decisions about their energy use and indoor environmental health. This paper explores the potential barriers to implementing an IMSS in practice. It explains how an IMSS was designed, based on a review of meter and sensor systems; details the process is taken to trial the IMSS in 19 social housing properties in the English Midlands; and makes recommendations for a larger scale rollout of IMSSs. The paper also reviews current progress in cloud storage and security as relevant to IMSSs and smart metering. [ABSTRACT FROM AUTHOR]

Highlights • To design building's controls and setup strategies for personal behaviours, factors related to behaviours are studied. • Adaptive behaviours can create balance between indoor quality, comfort and energy use (ICE factors). • A design framework is proposed to facilitate environmental and personal adaptive behaviours. Abstract Adaptive behaviour has a significant impact on the quality of indoor environment, comfort, and energy consumption. Therefore, facilitating positive occupant behaviours will improve these three factors. The aim of this paper is to develop a design framework that can be used as part of the design process to facilitate adaptive behaviours. This paper reviews studies that focus on reasons behind adaptive behaviours, and implication of these adaptive behaviours on the built environment. This paper highlights that 'Context', 'Occupant', and 'Building' (COB) have the most influence on adaptive behaviours. However, in most cases their influence is not considered holistically. This study also illustrates that adaptive behaviour has implications for the quality of Indoor environment, level of Comfort, and Energy consumption (ICE). This paper introduces a framework consisting of three stages: (1) Evaluate the relation between COB and ICE factors with adaptive behaviours holistically; (2) Design building's controls for 'environmental behaviours', set-up strategies for 'personal behaviours', and find a balance between these two; 3) Monitor the performance of adaptive behaviours through Post Occupancy Evaluation (POE). [ABSTRACT FROM AUTHOR]

This paper presents and discusses data-driven predictive models for the energy use of appliances. Data used include measurements of temperature and humidity sensors from a wireless network, weather from a nearby airport station and recorded energy use of lighting fixtures. The paper discusses data filtering to remove non-predictive parameters and feature ranking. Four statistical models were trained with repeated cross validation and evaluated in a testing set: (a) multiple linear regression, (b) support vector machine with radial kernel, (c) random forest and (d) gradient boosting machines (GBM). The best model (GBM) was able to explain 97% of the variance ( R 2 ) in the training set and with 57% in the testing set when using all the predictors. From the wireless network, the data from the kitchen, laundry and living room were ranked the highest in importance for the energy prediction. The prediction models with only the weather data, selected the atmospheric pressure (which is correlated to wind speed) as the most relevant weather data variable in the prediction. Therefore, atmospheric pressure may be important to include in energy prediction models and for building performance modeling. [ABSTRACT FROM AUTHOR]

The carried scientific research regarding evaluation the hygrothermal effects of integration the vegetation into the building envelope was influenced with the differences in necessity to use air-conditioning in the houses, which are not surrounded with vegetation in horizontal structure and which have such vegetation during the summer time. The experimental testing is based on the precise measurements of the relative humidity and temperature, which were carried close to the building plaster in the place without influence of vegetation and between the wall and vegetation. Vegetation on the house, which was used for experimental purposes, is made up of the vine species with a thickness of 40 cm in the place where measurement was carried. Although the investigation takes longer, the paper aims to one month to show the summer time. The mathematical modelling of the obtained data was realized using the numerical as well as the statistical methods The paper aims especially on modelling the differences in relative humidity and temperature of the air and between the wall and vegetation. The dependence of temperature differences was expressed as a piecewise function using the method of Least squares of multiple regression as statistical method. Also the proportional energy to that which might be saved daily instead of its use for air-conditioning in the house was determined. The measurements as well as the used methods: showed sufficient accuracy. [ABSTRACT FROM AUTHOR]

This paper addresses the challenge of incorporating occupant behavior into building performance simulation models used during the design process—that is, before the actual occupants are known. It proposes the use of synthetic population data, an approach that is novel in building performance modeling although common in urban planning and public health. A simpler approach embodied in the ASHRAE Fundamentals volume is to report standard distributions of values for behavioral variables, assuming that parameters vary independently of one another when in fact many co-vary or are interdependent. An alternative approach calibrates models of occupant behavior against actual occupants in specific existing buildings, but this raises questions of transferability. Needed is a database of “generic” occupants that designers can use prospectively during the design process. This paper documents a process of combining disparate field studies of commercial buildings into a larger occupant behavior database and generating a statistically similar synthetic data set that can be shared without compromising confidentiality requirements associated with field studies. The synthetic data set successfully incorporates much of the covariance structure of the underlying field data and supports multivariate modeling. Its scope and structure necessarily serve the needs of the associated modeling framework. Cooperative and systematic sharing of data by field researchers is crucial for building large enough data sets to serve as a behaviorally-robust basis for building design. [ABSTRACT FROM AUTHOR]

Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO 2 emissions. The drive to reduce energy consumption and associated greenhouse gas emissions from buildings has acted as a catalyst in the increasing installation of meters and sensors for monitoring energy use and indoor environmental conditions in buildings. This paper reviews the state-of-the-art in building energy metering and environmental monitoring, including their social, economic, environmental and legislative drivers. The integration of meters and sensors with existing building energy management systems (BEMS) is critically appraised, especially with regard to communication technologies and protocols such as ModBus, M-Bus, Ethernet, Cellular, ZigBee, WiFi and BACnet. Findings suggest that energy metering is covered in existing policies and regulations in only a handful of countries. Most of the legislations and policies on energy metering in Europe are in response to the Energy Performance of Buildings Directive (EPBD), 2002/91/EC. However, recent developments in policy are pointing towards more stringent metering requirements in future, moving away from voluntary to mandatory compliance. With regards to metering equipment, significant developments have been made in the recent past on miniaturisation, accuracy, robustness, data storage, ability to connect using multiple communication protocols, and the integration with BEMS and the Cloud – resulting in a range of available solutions, selection of which can be challenging. Developments in communication technologies, in particular in low-power wireless such as ZigBee and Bluetooth LE (BLE), are enabling cost-effective machine to machine (M2M) and internet of things (IoT) implementation of sensor networks. Privacy and data protection, however, remain a concern for data aggregators and end-users. The standardization of network protocols and device functionalities remains an active area of research and development, especially due to the prevalence of many protocols in the BEMS industry. Available solutions often lack interoperability between hardware and software systems, resulting in vendor lock-in. The paper provides a comprehensive understanding of available technologies for energy metering and environmental monitoring; their drivers, advantages and limitations; factors affecting their selection and future directions of research and development – for use a reference, as well as for generating further interest in this expanding research area. [ABSTRACT FROM AUTHOR]

[Display omitted] • Unique preconditions, specific characteristics for use can be boundary conditions. • Energy use, users' behavior, lighting are correlated conditions within buildings. • Boundary conditions can help explain the occupants' behaviour and the use of spaces. • Knowledge of boundary conditions helps to understand how to design buildings. • Boundary conditions can be building/ user/ input-values and method-specific. This paper aims to review the boundary conditions (B/C) in specific categories (energy, building use, and lighting) within non-residential buildings to pave the way to a better understanding of users' requirements and needs of the built environment. For this paper, B/C are understood as unique preconditions, specific characteristics for use, determining specific features of buildings, enabling an accurate understanding of non-residential spaces concerning energy use, user behaviour, and lighting. This paper describes the results of an overall quantitative (1st method) review and a systematic review (2nd method) of boundary conditions and their factors within different types of non-residential buildings from the users' perception. Followed by a qualitative experts' literature review (3rd method) on B/C within offices, schools, and hospitals chosen by a team of international experts working together on Subtask A: User perspective and requirements, Task 61 IEA (International Energy Agency): Solutions for daylighting and electric lighting. The first review method led to the selection of 21 papers. The second method resulted in the selection of 7 papers out of 93,143 found in Scopus; during the 3rd review, experts collectively chose 74 additional papers focussing on the users' factors contributing to specific B/C. The scope of this paper is limited only to offices, schools, and hospitals. Based on the findings, the authors recognise a broad definition of boundary conditions from specific values, and conditions to interconnected factors, user profiles, functions of the building types, and operating hours. This paper is an overview of B/C factors found in the literature that can help explain the occupants' behaviour and the use of spaces. B/C are often type of building/user/location/situation/simulation input-values and method-specific. Therefore, they cannot be widely applicable but offer patterns and help to understand the correlations between various factors shaping the built environment. A better comprehension of the reasons for identifying B/C and their factors can help in developing a deeper knowledge of how we use buildings to find optimal ways to design them. [ABSTRACT FROM AUTHOR]

This paper presents the development, evaluation and application of a spatially referenced domestic building level framework (i.e. address level) to estimate domestic energy end-use demand baseline in sub-city areas. The paper core idea and conclusion is that unless knowledge and model estimating is available at an appropriate level, future UK local energy infrastructure planning will not be effective. Our framework innovatively combines a dataset, which includes detailed building surveys of 60,977 out of a total of 139,257 dwellings, with a normalised national dataset (i.e. the English Housing Survey) and applied to a BRE Domestic Energy Model (i.e. Cambridge Housing Model) so as to establish an energy consumption baseline for the domestic stock in localised areas of Newcastle upon Tyne. Our validation results show a poor alignment with existing observed data as published by the Department of Energy and Climate Change (DECC), particularly at neighbourhood scale. Our belief is that as spatial resolution is increased, local building and urban socio-economic and physical characteristics play a more important part in the estimation of dwelling energy consumption. Thus, we propose a taxonomy to holistically deal with the sources of uncertainty arising from these issues and the components of our framework. [ABSTRACT FROM AUTHOR]

[Display omitted] • Implementation of a Hardware-Based BB-BC Optimized Controller with Fractional-Order for a HVAC System. • An FPGA implementation of a fractional order proportional-integral-derivative controller for an HVAC system. • Adoption of the BB-BC algorithm for optimal tuning of the controller parameters. • Use of a second-order plus time delay model to represent the HVAC system. • Illustration of the effective tracking and rejection of disturbance signals by the FOPID controller based on the BB-BC algorithm. • High-performance pipelined implementation of the BB-BC algorithm and FOPID controller on a Xilinx FPGA device. Industrial and commercial buildings are significant energy consumers, worldwide, emphasizing the need for effective control techniques to reduce power consumption. This paper presents an FPGA implementation of a fractional order proportional-integral-derivative (FOPID) controller for a Heating, Ventilation and Air Conditioning (HVAC) system. The FOPID model enhanced improved dynamic performance and system robustness compared to classical PID controllers. However, tuning the FOPID controller is challenging due to the need to adjust several parameters, i.e., the proportional, integral, and derivative gains of the PID model, as well as the fractional differential and integral orders. To address this, the Big Bang-Big Crunch (BB-BC) evolutionary algorithm is adopted to tune the controller parameters optimally. The BB-BC algorithm is executed to minimize six different performance indices. The HVAC system is represented by a second-order plus time delay (SOPTD) model, yielding six different cases are obtained by combining three delay values and two gain values. A high-performance pipelined implementation of the BB-BC algorithm andthe FOPID controller is designed and realized on a Xilinx FPGA device. The implementation has successfully reduced the oscillations of the HVAC output signal by employing auto-tuning of control parameters based on BB-BC, while improved results have been also achieved in terms of rapid convergence. Additionally, a substantial reduction of 80 % in the output control signal and 73 % in error has been observed when using a window size (L) of L = 256, in comparison to L = 32. The simulation results demonstrate the highly efficient performance of the FOPID-BB-BC control unit after optimal tuning. [ABSTRACT FROM AUTHOR]

In response to the increasing demand for thermal comfort and the rising trend of building energy consumption in the hot summer and cold winter (HSCW) zone of China, there is an urgent need to implement higher standards of energy retrofit programs for existing residentials. Practical strategies and technical solutions still need to be improved in China. The Passive House standard (and its EnerPHit standard) aims to achieve ultra-low operational energy consumption through passive strategies. However, studies and examples of passive houses and low-energy buildings are rare in hot climates, especially in the HSCW zone of China. This paper presents the representative of the existing residential in Guilin, China. Simulation modeling through DesignBuilder and a sensitivity analysis were performed to conclude that airtightness, envelope, glazing type, and roof are the most critical factors affecting the energy consumption of the building. Furthermore, the combined solution was validated by optimizing the different retrofit parameters, resulting in a model that meets the energy objectives. The feasibility of the combined solution was also analyzed from the energy, economic, and thermal comfort points of view. Ultimately, the optimal solution that meets the objectives is obtained through a multi-criteria decision making (MCDM) approach for a more sustainable building. The methodology and results of this study provide an effective decision-making process for designing and evaluating energy retrofits for typical residential buildings in the HSCW zone, as well as a rigorous basis for policymakers to update the design codes for retrofitting buildings in HSCW zone. [ABSTRACT FROM AUTHOR]

Energy consumption and air quality index (AQI) prediction is important for efficient heating, ventilation, and air conditioning (HVAC) system operation and management. A data-mining approach is presented in this paper for modeling and short-term prediction of the complicated non-linear system. The multilayer perceptron (MLP) ensemble performs best among the data mining algorithms discussed in this paper. A clustering-based method from preprocessing input data to construct the prediction models is proposed to decreases the prediction errors and the computational cost. The effectiveness of the proposed method is validated through a practical case study with both modeling and short-term prediction. The analytical results showed that the method was capable of reducing the prediction errors for modeling and short-term prediction by 11.05% and 12.21%, respectively, comparing with the models built without clustering method. [ABSTRACT FROM AUTHOR]

This paper investigates factors associated with variation in daily total (electricity and gas) energy consumption in domestic buildings using linked pre-COVID-19 smart meter, weather, building thermal characteristics, and socio-technical survey data covering appliance ownership, demographics, behaviours, and attitudes for two nested sub-samples of 1418 and 682 British households selected from the Smart Energy Research Laboratory (SERL) Observatory panel. Linear mixed effects modelling resulted in adjusted R2 between 63% and 80% depending on sample size and combinations of contextual data used. Increased daily energy consumption was significantly associated (p -value < 0.05, VIF < 5) with: households living in buildings with more rooms and bedrooms, that are older, more detached, have air-conditioning, and experience colder (more heating degree days) or less sunny weather; households with more adult occupants, more children, older adult occupants, higher heating temperature setpoints, and that do not try to save energy. The results demonstrate the value of smart meter data linked with contextual data for improving understanding of energy demand in British housing. Accredited UK researchers are invited to apply to access the data, which has recently been updated to include over 13,000 households from across Great Britain. This paper provides guidance on appropriate methods to use when analysing the data. [ABSTRACT FROM AUTHOR]

Abstract Measuring and tracking building energy use and other data is essential for cities, utilities, and service providers. Currently, buildings are conceived as "places/locations" and therefore are identified with a street address or with a single geographic coordinate point (latitude and longitude). However, the address-based system is insufficient to uniquely identify buildings, and to append and join data from disparate sources due to address name duplicates, incorrect entries, and lack of an input format standard. As a result, essential building energy data for energy efficiency policy decision making is difficult to leverage. The Unique Building Identifier (UBID) was developed as a natural key to match building energy and attribute data between databases and to facilitate matching across datasets. Our methodology converts a two-dimensional building footprint into a unique alphanumeric code based on an open source grid reference system. The UBID is designed to be easily overlaid on publicly available, web-based mapping platforms and enable fast and accurate spatial matching with minimal computational resources. In this paper, we present the UBID methodology, discuss the use cases in energy efficiency, and present the results of tests in three major US cities (San Francisco, Chicago, and New York City) to verify the uniqueness and effectiveness of the proposed building identifier. [ABSTRACT FROM AUTHOR]

Abstract Social housing providers have recently emerged as unlikely innovators of low carbon transitions in the UK residential sector. They tend to have a significant amount of influence over large housing stocks, opportunities to access funding to retrofit on a large scale, can make explicit connections between reduced carbon emissions and improved quality of life for low-income residents, and foster a close relationship with the place and communities they serve. In effect, social housing providers are 'middle actors' who not only facilitate but also realise low carbon transitions through various strategies. This paper uses empirical findings from interviews with social housing providers in Greater Manchester to understand the different ways that low carbon and energy efficiency innovation is being undertaken in this sector. The findings reveal that as middle actors, social landlords influence upstream to policy makers and regulators, downstream to individual households, and sideways to other actors in the social housing sector as well as to other building and energy professionals. The findings reveal opportunities for governments to supplement their existing policies with recognising and supporting middle actors to accelerate low carbon transitions of the built environment. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the influence of building fabric, services and occupant related factors on actual energy use of six case study dwellings, located in three new low energy social housing developments in UK, covering a variety of built forms and construction systems (timber frame, hempcrete, steel-frame). Physical monitoring of indoor environment and window-opening is cross-related with building fabric and systems’ performance, and qualitative data gathered through occupant surveys, review of control interfaces and handover guidance, to understand the causes of the gap between modelled and measured energy use. Actual energy use is found to exceed design expectations by a factor of three, questioning the need for whole-house mechanical ventilation heat recovery (MVHR) systems at measured air permeability rates of 6 m³/(h.m²) against the design target of 3 m³/(h.m²). Lack of proper commissioning of MVHR and heating systems, combined with inadequate user comprehension about their operation and control leads to occupant ‘misuse’ wherein systems are de-activated, thereby negatively affecting indoor air quality. This is confounded by occupant factors related to higher demand temperatures, unexpected opening of windows during winters due to under-performance of MVHR combined with habitual behaviours, and over-use of heating systems to compensate for higher than expected air permeability. [ABSTRACT FROM AUTHOR]

This paper presents a two year long empirical study on the effects of fabric retrofit insulation on a high rise social housing building (a 23-storey block with 157 flats) in Newcastle upon Tyne (UK). The study has followed a quasi-experimental approach coupled with qualitative methods and examines whether temperature take-back is taking place; whether it operates independently of socio economic characteristics due to saturation effects; and the relationship between temperature take-back, physical factors and occupant’s behavioural change. The presented empirical evidence suggests that, first, temperature take-back as extra warmth (or energy consumption savings) is not occurring. Second, the saturation effect has taken place. This supports the assumption that temperature take-back decreases owing to saturation effects when pre-intervention internal temperatures saturate (approaching 21 °C) in lieu of the hypothesis that low-income householders take the benefits of an energy efficiency intervention as extra warmth rather than energy savings. Third, an upper level or maximum take-back temperature was achieved for the dwellings ranging from 20.85 °C to 24.81 °C. Fourth, behavioural factors such as turning on the heating appear to be less relevant than physical factors such as energy-efficiency improvements to explain the increased of standardised mean internal air temperature. The study also suggests that local building characteristics (e.g. heating pipes routing) play an influential role and that to evaluate appropriateness of retrofitted energy-efficiency insulation measures pre-intervention variables such as internal temperatures, heating system and building fabric performance should be taken into account. [ABSTRACT FROM AUTHOR]

This paper presents a two-step approach to forecasting city-wide building energy demand. The initial engineering estimates with input from typical buildings are used as the priori beliefs, and are transformed into the posteriori distributions that describe energy consumption patterns of plots. This two-step approach takes advantage of the engineering estimate in analysis of physical factors that determine building energy consumption and uses demand regression to further correct the priori engineering estimates based on the observed energy consumption of plots. The results of a case study shows that the two-step approach makes the standard deviation of the predicting factors within 0.001 kWh/(m 2 ·a) compared with 6.186 kWh/(m 2 ·a) of the engineering estimate or 53.020 kWh/(m 2 ·a) of the demand regression. It means that the bottom-up two-step approach has a high confidence in forecasting the city-wide building energy demand if the priori engineering estimates are critically accepted and Bayesian analysis is performed according to the observed energy consumption of plots. It is a general methodology and can be applied in most cities to forecast the city-wide building energy demand aiming to enable policymakers to establish the medium or long-term targets related to buildings stock energy consumption and associated CO2 emissions. [ABSTRACT FROM AUTHOR]

External movable shading devices are mainly used to improve the thermal and lighting environment of an interior space by preventing overheating during the cooling season as well as by preventing glare. An external movable shading device can be controlled using various methods, where parameters related to the lighting environment, such as daylighting and glare, are commonly adopted as major variables associated with the control of the shading device. In this paper, an algorithm is provided with which an external movable shading device can be operated in any one of three control modes as selected according to the operation purpose preferred by the occupant. The algorithm can be applied to external movable shading devices of various shapes. The shaded fraction is adopted as a major control element, and the control purpose of the external shading device is configured to include energy conservation, illuminance satisfaction, and glare protection. The algorithm includes an hourly evaluation procedure for obtaining the range of allowable shading device movement that satisfies each of the three operation purposes. Real-scale mockup tests for the three control modes were conducted during different time periods in summer to verify the performance of the control strategies. The test results regarding the energy and environment performance for each control mode show that the control algorithm can be selected to provide satisfactory compromises between energy and visual comfort factors. The result of this study can provide users with options for controlling movable shading devices on a building according to their preferred operation purposes. [ABSTRACT FROM AUTHOR]

The energy used for cooling has increased in recent decades and the predicted future rise in consumption is driving a pressing need for more efficient technologies. Some technologies use environmental sinks as heat dissipation alternatives. This paper presents a model validation with experimental data from a passive vertical cooling panel. The novelty of the solution lies in two main characteristics. The first is that the panel is in a vertical position, and thus the heat sink is the ambient temperature and surrounding instead of the sky temperature. The second is that the panel is north-oriented. Avoiding the sun lengthens the operating time to the entire day, while most studies explore options that are limited to night radiation. The aim is to include this element as a heat exchanger before water moves into the cooling tower from the condenser stage in cooling systems. The results have shown that the model approaches significantly the experimental data with an average error of 1.5% in the dissipated heat. Besides, the cooling capacity of the panel varies from 107 to 230 W/m 2 depending on the inlet temperature and fluid flow conditions, confirming the viability of the integration in buildings. [ABSTRACT FROM AUTHOR]

Egyptian electricity demands have increased in recent years and are projected to grow further with significant economic and social impacts. Recently, mandatory and voluntary building codes based on international standards have been increasingly adopted. The performance of existing Egyptian buildings is not well understood making the impact of these new codes uncertain. This paper aims to provide insights into existing Egyptian building performance, and elaborate a process for developing a representative model to assist in future policy. The work presented is for office buildings but intended to be widely replicable. An energy survey was carried out for 59 Egyptian offices, categorised by building service type, it was observed that energy use increases as building services increase, and existing Egyptian offices use less energy than benchmarks. A more detailed investigation for a case study office was carried out, to inform detailed model calibration. This provided insight into energy use, thermal comfort and environmental conditions, and revealed high variability in behaviours. A calibrated model was created for the case study office, then a baseline model and input parameter sets created to represent generalised performance. Future uses including assessment of the impact of codes are discussed, and further replication potentials highlighted. [ABSTRACT FROM AUTHOR]

Air conditioning (AC) systems are responsible for the major percentage of energy consumption in buildings. Shared spaces constitute considerable office space area, in which most office employees perform their meetings and daily tasks, and therefore the ACs in these areas have significant impact on the energy usage of the entire office building. The cost of this energy consumption, however, is not paid by the shared space users, and the AC's temperature set-point is not determined based on the users’ preferences. This latter factor is compounded by the fact that different people may have different choices of temperature set-points and sensitivities to change of temperature. Therefore, it is a challenging task to design an office policy to decide on a particular set-point based on such a diverse preference set. As a consequence, users are not aware of the energy consumption in shared spaces, which may potentially increase the energy wastage and related cost of office buildings. In this context, this paper proposes an energy policy for an office shared space by exploiting an established temperature control mechanism. In particular, we choose meeting rooms in an office building as the test case and design a policy according to which each user of the room can give a preference on the temperature set-point and is “paid” for feeling discomfort if the set-point is not fixed according to the given preference. On the other hand, users who enjoy the thermal comfort compensate the other users of the room. Thus, the policy enables the users to be cognizant and responsible for the “payment” on the energy consumption of the office space they are sharing, and at the same time ensures that the users are satisfied either via thermal comfort or through incentives. The policy is also shown to be beneficial for building management. Through experiment based case studies, we show the effectiveness of the proposed policy. [ABSTRACT FROM AUTHOR]

This paper reports on the building performance monitoring and annual energy demand of two homes built side-by-side over an occupancy period of three years. The study compares the results from on-site monitoring against the assumed parameters and calculations from compliance modelling at design stage. It focuses on the differences and impact of occupancy behaviour, weather conditions, quality of construction and operation which contribute to an increase in energy consumption creating a gap in performance between design and actual. The results from the study show disparities in the fabric performance reflecting on the overall consumption of energy. This longitudinal analysis highlights how building performance needs to be evaluated over longer periods in order to fully understand how homes and their occupants operate and consume energy. The impact of the real performance of homes in Scotland over longer periods needs to become standardised, and a mechanism for feedback into regulatory mechanisms and construction practices applied, if carbon emission targets are to be met. [ABSTRACT FROM AUTHOR]

In this study, a solar based Rankine cycle and geothermal based system for multigeneration is designed and developed. It consists of a Rankine cycle with reheating for power generation, an absorption chiller cycle for cooling, a drying process to dry wet products, useful heat from the condenser of the Rankine cycle, and other useful heat out from heat exchangers. The overall energy and exergy efficiencies of the single generation and multigeneration systems are studied, and it is observed that the energy efficiency of the multigeneration system is higher than the single generation system. The energy efficiency of the single and multigeneration systems are 7% and 37%, respectively. Similarly, the overall exergy efficiencies for the single generation and multigeneration systems are also studied and presented in this paper. In addition to this, parametric studies are performed to observe the effects of different substantial parameters, namely inlet pressure and temperature of the turbine, and reference environment temperature in order to investigate the variations in the system performance in terms of the energy and exergy efficiencies. [ABSTRACT FROM AUTHOR]

Several building-stock modelling techniques have been employed to investigate the impact of energy efficiency measures (EEM), where the description of the building-stock generally consists of an age-type classification to specify building characteristics for groups of buildings. Such descriptions lack the appropriate level of detail to differentiate the potential for EEM within age groups. This paper proposes a methodology for building-stock description using building-specific data and measured energy use to augment an age-type building-stock classification. By integrating building characteristics from energy performance certificates, measured energy use and envelope areas from a 2.5D GIS model, the building-stock description reflects the heterogeneity of the building-stock. The proposed method is validated using a local building portfolio (N = 433) in the city of Gothenburg, where modelled results for space heating and domestic hot water are compared to data from measurements, both on an individual building level and for the entire portfolio. Calculated energy use based on the building-stock description of the portfolio differ less than 3% from measured values, with 42% of the individual buildings being within a 20% margin of measured energy use indicating further work is needed to reduce or quantify the uncertainty on a building level. [ABSTRACT FROM AUTHOR]

Solar energy is a hygienic, generous and easily available renewable energy. Usage of solar energy in different kinds of photovoltaic systems provides scope for several researches on exergy studies. In this paper, a detailed review on energy and exergy analysis of building integrated photovoltaic module to evaluate the electrical performance, exergy destruction and exergy efficiency with photonic method has been discussed. The wavelength of visible spectrum plays an important role on the exergy efficiency characteristics. Both the photonic energy method and parametric methods are needed to obtain a deep correlation between climatic and operating parameter. Finally other possibility to optimize and increase the building integrated photovoltaic module performance can be found. [ABSTRACT FROM AUTHOR]

This study presents a simple heat transfer methodology for box double skin façade. There are a number of numerical methods described in different papers, but at local and European level it is a lack of standards or unique methodologies regarding this system. The methodology presented is an extended and corrected version of a heat transfer method through a double-glazed window described by Oosthuizen and Naylor in [1] . The box double skin façade consist of an internal double pane window and a 10 mm secure glass as double skin. The methodology incorporates heat transfer by conduction and convection, considering two extreme climatic conditions for exterior temperature. The main purpose of this study is to identify the difference between single-skin façade and double skin façade from heat transfer point of view. For this purpose were taken into account and calculated face temperatures, total thermal resistances, transmittances and heat fluxes. Analyze of the heat transfer indicators were described by tabular values and by one year chart for Braşov region, in Romania. For a faster calculation some second degree polynomial equations are proposed, for finding thermal conductivity, thermal diffusivity and kinematic viscosity as a temperature function. For each property it was found one equation for air and one for argon. Argon and air are the most common gases included in window systems. Overall, the study shows an increase in envelope insulation with greatest benefits during the cold season. [ABSTRACT FROM AUTHOR]

The modeling and simulation of domestic hot water systems, including solar thermal and co-generation technologies, relies on accurate, high time-step resolution water consumption profiles. Due to the expensive nature of field studies, previous profiles have been limited in number of participants, or have been generated synthetically using probabilistic modelling techniques. The Solar City program in Halifax has measured hot water flow rate and temperature data in 119 homes at a time-step of 1 min; and includes a survey of occupancy rates and other relevant meta-data. In this paper, we discuss the data acquisition and processing (with a focus on flow rate data), and conduct analysis to reveal consumption trends and produce a new set of time-step profiles for modeling and simulation. Average hot water consumption per household is 172 L/day with a strong dependency on number of occupants. The hourly profile peaks twice daily, and shifts by several hours on Sunday. The average draw temperature was found to be 51.8 °C, which is lower than the default value of 55 °C applied by many building modeling/simulation packages. The average cold water supply temperature was found to be roughly sinusoidal about 12.4 °C with approximately one-month lag compared to ambient air temperature. [ABSTRACT FROM AUTHOR]

Mechanical ventilation systems have a significant influence on the energy demand of buildings. The Government's aim is to reduce the energy demand for mechanical ventilation by 2020. Therefore, energy efficient mechanical ventilation systems are required. Using dampers to balance the ventilation system, the centralised fan must provide sufficient static pressure to overcome the maximum pressure drop in the system. This means that there will be excess pressure in parts of the duct system. Using decentralised fans instead of dampers, the excess pressure can be eliminated as each fan provides the pressure needed for that particular part of the duct system. In duct systems in conventional supply ventilation systems, there is a positive static pressure compared with the pressure inside the building. Using decentralised fans, parts of the duct system will have a negative pressure and room air may enter the duct system and spread to other parts of the building. In this paper, the possibility of reversed airflow was investigated. An evaluation of reversed airflow was implemented both theoretically and experimentally. With the objective of simulating a malfunctioning, one integrated fan did not operate during the investigations while the others did. When a manifold was used to distribute the pressure, the reversed airflow was eliminated. This was due to the positive pressure in the manifold that was maintained by the main fan. When the ventilation system was a regular supply duct system with a main fan and a main duct with branches, then there was a possibility of reversed airflow if a fan malfunctioned. [ABSTRACT FROM AUTHOR]

In practice, monthly temperature records play a major role calculating the heating and cooling degree-days of the air conditioner management in buildings. Classically, heating and cooling degree calculations are based on the comparison of outdoor temperature measurements with a standard level called the base temperature. Truncating the temperature series at a constant base temperature causes heating (deficits) and cooling (surpluses) degrees. Since outdoor temperature records are of random character, future predictions with probabilistic and statistical methods are convenient means for calculations. All previous methodologies in the literature are based on crisp logic with simple mathematical calculations. This paper proposes a new methodological approach by converting the actual temperature record probability distribution function (PDF) into a probabilistic standardized degree indicator (SDI) in normal (Gaussian) PDF form with zero mean and unit standard deviation. Furthermore, as a new evaluation methodology fuzzy logic inference calculations are provided. SDI is divided into seven classes, three for cooling, heating, and a single class for uncooled-unheated states. Heating and cooling degree changes according to SDI values are presented with crisp and fuzzy sets. The application of the methodology is made for Kadıköy urban area on the Asian side of Istanbul, Turkey. In the case of fuzzy set SDI air conditioned operation, it has been determined that there is cooling energy saving of approximately 25% compared to the crisp set. The same is true for the heating degree-day side. [ABSTRACT FROM AUTHOR]

Aquatic centres are popular recreational facilities in Australia and other developed countries. These buildings have experienced exponential demand over the past few decades. The growing desire for better indoor environmental quality in aquatic centres has resulted in a marked increase in energy consumption in this sector. With the existence of multiple user groups, achieving thermal comfort has always been challenging. Even though several thermal comfort studies are conducted in other building types, such studies are very limited with respect to aquatic centres. This paper analyses the thermal comfort conditions of various user groups in seven aquatic centres in Australia. Comfort measurements are performed through monitoring environmental parameters and surveying swimmers, staff and spectators. The results revealed the variation of air temperatures among the buildings, resulting in high level of thermal discomfort for the spectators and staff in some of the buildings. The thermal sensation of the staff and spectators had good correlation with the indoor temperatures and PMVs. Altering temperature settings according to the seasons will help to improve the comfort with respect to the adaptation and expectation of the occupants. [ABSTRACT FROM AUTHOR]

The construction sector has grown to have the second-highest energy consumption in China, smaller only than the industrial sector. The objective of this paper is to explore whether compactness is sustainable city form from aspects of urban household energy use carbon emission (UHEUCE). To eliminate social influence as much as possible, we designated a standard family whose social conditions represent the entire city average. Normalized compactness index, connectivity of green space (GS) and water bodies (WB), and accessibility to GS and WB by households were selected as quantitative indicators related to urban sprawl. These indicators were quantified using remote sensing and geophysical information system methods. Urban sprawl aspects of compactness were positively correlated with UHEUCE. The other urban sprawl form indicated by GS and WB connectivity had the same positive correlations with UHEUCE. The greater the GS and WB accessibility, the less UHEUCE. This indicates that designing cities to be compact with less accessibility to GS and WB may increase household energy consumption. Substantial use of GS and WB, even if they are fragmented, will reduce carbon emission from residential energy use. This study provides useful implication toward achieving scientific landscape plans for low carbon city construction. [ABSTRACT FROM AUTHOR]

The increase of complexity in school buildings to ensure for users comfort and social and functional demands are changing energy consumption patterns. In the Portuguese context, a recent rise in energy consumption, after a major national refurbishment programme, confirms the need to improve energy management in schools in order to reduce their environmental impact. Besides building design and systems, users are also a determining factor impacting energy consumption in buildings. However, behavioural issues are still among the areas least covered by scientific literature. The present paper analyses the energy consumption patterns of eight Portuguese case-study schools, with a methodological approach that integrates quantitative and qualitative data analysis. The approach made it possible to link the energy consumption patterns of the schools (selected as Key Performance Indicators) with the user behaviour and management strategies. As a result, six Key Performance Strategies (KPS) were identified so as potentially to enhance the energy performance of school buildings through use and management. Some of the identified KPS can be implemented directly through school management policies to reduce energy use and enhance efficiency. Others can be incorporated in future building design strategies. Some have the potential for being hereafter integrated into the simulation models of buildings’ energy performance. [ABSTRACT FROM AUTHOR]

The principal aim of our study is to investigate the contribution and/or the influence of Foreign Trade (FT), Foreign Direct Investment (FDI), and Financial Development (FD) on the Energy Consumption (EC)-Environmental Pollution (EP)-Economic Growth (EG) link for the Gulf Cooperation Council (GCC) over the period 1971–2019. To realize the study aim, we develop an augmented growth model to examine the long-run relationship between the mentioned variables by applying the Autoregressive Distributed Lag (ARDL) procedure and the Vector Error Correction Model (VECM) to capture direction causality. The empirical results suggest that the variables concerned are cointegrated. Further, the coefficients estimated are mixed across countries. In the long-run, EC, FT (except Kuwait), and FDI (except Oman and KSA) are related to a rise in EG for all countries. Besides, the findings support that EC generates EG in the short-run for all GCC countries, implying economic expansion. Moreover, the major conclusion of this research paper has an impressive value for the policymakers to advance comprehensive trade, investment, financial, and energy policies that enable to achieve sustainable development. [ABSTRACT FROM AUTHOR]

This paper proposes a new method for an optimal control of the heating system at the building scale. This control is a new approach of energy planning that aims to decrease the heating consumption/expenses over a defined prediction horizon while respecting the occupants’ thermal comfort. It employs a simplified building thermal model to simulate the building thermal behavior taking into consideration the weather predictions. This approach is based on the application of Monte Carlo method, i.e., a random generator for the heating system scenarios. The aim is to determine the optimal heating plan for the prediction horizon that fulfills the constraints regarding the thermal comfort of occupants and the minimization of the energy consumption/expenses together with achieving a load shedding. [ABSTRACT FROM AUTHOR]

The use of software tools to aid building design, or to show compliance, is now commonplace. This has motivated investigations into the potential of optimisation algorithms, used in such software, to automatically optimise designs, or to generate a variety of near-optimal designs. Optimisation always requires the evaluation of a large number of possibilities, before a final selection is made. Normally when using a building simulator to assess the quality of designs, all possible solutions in the early stages of optimisation (when there is a high volume of choices) are evaluated using the same tool, so that the computational time for the assessment of each of the possibilities is the same as the time required for the final, refined choice of solutions. This paper suggests using a method of evaluation which changes as the algorithm evolves: whereas accuracy is initially compromised to improve the speed of the algorithm, the process is subsequently altered to produce a more accurate, evaluation process. This is a case of dynamic optimisation that requires an algorithm able to cope with changes in the objective landscape. A self-adaptive evolutionary strategy has been chosen, for its ability to “learn” about changes, and the influence of the different decision variables in the objective function as they arise. The results show that this method can reach the same optimal design, with substantially lower computational time than the optimisation methods found in the literature. [ABSTRACT FROM AUTHOR]

• Adobes and fired clay bricks with and without biomass bottom ashes replacement have been assessed. • Four types of infill walls have been modelled for each type of considered construction material. • One- and four-stories buildings have been modelled by incorporating such infill walls. • Residential and non-residential uses have been considered for calculations. • Mechanical response, energy behavior and CO 2 emissions have been assessed for each case. With the aim of both reducing environmental footprint and improving technological properties, several construction materials have been successfully manufactured using using waste. However, the assessment has commonly been based on comparing technological behaviors, while the overall assessment of the so made building has been commonly overlooked. Thus, this papers shows the energy and mechanical performance of buildings with same structure design, building shape and envelopes characteristics but with different types of infill walls (IWs) which have been modelled by considering traditional materials (i.e. adobe and perforated fired clay bricks) and eco-materials, such as adobe and bricks made by using up to 10% and 17.5% of biomass bottom ashes, respectively. Building models have been designed in accordance with building codes, in terms of seismic and energy savings criteria. In addition, residential (RB) and non-residential (NRB) uses have been also considered for calculations. IWs had in all cases similar equivalent thermal transmittance, achieved by varying the air gap length between layers in order to establish a common comparative framework. Otherwise, IWs showed a different thermal capacity depending on used material within the wall construction. The analysis concluded that the mechanical behavior was similar in all cases, regardless the excess of weight added by adobes. Besides, in low height buildings the increasing of stiffness possesses an advantage for lateral loads resistance. In addition, by using adobe with ashes, 5% of equivalent CO 2 footprint (i.e. from cradle to gate) and 4% of energy consumption may be saved. These savings must be even lower when the entire life cycle is considered, since adobes may be easily collected and reused without any treatments while fired clay bricks require further treatments. [ABSTRACT FROM AUTHOR]

• Data-centric methods include computational modelling, monitoring and statistics. • Dwelling retrofit research in North Western Europe has been dominated by energy efficiency. • More parameters in the home environment can be monitored, informing retrofit impacts. • Monitored data with agent-based modelling or property passports can inform retrofit practice. • Data on retrofit impact could increase the low retrofit rates (typically 0.4–1.2% per year). Data-centric innovation can inform the development of effective retrofit strategies through novel methods of collecting, analysing and sharing data. This bibliometric review uses a text-mining tool to identify research trends in dwelling retrofit research across North Western Europe. The review identifies a major focus on energy efficiency, with sub-themes on: 1) energy performance, 2) heat, power and control technologies, 3) indoor environment quality and 4) retrofit practice. In dwelling retrofit, there is now an established research tradition of using data-centric methods in monitoring and modelling energy performance to inform and learn from energy efficiency interventions. Building on the state-of-the-art, our analyses suggest opportunities for data-centric methods to consider the indoor environment quality and material impacts resulting from energy performance improvements. This information can then be openly communicated across the supply chain. Thus the paper discusses the retrofit themes and data-centric methods within North Western Europe, for an emerging trajectory of data-centric retrofit research and practice. [ABSTRACT FROM AUTHOR]

• The DSHP is a valid alternative to both the air and the ground source HP. • A significant reduction in the BHE length can be obtained by the DSHP. • The DSHP has a higher performance leading to a lower electric energy consumption. • The electric energy mix consumption during use plays a key role. Using all phases of a life cycle assessment (LCA), this paper analyses the environmental impact of a dual-source heat pump (DSHP) system that uses either the air or the ground as external heat sources. Data on the production were provided by the manufacturer of the heat pump prototype. The use phase was considered by evaluating the seasonal and annual energy performance of the system, using dynamic simulations. The system maintenance and end-of-life were modelled in accordance with the current regulations and statistical data in this sector. The Ecoinvent database was used as a reference for background data. The ReCiPe, CED and IPCC 100a impact methods were used to assess the environmental impact categories. The results were compared with those of conventional air and ground source heat pump systems. A sensitivity study on the influence of the energy in the use phase was carried out in terms of a variation in energy use and for different energy mixes, including photovoltaic energy. The results demonstrated the environmental validity of the technology in comparison with the two conventional heat pumps used for residential applications in different conditions. The results could be used by heat pump manufacturers to improve the design and performance of their products, by designers in the selection of thermal technologies, and by researchers involved in the study of similar emerging renewable energy technologies. [ABSTRACT FROM AUTHOR]

• Conduct a comprehensive review on the studies related to energy, thermal comfort and indoor air quality performance of underground buildings. • Reveal that numerical simulation is mostly used for energy study, while field experiment is primarily for indoor environment quality which need more attentions for underground buildings. • Finite difference method is the most adopted prediction method for underground building energy use in which the ground coupled heat transfer scheme requires further improvement. Underground spaces have received increasing attention in the past decades owing to the growing urban land scarcity. Underground spaces can have a variety of functions such as storage, shelter, and civic infrastructures, while underground buildings for human activities have gained less attention mostly due to the challenges in creating suitable living and working environments. With the attempt to design a healthy, comfortable and energy efficient underground building, this paper conducts a comprehensive review on the studies related to energy, thermal comfort and indoor air quality performances of underground buildings, ranging from prediction methods to influential factors to improving solutions. The review reveals that numerical simulation is mostly used to study underground building energy performance while field experimentation is primarily employed for investigating underground building indoor environment quality performance. Finite difference method is found to be the most adopted numerical method to predict the energy performance of underground buildings. Inherent uncertainty issues in ground coupled heat transfer still need to be improved to reflect more physics and balance prediction accuracy with computational cost. Further research is more necessary and crucial in the field of indoor environment quality performance than energy efficiency performance for underground buildings. [ABSTRACT FROM AUTHOR]

Buildings account for about 40% of total U.S. energy consumption and around a third of total energy-related CO 2 emissions. Concerns about these emissions have led federal, state, and local governments to pass policies to reduce energy use in buildings. In this paper, we examine whether policies aimed at encouraging green building certifications are associated with an increase in the gross floor area per capita of Leadership in Energy and Environmental Design (LEED) certifications. We focus specifically on commercial LEED building retrofits certified under - :existing buildings: operations and maintenance (EB), commercial interiors (CI), and core and shell (CS) rating system categories. Using a panel data approach, we find that metropolitan statistical areas (MSAs) with local policies, particularly requirement and density programs, are associated with significant increases in commercial LEED retrofits. Specifically, we find that the switch of an MSA from having no requirement policy to having a requirement policy is associated with an increase of 0.22 LEED sqft/capita [0.02 LEED sqm/capita] (compared to an average of 0.6 LEED sqft/capita [0.06sqm/capita] across all buildings in 2016). We also find that federal policies and improvements to the LEED rating system are associated with increases in LEED certifications. While the impacts of federal policy and LEED rating system updates are difficult to separate, our work suggests that local policy, federal policy, and modifications to the LEED rating system can work in concert to drive green building adoption. [ABSTRACT FROM AUTHOR]

Expert guidance in the UK suggests a limit to temperatures in bedrooms to of 26°C or less to avoid overheating. This short paper looks at the temperatures in bedrooms and uses data from comfort surveys combined with models which link comfort to the thermal environment. Evidence is given that people sleep comfortably where temperatures are 29–31°C in their personal space within the bed and they use bedclothes to allow them to attain these temperatures. The effect of the use of a mattress and the adaptive opportunities afforded by the bedclothes and sleepwear are briefly explored as are methods used in hot climates to offset high bedroom temperatures. [ABSTRACT FROM AUTHOR]

Energy efficiency in existing buildings, including historic buildings, is perhaps our greatest opportunity for a sustainable future. Energy efficiency retrofits in all existing structures must consider both long-term use and conservation. This paper focuses on ASHRAE's work in this area. [ABSTRACT FROM AUTHOR]