Search

This paper introduces a digital simulation workflow that calculates annual eye-level illuminance and energy demand from daylight and electric lighting sources for an array of view positions across 9-channels of spectral data. This Radiance-based workflow combines parts of the LARK spectral lighting code to offer better spectral resolution and accuracy when computing melanopic lx to evaluate the non-visual health potential for view positions within a digital model. The authors have implemented a series of annual climate-driven simulations and post-processed time-series of resulting data using the R statistical analysis software to compute Equivalent Melanopic Lux (EML) and energy demand (kWh) for an array of view positions and view directions in a digital model. This allows us to compute the energy demand of a given lighting and shading control scenario, which is optimized by hourly daylight availability to meet a recommended level of melanopic lx. This combined workflow uses digital models of an interior space to evaluate the annual potential of non-visual light exposure under different architectural, lighting, and shading control scenarios. This paper demonstrate the utility of this workflow by evaluating a luminaire-level lighting controls (LLLC) system to meet eye-level light exposure recommendations from the WELL Building Institute Feature L03 Circadian Lighting Design and compare the energy demand between targeted melanopic lux thresholds and shading control scenarios. [ABSTRACT FROM AUTHOR]

The use of Phase Change Materials (PCM) in different building applications is a hot topic in today's R&D activities. Numerical simulations of PCM-based components are often used both for research activities and as a design tool, although present-day codes for building performance simulation (BPS) present some shortcomings that limit their reliability. One of these limitations is the limited possibility of replicating the effects given by thermal hysteresis – a characteristic of several PCMs. In this paper, an original algorithm that allows hysteresis effects to be accounted for is described and the results from simulations are compared against experimental data. The algorithm is implemented in EnergyPlus™ and makes use of the Energy Management System (EMS) group, one of the high-level control methods available in EnergyPlus™. The algorithm enables the replication of PCM's different heating/cooling enthalpy curves in this BPS tool, which just recently was equipped with an integrated module for the replication of the effects of thermal hysteresis. A comparison between numerical results from the proposed model and from other methods implemented in BPS tools, and the experimental data provided, shows the impact of the algorithm in the simulation of heat transfer in a PCM layer intent for opaque walls. In general, it is shown that the proposed method presents a better agreement with experimental data than alternative modelling approaches, but it is also seen that all the tested numerical models are not fully able to replicating the behaviour of PCM layers if the PCM does not melt or resolidify completely (i.e. it remains in the phase change) during the charge/discharge cycle. A local sensitivity analysis complements this study and highlights the most relevant parameters that influence the results of a simulation carried out with the proposed model. Finally, the paper hypothesises that the general discrepancy between simulations and experimental data seen in the case of incomplete melting of the PCM layer can be due to unsuitable data for the thermophysical behaviour of the PCM, which are obtained through conventional characterisation procedures far from the physics of the PCM layer when in real building structures. [ABSTRACT FROM AUTHOR]

This paper provides practical guidelines to the Bayesian calibration of building energy models using the probabilistic programming language Stan. While previous studies showed the applicability of the calibration method to building simulation, its practicality is still impeded by its complexity and the need to specify a whole range of information due to its Bayesian nature. We ease the reader into the practical application of Bayesian calibration to building energy models by providing the corresponding code and user guidelines with this paper. Using a case study, we demonstrate the application of Kennedy and O’Hagan’s (KOH) [1] Bayesian calibration framework to an EnergyPlus whole building energy model. The case study is used to analyze the sensitivity of the posterior distributions to the number of calibration parameters. The study also looks into the influence of prior specification on the resulting (1) posterior distributions; (2) calibrated predictions; and (3) model inadequacy that is revealed by a discrepancy between the observed data and the model predictions. Results from the case study suggest that over-parameterization can result in a significant loss of posterior precision. Additionally, using strong prior information for the calibration parameters may dominate any influence from the data leading to poor posterior inference of the calibration parameters. Lastly, this study shows that it may be misleading to assume that the posteriors of the calibration parameters are representative of their true values and their associated uncertainty simply because the calibrated predictions matches the measured output well. [ABSTRACT FROM AUTHOR]

Users’ behaviour and indoor climate are two leading aspects that must be taken into account if we want the retrofitting of the housing stock to contribute to CO 2 reduction, comfort improvement and reduction of living costs. The integrated facade module evaluated in this paper, which constitutes an approach to zero energy renovation, includes a preliminary study for the identification of target occupants and their characteristics and requirements that will guide the design decisions. The proposed strategy primarily focuses on the case of social rental multi-family housing stock in the Netherlands, but should provide insights in the application of the concept in Europe. This paper presents the analysis of the adaptability of this solution to the Mediterranean climate, taking into account the specific characteristics of the occupants of this climatic zone. The results showed an improved performance of building after the application of the evaluated solution in southern Spain, but with lower savings on the energy demand than in the Netherlands, so the economic investment should be reduced in this case. Also, the inclusion in the solution of some variables, such as the forced night-time ventilation for passive cooling and the insulation thickness reduction, were tested and proved to be an optimisation of its performance in the Mediterranean climate. Overall, the study concluded that the proposed refurbishment strategy has the potential to be implemented in different climates, particularly if certain modification in the facade operation is considered. [ABSTRACT FROM AUTHOR]

Empirical validation and code-to-code comparison of more than one building simulation tool has seldom been done in literature. Therefore this paper presents the first detailed comparison of 1D building energy simulation tools with 3D CFD simulation and measurement data from a test bed (Test-Box), exposed to natural environmental conditions. Dymola (library: IDEAS), EnergyPlus, IDA ICE and TRNSYS –four commonly used tools– were selected for comparison against highly accurate real measurement data and dynamic CFD results. This paper evaluates the performance of mentioned above 1D simulation tools and in particular their implemented Thermally Activated Building Systems (TABS) models. The mean error, RMSE, standard deviation and maximal error for the room air, the ceiling surface and concrete temperature of the Test-Box model results are acceptable for all tools. The time course of the room air temperature follows the measurement data relatively well for all four tools. However, the negative bias (Dymola -0.92 K, EnergyPlus -2.18 K, IDA ICE -0.37 K and TRNSYS -1.13 K) indicates a general overestimation for all tools. Furthermore, the paper reflects the properties of simulation tools regarding the modelling language, GUIs, co-simulation capabilities and their recommended field of application. [ABSTRACT FROM AUTHOR]

Increased environmental and economic awareness, coupled with local government incentives, means that solar energy applications in buildings are crucial to sustainable urban development and commercial energy investment. Considering the large available areas on building rooftops and walls, and the application of building-integrated photovoltaic products, previous research has paid extensive attention to solar radiation estimation for roofs and vertical walls. This paper proposes a developed pixel method integrated with Net Present Value (NPV) analysis and applies the measurement to 3D visualisation of the revenue distribution of potential PV projects on building surfaces, including vertical and non-vertical facades. A building model derived from a real student accommodation building is then chosen as a case study in this paper. The developed algorithm extracts data built in SketchUp, exports instantaneous shadow images and estimates solar energy potential over building surfaces for each pixel unit. Coloured 3D radiation maps illustrate the distribution of solar energy potential on roofs and facades. 3D contour lines with NPVs are introduced to visually conduct PV installation strategies with desirable revenues over project lifetimes. The results reveal that facade installation is also worthwhile, as the corresponding project revenues are competitive with rooftop installation during specific periods. This study will benefit designers and construction managers in determining the optimal solution for implementing solar rooftop and facade systems in the design and construction phases. [ABSTRACT FROM AUTHOR]

This paper presents a method to evaluate the thermal impact of complex fenestration systems on the energy balance of a building zone based on directional solar heat gain coefficients (DSHGC) and bi-directional scattering distribution functions (BSDF). The proposed methodology is presented as an alternative to layer-by-layer heat transfer models. An example of a layer-by-layer heat transfer model is the ISO15099 as implemented in the EnergyPlus building simulation program. The ISO15099 model relies on a number of assumptions that are not justified in the case of three-dimensional structures, air-permeable layers and deviations from ideal geometries, which are common features in commercial daylighting and solar-control systems. In this paper, the proposed methodology is implemented in the Fener simulation engine and compared with EnergyPlus for systems for which the assumptions of the ISO15099 model are valid. Then, the Fener program is used to simulate the thermal behaviour of a zone with a fenestration system that contains sawtooth-shaped retro-reflecting interior blinds, which cannot be directly modelled with the ISO15099 model. The impact of different control strategies on the thermal performance of the zone is demonstrated for this case study. [ABSTRACT FROM AUTHOR]

At present, dynamic simulation and analysis on building thermal environment and energy consumption achieved by computer software become a reality. However, it is found that defined gaps exist between simulation and on-site measurement. To explore the gaps, this paper takes typical air-conditioned university dormitories located in Chongqing as a case study. Simultaneously, the gaps are explored with a DeST-h building energy simulation model and on-site measurement. Indicators including indoor temperature, relative humidity and air conditioning energy consumption under different setting temperature are simulated and measured. Then, a comparison between simulation results and measured data is explored as well as the cause of these gaps. This paper studies thermal environment and energy consumption by combining on-site measurement and numerical simulation, and the conclusion is that the gaps can from occupant behaviour and physical parameters of the indoor and outdoor environment, which provides a reference for thermal environment of the dormitory and building simulation. [ABSTRACT FROM AUTHOR]

In this paper, CFD analysis was used to determine the internal air temperature over long periods of four full scale housing test modules in Newcastle, Australia exposed to a moderate climate. The influence of different time steps (i.e. 15, 20 30, 35, 40 45, 60, 80, 100, 120, 150, 180 minute intervals) on the discrepancies in peak temperature for the CFD simulations is discussed in the paper. It was found that the average discrepancies in time for internal peak temperatures were between one and five hours compared with the real responses of the testing modules. [ABSTRACT FROM AUTHOR]

HVAC manufacturers make important investments to develop more efficient technologies for space heating (SH) and domestic hot water generation (DHW). Among these technologies, this article focuses on Double service air-to-water-heat-pumps (AWHP). The control of AWHP strongly impacts their performances, so that manufacturers of AWHP need to optimize the control of their systems to increase their performances. This paper presents the implementation of a Hardware-In-the-Loop – HIL – real time simulation test bench for AWHP. The new test bench proposed uses real weather conditions and simulates building’s and occupants’ response thanks to a virtual model. This test bench allows R&D departments and manufacturers to test several heating systems in parallel as well as different control options. It may also limit the need for field testing. It thus has the potential to reduce the cost and time required for AWHP development-to-market process. The test bench presented in this paper is used for a specific AWHP and a typical building in France. The analysis of the impact of the heat pump’s control on the system dynamics and on the indoor thermal comfort enables to highlight control issues related to the heating curve, the DHW management and the defrost process of AWHP. Optimized control parameters throughout time are proposed in view of reaching lower consumption and better performances. This case study shows the potential of the HIL test benches for manufacturers to optimize the development of their products controls. [ABSTRACT FROM AUTHOR]

Uncertainty Quantification (UQ) employing a Monte Carlo Sampling (MCS) method in a building simulation domain has been widely used to account for risks of predicted outputs for robust decision making. However, the stochastic approach for UQ problems requires significant computational burdens compared to the deterministic approach. This paper addresses two surrogate models (Gaussian Process Emulator (GPE) and Polynomial Chaos Expansion (PCE)) which together can be regarded as a meta-model of a Building Performance Simulation (BPS) tool with a high-fidelity model. In the paper, the developed GPE and PCE with different model structures were compared in terms of a prediction capability under different amount of training data and number of inputs. The aim of the comparative study is to identify the relative prediction abilities and model flexibility of GPE and PCE. It was found that the GPE and PCE produce high performance qualities having fast computation speed compared to the developed basis model if new inputs having identical inputs and probability ranges were used. In terms of two-sample Kolmogorov-Smirnov (K-S) hypothesis test, mean values of the minimum p-values of the GPE and PCE were 0.999 and 0.569, respectively, if the number of samplings are over 30 cases. Otherwise, the PCE shows significantly reduced performance quality than the GPE. [ABSTRACT FROM AUTHOR]

The building sector is one of the largest consumers of natural resources and energy in the world. Strategies to improve the energy efficiency are a solution to improve the performance of a building. However, in most cases, such strategies are assessed only at the operational phase of a building. The life-cycle energy analysis can be an important tool to allow choosing the best strategy. The objective of this paper is to assess the energy performance of four window shading systems in a house using life-cycle energy analysis. Life-cycle cost analysis was also used to determine not only the most energy-efficient strategy, but also the most economically feasible one. A house located in Florianópolis, southern Brazil, was evaluated based on a 63-year lifespan. The four window shadings analysed were: punctured concrete blocks, aluminium double sliding shutters, PVC roller shutters and wooden double open shutters. The EnergyPlus computer programme was used to estimate only the annual energy consumption for air-conditioning with and without the shading strategies. National and international databases were used to perform the life-cycle analysis. For the life cycle cost analysis, the cost of each strategy was obtained through a survey in local stores. The average inflation rate in the last ten years in Brazil was used to estimate the future costs. The results showed that the use of wooden double open shutters and PVC roller shutters are the most suitable solutions for window shading, both in terms of energy and costs, if they are not replaced during the lifespan of the building. This paper pointed out the need of using the proposed methodology to assure the right choice of strategies for energy efficiency in buildings. [ABSTRACT FROM AUTHOR]

Computer simulation for buildings has become affordable and possible in both research and industry during the last decades with rapid progress of computer industry as well as fundamental advancement of computational techniques. This paper provides an overview of such advancements achieved between 1987 and 2014, during which Professor Branko Todorovich served as Editor in Chief of Energy and Buildings Journal. The review, however, was not restricted to this journal only, in order to provide a fair snapshot on overall technique advances. Simulation and computational techniques cover a variety of aspects of building. This paper focuses specifically on six different topics including ventilation performance prediction, whole building energy and thermal load simulation, lighting and daylighting modeling, building information modeling, indoor acoustic simulation, and life cycle analysis of buildings. Major advances in each area are highlighted, as well as the trends for development and application. [ABSTRACT FROM AUTHOR]

The buildings sector is responsible for 37 % of global final energy consumption and nearly 40 % of total direct and indirect CO 2 emissions. This has led to promoting renovation efforts to decrease operational emissions of the existing building stock. With decreasing operational emissions, embodied emissions are becoming more important. In new buildings, embodied emissions account for about half of total emissions through the life cycle of a building. If both embodied and operational emissions are considered, renovation often outperforms new constructions, due to high embodied emissions of the structure - especially solid construction with a basement. Based on this, the decision if a building should be renovated or replaced is often not straight forward and depends on various factors. In this paper, a typical German building was considered as a case study, for which both renovation and replacement scenarios were considered, to identify the optimal solutions in terms of overall energy consumption and CO 2 emissions of the building in the use phase, the environmental impacts of the building along its entire life cycle, and related costs. Results show that the lowest CO 2 emissions during the lifetime of the analyzed building can be achieved with a sustainable replacement building (-2.05 kg CO 2 /m2/year) by using a heat pump with ground collector coupled with PV. This allows, compared to the existing reference building, reductions of 97 % and 101 % in terms of energy consumption and CO 2 emissions, respectively; while natural gas-based technologies are the least targeted and the most volatile to fuels' prices changes over the years. [ABSTRACT FROM AUTHOR]

In this paper simulation results of two typical houses in St. John's are presented using BEOpt (Building Energy optimization) software. Simulation is done using one-year weather data, typical thermostat settings and occupation of two houses. BEopt provides capabilities to evaluate residential building designs and identify cost-optimal solution at various levels of whole-house energy savings along the path to zero net energy. It was noticed that the annual energy consumption determined using simulation in BEopt is almost same as the actual energy consumption, logged with a sampling time of 2 minutes for both the houses. This simulation, analysis and a comparison is necessary to validate the thermal model of houses. The developed model of the houses could be used to design a renewable energy system or study human behaviour impact on the house energy consumption. Simulation results and a detailed analysis of the logged data are presented in the paper. [ABSTRACT FROM AUTHOR]

To facilitate the integration of buildings to the power grid, battery-equivalent models have been proposed to characterize and quantify aggregate flexibility from building loads. An analytical method has been proposed to construct such a flexibility model for thermostatically controlled loads. Since this analytical method is derived from a simplified representation of building thermal dynamics, it is necessary to evaluate the resulting flexibility model in a more realistic context. This paper focuses on the validation of this analytical method for estimating aggregate flexibility from residential air conditioning (ACs) systems. A high-fidelity model is first developed to mimic thermal behaviors of a residential AC system through a co-simulation between Modelica and EnergyPlus. A population of virtual residential AC systems is then generated by randomizing parameters of the high-fidelity model. Finally, an aggregate flexibility model is constructed for the residential AC population using the analytical method and validated using results from simulation of the high-fidelity model. It is found that the flexibility estimated using the analytical method is with reasonable accuracy, but can be improved by explicitly incorporating heat gains into the method. [ABSTRACT FROM AUTHOR]

The paper aims to achieve the modelling of climate change effects on heating and cooling in the building sector, through the use of the available Intergovernmental Panel on Climate Change forecasted data. Data from several different climate models will be fused with regards to mean air temperature, wind speed and horizontal solar radiation. Several climatic models data were analysed ranging from January 2006 to December 2100. Rather than considering each model in isolation, we propose a data fusion approach for providing a robust combined model for morphing an existing weather data file. The final aim is simulating future energy use for heating and cooling of a reference building as a consequence of the expected climate changes. We compare results, in terms of robustness to overfitting, for two different fusion methodologies, based on the comparison between errors on punctual historical data or prediction models that can be obtained by each climate simulator and by the actual ERA-INTERIM data set. Finally, we map the new aggregated data into a prediction trace of heating and cooling energy requirements. The expected energy demand is in the range of the one provided by single climate models, with a variability that reaches up to the 10% of the overall energy requirements. The approach proposed is an advancement as it allows to achieve better fits with existing re-analysis data if compared to specific global circulation models output data. Thus a more reliable estimation of energy use for heating and cooling can be achieved. [ABSTRACT FROM AUTHOR]

Among the various factors that affect building performance, occupant behavior (OB) has received more and more attention and has become a research hotspot in building design and operation in recent years. However, due to the remarkable randomness and diversity of OB in buildings, it is difficult to accurately describe its characteristics using a fixed schedule, which is a normal approach of most energy simulation tools. DeST, a whole building energy simulation tool offers the function of stochastic OB simulation so that the simulation results can be more in line with the actual situation. In the newly released DeST 3.0, the OB modules are developed based on the actual observed OB data and are divided into two parts: occupancy and occupant action modules. The occupancy module is based on the Markov chain, which simulates the occupant movements among the spaces inside and outside the buildings. The occupant action modules are proposed with an environment and event-driven stochastic infrastructure based on a three-parameter Weibull distribution, such as occupant shading, window, and air-conditioning (AC)/heating control behavior modules. This paper presents the OB modules development for coupled simulation in DeST 3.0 and discusses the effects of integrated simulation of occupant behavior on building energy consumption. Firstly, an overview of the current modelling efforts of OB is given, from the trend to the existing foundation. Secondly, the development of OB modules for coupled simulation in DeST 3.0 is introduced in-depth, including co-simulation of AC/heating control behavior, window behavior and shading behavior. Lastly, two case studies that realize coupled simulation using the developed modules are shown, one is the comparison between existing occupancy schedules from GB standards and the developed occupancy simulation, and the other is the comparison between the result of simulating with or without using AC/heating control behavior modules in two bedrooms of the residential building. [ABSTRACT FROM AUTHOR]

Abstract: Metal mesh grids and perforated screens are used in new and renovated buildings as an external second skin for the building envelope; to enhance architecture design, to filter daylight and to reduce solar gains. Their effectiveness as shading devices depends on their geometry, texture and application. In the first part of the paper six types of shadings with similar transparencies, depending on geometry and openness factor of metal mesh grid and perforated screen, were investigated. Integrating sphere measurements were collected to obtain spectral optical properties of the shading devices. The optical properties were measured for incidence angles between normal and 60°with a step of 15°. The data collected were integrated to obtain visible and solar transmittance values in accordance with ISO 9050. In the second part of the paper a parametric study on spacing and thread dimension of metal mesh grids was done using Window 6.2 models to evaluate their shading potential, defining annual different shading profiles depending on shading geometry, latitude and orientation. A conventional office unit with a curtain wall façade with a metal mesh grid shading system was modeled in TRNSYS to evaluate the solar gain profiles and their effects on the energy balance of the office unit, under different weather conditions. [Copyright &y& Elsevier]

Abstract: In this paper the energy and exergy performance of a social dwelling of a multi-family building from the 1960s in Bilbao (Spain) is presented and various improved energy concepts based on exergy principles are proposed and investigated. The aim of this paper is to explore and demonstrate the usefulness of the exergy approach in the assessment and development of an energy system for the dwelling under consideration. The total energy supply system is analysed, including the demand (space heating, domestic hot water and electricity), the system components (for conversion, storage and distribution) and the energy input from energy resources (primary energy and renewable resources). The study includes a comparison of the primary energy input of all cases considered and an analysis of the energy and exergy losses of each system component. The study has shown that the exergy analysis reveals thermodynamic losses that are not revealed using energy analysis and secondly, that the development of an improved energy system based on exergy principles has resulted in a significantly reduced primary energy input compared to the reference situation. [Copyright &y& Elsevier]

Abstract: Although absorption cooling has been available for many years, the technology has typically been viewed as a poorly performing alternative to vapour compression refrigeration. However, rising energy prices and the requirement to improve energy-efficiency is driving renewed interest in the technology, particularly within the context of combined cooling, heat and power systems (CCHP) for buildings. In order to understand the performance of absorption cooling, numerous models are available in the literature. The complexities involved in the thermodynamics of absorption chillers have, however, so far restricted researchers to creating steady-state or dynamic models reliant on data measurements of the internal chiller state, which require difficult-to-obtain, intrusive measurements. The pragmatic, yet fully dynamic model described in this paper is designed to be easily calibrated using data obtained from the measurements of inflows and outflows to a chiller, without resorting to intrusive measurements. The model comprises a series of linked control volumes featuring both performance maps and lumped mass volumes, which reflect the underlying physical structure of the device. The paper describes the modelling approach, theory and limitations, along with an example of the implementation of the model in the ESP-r code complete with calibration and an application to a specific example. [Copyright &y& Elsevier]

This paper presents the development of a self-tuned HVAC controller that provides customized thermal conditions to satisfy occupant preferences (i.e., online learning) while minimizing energy consumption, and the implementation of this controller in a real occupied office space. The evolution of personalized thermal preference models and the delivery of thermal conditions with model predictive control (MPC) form a closed-loop. To integrate these two parts, we propose a new method that always provides a set of lower and upper indoor temperature bounds. Different from ad hoc rules proposed in previous research, the control bounds are based on a decision-making method that minimizes the expected cost. We implemented the self-tuned controller in an actual open-plan office space conditioned with a radiant floor cooling system with eight independently controlled loops. Localized operative temperature bounds in each radiant floor loop were determined based on occupants' feedback and personalized thermal preference models, developed using a Bayesian clustering and online classification algorithm. The self-tuned controller can decrease occupant dissatisfaction compared to a baseline MPC controller, tuned based on general comfort bounds. To generalize the findings of this work: (i) we integrated the self-tuned controller with local MPC into a building simulation platform using synthetic occupant profiles, and (ii) demonstrated a method for automatic system adjustment based on comfort-energy trade-off tuning. In this way, decisions resulting in energy waste or occupant dissatisfaction are eliminated, i.e., the energy is deployed where it is actually needed. [ABSTRACT FROM AUTHOR]

Abstract When integrated photovoltaics into building windows, the solar cells will absorb a fraction of solar radiation that hit on the window surface to generate electrical power and thus obstruct the solar energy and natural daylight that would have penetrated into inside space. In this paper, a window system integrated with thin film CdTe solar cells with 10% transparency was electrically characterised by Sandia model. The annual energy performance of a typical office with this PV window applied to different façade design was investigated using EnergyPlus under five typical climatic conditions in China. The dynamic daylight performance of the office has been assessed using RADIANCE. The result shows that when compared to a conventional double glazed system, the application of PV window can result in significant energy saving potential if the office has a relative large window-to-wall ratio (i.e. WWR≥45%). The simulation results also show that this PV window offers better daylight performance than conventional double-glazing. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes a new general method for building simulation programs which is intended to be used for the modelling of complex facades. The term ‘complex facades’ is used to designate facades with venetian blinds, prismatic layers, light re-directing surfaces, etc. In all these cases, the facade properties have a complex angular dependence. In addition to this, such facades very often have non-airtight layers and/or imperfect components (e.g. non-ideal sharp edges, non-flat surfaces, …). Therefore building planners often had to neglect some of the innovative features and to use ‘work-arounds’ in order to approximate the properties of complex facades in building simulation programs. A well-defined methodology for these cases was missing. This paper presents such a general methodology. The main advantage of the new method is that it only uses measureable quantities of the transparent or translucent part of the facade as a whole. This is the main difference in comparison with state of the art modelling based on the characteristics of the individual subcomponents, which is often impossible due to non-existing heat- and/or light-transfer models within the complex facade. It is shown that the new method can significantly increase the accuracy of heating/cooling loads and room temperatures. [ABSTRACT FROM AUTHOR]

Highlights • Assess the impact of design factors of semi-transparent PV window on building performance. • Evaluate an office performance with integrated STPV window using innovate approach. • Apply window integrated PV resulting in a reduction in energy consumption of up to 73%. • Selected PV window offers better daylight performance than conventional double glazing. Abstract When integrating photovoltaics into building windows, the photovoltaic glazing modules inhibit the function that glass performs, with the additional function of energy production. Semi-transparent Photovoltaic (STPV) glazing will absorb part of the solar radiation incident on the window surface to generate electrical power. In turn, this affects the overall solar energy and natural daylight penetrating into the indoor space. Various factors determine the building energy performance and indoor comfort level as a result of adopting STPV glazing. The factors regarding window design alone (window size, PV glazing coverage ratio and PV glazing placing position) require rigorous study. In this paper, an innovate model (combined optical, electrical and energy model) was developed to comprehensively evaluate the performance of an office equipped with STPV window and firstly analyse the effect of window design on overall energy efficiency. A double-glazing unit integrated with thin film CdTe solar cells with 10% transparency was electrically characterised by Sandia Array Performance Model (SAPM). The annual energy performance of a typical office served by window integrated STPV glazing was investigated through EnergyPlus simulation for various window designs under five typical climatic conditions in China (using weather files of Harbin, Beijing, Shanghai, Guangzhou and Kunming for representation). The optical performance (defined by a Bidirectional Scattering Distribution Function) of this STPV glazing was also obtained using a ray-tracing technique. Then, the annual daylight performance of the porotype office was assessed using RADIANCE. We found that when compared to a conventional double-glazed system, the application of PV window can result in considerable energy saving if the office has a relatively large window-to-wall ratio (i.e. ≥ 45%), while the position of placing STPV glazing has significant influence on the lighting energy consumption. In the specific climates under test, the optimal design scenario of applying window integrated PV can result in a reduction in energy consumption of up to 73%. The simulation results also show that this PV window offers better daylight performance than conventional double glazing and effectively reduces the possibility of glare. [ABSTRACT FROM AUTHOR]

Highlights • A component-based method of machine learning for performance prediction in engineering. • Components instead of one monolithic model extend reusability and generalization. • Flexible design support by machine learning for early design phases. • Internal parameters between components allow insights in the “black box” of machine learning. • Good prediction accuracies (error < 3.9%) for test cases different from the training model. Abstract Machine learning is increasingly being used to predict building performance. It replaces building performance simulation, and is used for data analytics. Major benefits include the simplification of prediction models and a dramatic reduction in computation times. However, the monolithic whole-building models suffer from a limited transfer of models and their data to other contexts. This imposes a vital limitation on the application of machine learning in building design. In this paper, we present a component-based approach that develops machine learning models not only for a parameterized whole building design, but for parameterized components of the design as well. Two decomposition levels, namely construction level components (wall, windows, floors, roof, etc.), and zone-level components, are examined. Results in test cases show that, depending on how far the cases deviate from the training case and its data, high prediction quality may be achieved with errors as low as 3.7% for cooling and 3.9% for heating. [ABSTRACT FROM AUTHOR]

Abstract Numerous occupant behavior models, typically stochastic ones, have been built to quantify the effect of occupants on building energy simulation, which however are supposed to go through a rigorous validation, or evaluation process to claim that they are qualified to be used in the application. Current contributions relevant with occupant behavior modeling in literature have been resorting to statistical metrics rather than those orienting on their application, causing the disputation in interpreting the accuracy of the occupant behavior models when they are actually used in simulation. Furthermore, the stochasticity of occupant behavior models necessitates statistical evaluation of the model accuracy, instead of the comparison between actual data and a single-run simulated data. This paper proposes a methodological framework for model evaluation from an application-oriented perspective, with lighting behavior as a case study. The metrics for evaluating lighting behavior models are identified according to different application scenarios, while the comparison between the measurement and simulation is done by introducing the statistical hypothesis testing. Analogous analyses on other behaviors can be conducted in the future, which altogether would foster more rigor and application significance in occupant behavior model evaluation. [ABSTRACT FROM AUTHOR]

Buildings consume a significant amount of energy worldwide in maintaining comfort for occupants. Building energy management systems (BEMS) are employed to ensure that the energy consumed is used efficiently. However these systems often do not adequately perform in minimising energy use. This is due to a number of reasons, including poor configuration or a lack of information such as being able to anticipate changes in weather conditions. We are now at the stage that building behaviour can be simulated, whereby computer programs can be used to predict building conditions, and therefore enable buildings to use energy more efficiently, when integrated with BEMS (i.e. simulation assisted control [1]). In this paper we demonstrate a low cost BEMS that uses building simulation to predict optimised electrical heating startup control points. Those that use electricity for heating in Scotland, where this study was based, tend to be fuel-poor, hence there is a strong case for optimisation, particularly when electricity costs nearly three times as much as the equivalent unit of gas for heating applications. The proposed system demonstrated a 50% energy saving in the reduced heating time compared to scheduling when retrospectively evaluated. [ABSTRACT FROM AUTHOR]

Most building energy simulation (BES) tools need detailed inputs for the modeling process because of the nature that building is a complex system and evaluating its performance usually involves many factors and uncertainties. In this research, a lightweight building energy simulation tool – SimBldPy, is proposed. The proposed simplified hourly method in this paper includes additional thermal resistances of the zone internal floor and internal walls coupled with adjacent zone temperature. Two DOE reference building types (one residential and one office) located in Philadelphia and San Francisco are used in the research to verify the performance of the tool. Its performance and validity in simulating hourly energy use with different heating and cooling set points in each zone, under various climate conditions, and with multiple ECMs being applied to the building, have been tested and verified with EnergyPlus. This tool and modeling method could be used for rapid modeling and assessment of building energy for a variety of ECM options. By using this tool in modeling an on-campus building in University of Pennsylvania, it is shown that the calibrated building model in SimBldPy can be used to model the energy use of an existing building. With low cost in computation, the tool is able to provide rapid modeling and assessment of building energy use (BEU) for parametric studies. [ABSTRACT FROM AUTHOR]

Abstract: A building is permanently in thermodynamic non-equilibrium due to changing weather, free gains and indoor temperature set-point. Load calculation in dynamic conditions is an essential goal of building energy simulation. This paper demonstrates that the load calculation is a control problem. Supposing that the thermal model of the building is linear and that the model of the building, the weather conditions and occupational program are known in the design stage, the paper proposes an unconstrained optimal control algorithm which uses feed-forward to compensate the weather conditions and model predictive programming (MPP) for set-point tracking. MPP is obtained by modifying the dynamic matrix control (DMC), a variant of model predictive control (MPC). The peak load depends on the set-back time of the indoor temperature: smaller the set-back time, larger the peak load, but smaller energy consumption. Then, the choice of the weighting coefficients in the model predictive programming may be done on economical considerations. [Copyright &y& Elsevier]

Abstract: To maintain ultra-low particle concentrations, cleanrooms can require several hundred air changes per hour. These ventilation rates make cleanrooms 30–50 times more energy intensive than the average U.S. commercial building. There are an estimated 12millionm2 of cleanroom space in the U.S., consuming over 370PJ of energy each year. This paper explores opportunities to improve the energy efficiency of cleanrooms while maintaining or improving operating conditions. This paper documents the modeling of a 1600m2 cleanroom in upstate New York. The TRNSYS model includes TMY2 weather data; building geometry and material properties; empirical data on occupancy, lighting and process equipment; and sophisticated HVAC systems. The model was validated based on metered steam, chilled water and electricity usage. Under 8% error was achieved in all fields. Four strategies were simulated: a heat recovery system for exhaust air, resulting in an 11.4% energy reduction with a 2.7-year simple payback; solar preheating of desiccant dehumidifier regeneration air (2.4% energy reduction, 11.5-year payback); improved lighting controls (0.3% energy reduction, 1.5-year payback); and demand-controlled filtration (4.4% energy reduction, 3.1-year payback). Implementation of recommended strategies is predicted to save 9TJ, 862tonnes of CO2, and $164k annually. [Copyright &y& Elsevier]

Abstract: The efficiency of heating systems is increasingly important because of the increasing need to save energy and protect the environment. This paper presents an innovative technique for modeling multi-zone hydronic heating systems in buildings in an easier and more user friendly manner. An original approach is described in which the thermal and hydronic systems are solved simultaneously by simulating the dynamic behavior of pipe water flow rates, water temperatures, and room air temperatures. The simulation uses mathematical models that apply a Newton–Raphson method (NRM) developed in Matlab© and Simulink© environments. A user friendly graphical user interface (GUI) enables the designer to analyze any multi-zone hydronic heating system from the point of view of improving its efficiency. A laboratory heating system was used to validate this modeling technique. A series of trials were conducted in a multi-zone laboratory heating system located within the R&D division of a leading Italian boiler manufacturer, and the results presented in this paper validate the model. [Copyright &y& Elsevier]

This paper summarizes a PhD-project that is currently under completion at Delft University of Technology, Faculty of Architecture, Building Physics Group. The general problem addressed in this project is the integration of building simulation tools and building design. This problem has been narrowed down to computational support for one specific type of building design decision: the selection and integration of one or more energy saving building components like solar walls, advanced glazing systems, sunspaces and photovoltaic arrays into a given building design.The paper provides an overview of the main research efforts that were carried out during the research [Computational Support for the Selection of Energy Saving Building Components, PhD thesis (in preparation), Building Physics Group, Faculty of Architecture, Delft University of Technology, 2004]. Based on results and on views that have been described in earlier publications (e.g. [Beter ontwerp door gebouwprestatie-simulatie? in: Proceedings of the Third IBPSA-NVL Conference, Petten, The Netherlands, December 2001]), the paper then will identify relevant, challenging issues for future research in the area of integration of building simulation tools into the building design process. Specific attention will be paid to issues related to the use of different categories of tools (simulation tools as well as other instruments) for the development of new, energy-efficient building design concepts. [Copyright &y& Elsevier]

• Changes in peak demand are often larger than changes in annual demand. • Ventilation rate is the parameter with the largest contribution for HVAC demand. • Equipment and lighting density have substantial contributions for total demand. Previous dynamic building simulation studies have not often focused on analysing the sensitivity of peak loads to input parameters. However, these peak loads may have a critical impact on system design capacities and power network operation. This study aims to examine the sensitivity of cooling demand related results (total electricity demand, HVAC end-use and space cooling) in a large office building using two global sensitivity analysis methods: Morris elementary effect and Sobol indices. More specifically, this paper examines the implications of different type of climates to the uncertainty in these different cooling output results and the sensitivity of the different parameters for each result. Moreover, this paper investigates the difference between the effects of annual and peak analysis for cooling demand of office buildings, which can provide insight on cooling demand from the perspectives of total cooling energy and system capacity for building cooling systems, respectively. This study has found that generally, the changes are more significant for peak demand than for annual demand. The coefficient of variation for the total peak demand is around 25% and 21% for total annual demand. This study identifies that the ventilation rate is the parameter that contributes the largest for the uncertainty in electricity demand of the HVAC end-use, between 50% and 70% of the change (S T), both for annual and peak demand. Regarding the effect on total electricity demand, ventilation rate is still one of the most critical factors, but equipment and lighting densities also become a significant contributor to the sensitivity of the total demand. [ABSTRACT FROM AUTHOR]

Built environments contribute significantly to mitigating climate change. However, existing buildings, which form most urban infrastructures, do not typically meet contemporary stringent energy efficiency standards. They are naturally continuously deteriorating, making them a continuous negative contributor to their surrounding environments, which keeps getting worse. Therefore, there is a need to develop performance diagnosis frameworks and approaches for accurate Building Energy Model (BEM) simulations to develop impactful retrofitting design solutions that could make existing buildings perform closer to current efficiency measures. This paper reports on research that focuses explicitly on calibrating envelopes of existing BEMs using drones equipped with thermography sensors. The study specifically focuses on the automation of on-the-fly envelope U-value estimations and verification of calibrated envelope BEMs. The paper examines a renovated campus building in Boston, MA., representing material degradation, thermal bridging, and insulation failures using thermal imaging. A BEM is then calibrated, and post-renovation metered and modeled wintertime heating energy are compared. Goodness of fit measures showcase BEM performance improvement from 21.8%to 0.9%, which demonstrates the utility of the proposed framework. Further research is recommended to expand the focus on anomalies in the envelope and increase the scope from the building scale to the neighborhood scale. [ABSTRACT FROM AUTHOR]

Due to the rapid rise of power consumption of data centers in recent years, much work has been done to develop energy-efficient design, controls and diagnosis of their cooling systems, while the energy system simulation is used as an effective tool. However, existing models of information technology (IT) equipment of data centers cannot well represent the effects of IT equipment design and operation status on the data center cooling demand, and this hinders the development of the energy saving cooling technologies of data centers. To address this issue, this paper introduces a power consumption model of IT equipment in data centers with coefficients and modeling script provided for immediate use in data center energy system simulation. This energy model can be used to simulate energy performance of typical IT equipment in data centers under real-time dynamic operation conditions conveniently and effectively without the need of data other than the specifications of a data center design and IT equipment manuals. Its use with a commonly used building simulation program is demonstrated with a building model of a typical large office in a subtropical area. The results show that the model can represent the change of power consumption of data centers with different IT equipment designs and operation appropriately. [ABSTRACT FROM AUTHOR]

Developing BEPS models which predict energy usage to a high degree of accuracy can be extremely time consuming. As a result, assumptions are often made regarding the input data required. Making these assumptions without introducing a significant amount of uncertainty to the model can be difficult, and requires experience. Even so, rules of thumb from one geographic region are not automatically transferrable to other regions. This paper develops a methodology which can be used to determine useful guidelines for defining the most influential input data for an accurate BEPS model. Differential sensitivity analysis is carried out on parametric data gathered from five archetype dwelling models. The sensitivity analysis results are used in order to form a guideline minimum set of accurately defined input data. Although the guidelines formed apply specifically to Irish residential dwellings, the methodology and processes used in defining the guidelines is highly repeatable. The guideline minimum data set was applied to practical examples in order to be validated. Existing buildings were modelled, and only the parameters within the minimum data set are accurately defined. All building models predict annual energy usage to within 10% of actual measured data, with seasonal energy profiles well-matching. [ABSTRACT FROM AUTHOR]

Building retrofits provide a large opportunity to significantly reduce energy consumption in the buildings sector. Traditional building retrofits focus on equipment upgrades, often at the end of equipment life or failure, and result in replacement with marginally improved similar technology and limited energy savings. The Integrated System (IS) retrofit approach enables much greater energy savings by leveraging interactive effects between end use systems, enabling downsized or lower energy technologies. This paper presents a case study in Hawaii quantifying the benefits of an IS retrofit approach compared to two traditional retrofit approaches: a Standard Practice of upgrading equipment to meet minimum code requirements, and an Improved Practice of upgrading equipment to a higher efficiency. The IS approach showed an energy savings of 84% over existing building energy use, much higher than the traditional approaches of 13% and 33%. The IS retrofit also demonstrated the greatest energy cost savings potential. While the degree of savings realized from the IS approach will vary by building and climate, these findings indicate that savings on the order of 50% and greater are not possible without an IS approach. It is therefore recommended that the IS approach be universally adopted to achieve deep energy savings. [ABSTRACT FROM AUTHOR]

With increased use of variable refrigerant flow (VRF) systems in the U.S. building sector, interests in capability and rationality of various building energy modeling tools to simulate VRF systems are rising. This paper presents the detailed procedures for model calibration of a VRF system with a dedicated outdoor air system (DOAS) by comparing to detailed measured data from an occupancy emulated small office building. The building energy model is first developed based on as-built drawings, and building and system characteristics available. The whole building energy modeling tool used for the study is U.S. DOE’s EnergyPlus version 8.1. The initial model is, then, calibrated with the hourly measured data from the target building and VRF-DOAS system. In a detailed calibration procedures of the VRF-DOAS, the original EnergyPlus source code is modified to enable the modeling of the specific VRF-DOAS installed in the building. After a proper calibration during cooling and heating seasons, the VRF-DOAS model can reasonably predict the performance of the actual VRF-DOAS system based on the criteria from ASHRAE Guideline 14-2014. The calibration results show that hourly CV-RMSE and NMBE would be 15.7% and 3.8%, respectively, which is deemed to be calibrated. The whole-building energy usage after calibration of the VRF-DOAS model is 1.9% (78.8 kWh) lower than that of the measurements during comparison period. [ABSTRACT FROM AUTHOR]

Australia’s commercial building stock exceeds 134 million m 2 of net lettable area, with retail buildings contributing 35% to this sector’s energy use. The energy intensity of retail buildings in hotter climates is higher than the national average, as is the energy intensity of smaller buildings (under 1500 m 2 ) that are not considered ‘high-end’ commercial properties. Little attention has been paid to improving the energy efficiency of these types of buildings through regulation (for new buildings) or through market mechanisms (for retrofitting). As many of these buildings are single storey ‘warehouse’ type buildings, their predominant heat load comes through the roof, and thus are well suited to benefit from cool roof technology. Despite this, there remains a deficiency in quantifying the benefit of such technology in the context of single-storey retail buildings in Australia. This paper reports on an experimentally validated numerical study aimed at addressing this deficiency. Results show that application of cool roof technology to a warehouse type building in a subtropical environment increases the energy efficiency by shifting space temperature towards the design set point (21–23 °C), and thus reducing cooling energy demand. This study also indicates an energy saving every month with the application of cool roof, with the largest saving in hotter months and no heating penalty in cooler months. Application of cool roof technology on warehouse style buildings across Australian buildings indicates energy savings can be achieved in all broad Australian climatic zones, with the greatest energy reduction associated with tropical, subtropical and desert environments. [ABSTRACT FROM AUTHOR]

The IT equipment power consumption estimated by building simulation software is much higher than the actual case, but there are no simple solutions for building engineers to reduce the bias in data center models in building simulation. This paper address this issue by proposing a simple model of IT equipment load. The model estimates the IT equipment load based on critical control inputs of the IT equipment such as its processor utilization rate and on/off status, and a survey of literature for the ordinary values of these IT equipment control variables is conducted to facilitate its uses by building engineers. A case study was conducted with building models of large offices with lots of IT equipment, and the estimated annual building energy use was reduced by more than 30% in all three cases. This shows that the conventional constant thermal load model overestimates the IT equipment load and the IT equipment model improves the accuracy of modeling of data centers in building simulation by modeling the changes of the load with the status of the servers. [ABSTRACT FROM AUTHOR]

Sensitivity analysis has been widely used in building energy assessment to provide reliable analysis of importance ranking for input variables in buildings. Most of previous studies used one single batch simulation models to obtain sensitivity indicators. To conduct robust analysis, this paper implements a sequential sensitivity analysis to assess the convergence of sensitivity indicators for two global sampling-based sensitivity analysis methods (standardized regression coefficients and meta-modelling Sobol) in an office building. The results indicate that this sequential method can be more effective and robust. In contrast, a single batch sensitivity method for building energy assessment may lead to non-convergence results due to smaller number of simulation models or over-convergence results due to larger number of simulation models. It is also found that the convergence rate for standardized regression methods are slower than that for the meta-modelling Sobol method. [ABSTRACT FROM AUTHOR]

Uncertainty analysis has become an active research area in the field of building energy analysis because most of parameters are inherently uncertain in buildings. Most of previous studies implement probabilistic-based uncertainty analysis, which requires detailed information to define probability for input factors. However, it is hard to obtain detailed information for these inputs, especially at the initial design stage of a building project. Therefore, this paper applies the non-probabilistic Dempster-Shafer theory of evidence approach for uncertainty analysis in an office building using the EnergyPlus program. The results indicate that the Dempster-Shafer theory can be very useful to provide pertinent and reliable results by taking into account the level of available information in the design stage of building projects for sustainable buildings. The reliable machine learning models can be constructed in order to reduce high computational cost of this non-probabilistic uncertainty analysis method. [ABSTRACT FROM AUTHOR]

The commercial and residential buildings consume about 33% of energy for cooling and day lighting in India. This paper aims to present thermal performance of buildings constructed with various building and window glass materials in five different climatic zones of India. The climates considered include: hot and dry (Ahmedabad), moderate (Bangalore), cold (Guwahati), warm and humid (Madras), and composite (New Delhi). In this study, four building materials such as laterite stone, dense concrete, burnt brick, and mud brick were selected and four glasses such as clear, bronze, green, and bronze-reflective glasses were used for windows. Spectral characteristics of four glasses were measured experimentally by using Perkin-Elmer lambda 950spectrophotometer in the wavelength range of 300 -2500 nm as per ASTM standards. A mat lab code was developed to compute the solar optical properties such as transmittance and reflectance of glasses as per European standards in entire solar spectrum region. The building models were designed in Design builder 4.3.0.039 and thermal analysis was carried out in Energy plus 8.1.0.009. The solar heat gain in buildings was investigated. The results revealed that the mud brick wall building with south bronze-reflective glass window as energy saving from the least heat gain point of view among eighty building models studied. The results also showed that the mud brick wall building with bronze, green and bronze reflective window glasses reduces heat gain through wall by 2.52%, 3.83%, and 6.46% as compared to the mud brick wall building with clear glass window. The results helps in selecting energy saving combination of wall envelope and window glass materials for reducing air-conditioning loads in residential and commercial buildings of five different climatic zones of India. [ABSTRACT FROM AUTHOR]

The Energy Performance of Buildings Directive (EPBD) requires Member States to assess the energy use of buildings. However, the results heavily depend on the correct implementation of building properties and boundary conditions. This paper challenges the average indoor temperature assumed in Quasi Steady State methods and proposes a temperature profile to improve the accuracy of the simulation. This temperature profile is derived from in-situ measurements of the indoor temperature in nine terraced houses and is characterised by the energy performance of the building, the outdoor climate and the user behaviour. Applying this new temperature profile in the energy simulation model decreases the energy performance gap between simulated and actual energy use. [ABSTRACT FROM AUTHOR]

In the present paper CFD tool was used for thermal comfort evaluation in natural convection and in transient conditions in a room by setting only the external weather conditions as input parameters. A survey in a classroom at the Department of Engineering, University of Perugia, was carried out and data required for the thermal comfort evaluation and CFD simulation model set up was acquired. The simulation model was validated with experimental data and it was used for the thermal and velocity profiles simulation and for the thermal comfort indexes calculation, according to UNI 7730. [ABSTRACT FROM AUTHOR]

The transient nature of the occupant heat load is not fully addressed and implemented in a building simulation tool. In this paper, the effect of using dynamic occupant heat loads in building simulation on energy building performance and occupant thermal comfort has been studied. A two-node thermoregulatory model was integrated into ESP-r. The predictions of the integrated two-node model were compared to two commonly used approaches in building simulation: gains modelled as a basic fixed profile and gains modelled using a polynomial function of temperature and relative humidity. The variation in occupant thermal load demonstrated appreciable differences on both cooling and dehumidification loads. [ABSTRACT FROM AUTHOR]

Considering the complex interaction between energy performance, lighting, acoustic and thermal comfort in contemporary design, building performance simulation [BPS] shall play a key role in addressing decision making process and technical choices towards optimized configuration during the whole design phase. The paper reports the outcomes of a case study – performed in the framework of Ma Final Design Lab at the Department of Architecture, University of Bologna – where BPS was adopted from the very beginning as a tool to support the design process from the concept validation to the final architectural configuration to fit with passive house standards. [ABSTRACT FROM AUTHOR]

• Novel methodology for calculating cost-optimized refurbishment roadmaps is presented. • Coupling of building model for refurbishment and system model for heating technologies. • Refurbishment roadmap include timing and refurbishment measures for specific buildings. • Applying the optimization achieves cost savings of 6–16 % and CO 2 savings of 6–59 % • Heat pumps play a central role in the context of CO 2 reduction. 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 CO 2 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 CO 2 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. [ABSTRACT FROM AUTHOR]

The objective of this paper is to review the topics related to the optimized operation of intelligent buildings with respect to occupant comfort and energy consumption. To simultaneously optimize energy costs and indoor environmental quality, intelligent buildings should consider several continuously changing inputs including energy exchange processes across the building, sets of indoor and outdoor environmental parameters, energy prices, occupants' presence, preferences, and behavior inside the building. Therefore, a well-structured framework supported by computational intelligence and optimization methods, environmental monitoring, and behavior modeling techniques, as well as comfort, productivity, and behavioral studies, are required to make optimal decisions for the indoor environment. In this paper, the main concepts, challenges, the latest studies, findings, and developments related to the six topics of (1) Occupant comfort conditions; (2) Occupant productivity; (3) Building control; (4) Computational optimization; (5) Occupant behavior modeling; (6) Environmental monitoring and analysis, in offices, commercial and residential buildings are reviewed. Moreover, future directions and challenges related to the optimized operation of intelligent buildings are discussed. [ABSTRACT FROM AUTHOR]