Current housing unit design focuses on performance optimization, such as building energy use, daylighting, and occupant comfort. There is significant potential for efficient optimization in the early design stage. This paper proposed a building energy demand optimization framework that considers building design variables for housing unit design in Beijing. First, a high-rise apartment building was

Accurate simulation of solar irradiance on facades and roofs in a built environment is a critical step for determining photovoltaic yield and solar gains of buildings, which in an urban setting are often affected by the surroundings. In this paper, a new modelling method is introduced that uses Digital Surface Model (DSM) point clouds as shading geometry, combined with a matrix-based approach for simulating

In this paper, we introduce a real-time modelling approach to predict the heating and cooling energy consumption of each housing unit in multi-family residential buildings. We first present measured yearly heating and cooling energy use data from an actual building and introduce the eco-feedback design and associated modelling challenges. Subsequently, we present a real-time parameter learning-based

A new method is presented to evaluate thermal interactions between vertical geothermal boreholes. The finite line source (FLS) solution is extended to consider thermal interactions between groups of boreholes. Groups of boreholes that share similar temperatures and heat extraction rates are identified using hierarchical agglomerative clustering, and each group is represented in the model as a single

This paper models and forecasts the cooling demand of centralized chiller plants in commercial districts using different statistical techniques – including OLS, Lasso, ARX, SARIMA, SARIMAX and Cochrane–Orcutt. Direct estimation of the test error using a validation data set is used to compare different techniques and to quantify goodness of fit. As a validation, these statistical techniques are compared

Intuitive visualizations of building performance simulation (BPS) output are important to the uptake of simulation-based decision-making in the early design stages. However, reports on studies that investigate this aspect of BPS output visualizations are scarce and often assume what building design stakeholders consider as desirable traits for intuitive interpretation. This paper reports on a research

In this paper, heating and ventilation air conditioning system (HVAC) dataset for a medium-large size building in Romania has been used. It has been collected in one year. Linear state-space model of each air handling unit (AHU) has been estimated using two methods. Recursive extended least squares (RELS) algorithm has been used to estimate the state-space model in one year and seasonal form in the

(2021). Professor Godfried (Fried) Augenbroe. Journal of Building Performance Simulation: Vol. 14, No. 4, pp. 401-402.

Most of the window use models developed for building energy simulations include physical environmental variables as drivers. Even though it is a common approach to include these variables, the validity of this approach can be questioned based on observations in the literature regarding the consistency and seasonality of the relationship between these variables and the window use. Additionally, it was

In this paper, we present a new unit-level data-driven modelling approach to normalize heating and cooling (HC) energy usage in multi-family residential buildings based on easily accessible data from smart thermostats and WiFi-enabled power metres. Our physics-informed approach starts from a heat balance equation to derive a linear regression model and uses a Bayesian mixture model to identify groups

Connected thermostat data provide new opportunities to access heating, ventilation and air conditioning (HVAC) operation and indoor condition data in high-rise residential buildings. However, how well these thermostat data reflect actual conditions and operation is unclear and best-practices to leverage these data for energy use modelling are needed. Connected thermostat data from 54 suites in two

In building energy simulation (BES), internal loads are typically defined as hourly schedules based on occupant-related ‘activities’ assigned to each building zone. In this paper, a data-centric bottom-up functional data analysis model is used to examine how activities in a building correlate with energy demand for plug loads and lighting. Functional principal component analysis and hierarchical clustering

It is challenging to accurately establish the dynamic heat transfer model of the internal thermal mass owing to the irregular shape. In building energy simulation software, the internal thermal mass is described as slabs. However, the parameter setting of the equivalent slabs depends primarily on the user experience, which may lead to uncontrollable errors. Therefore, this paper proposes a method,

This paper presents a novel system of data-driven approaches for simulating the dynamics of electricity demand profiles. Demand profiles of individual dwellings are decomposed into deterministic (e.g. ‘Trends’ and ‘Seasonal’) and stochastic (‘remainder’) components using the STL (a Seasonal-Trend decomposition procedure based on Loess) approach. Stochastic components are modelled using a Hidden Markov

ABSTRACT Recent findings suggest that rooftop greenhouses could be more efficient when combined with waste streams in buildings, but there is a gap in quantification of the combined performance of building integrated greenhouses. This paper addresses this deficit for school buildings in London, UK, where urban agriculture is of increasing interest. A building energy simulation (BES) of an archetype

Ventilated slabs are used to provide indoor comfort by taking advantage of thermal inertia. The underlying difficulty is that the computational cost is high, which is hardly compatible with an exhaustive study of dynamic behaviour at room scale. This paper presents a methodology for obtaining a lumped model based on the identification of the transfer functions for constant airflow rate systems. The

Indoor climate and lighting in office buildings are operated using static and conservative setpoints and schedules that are sub-optimal for real occupancy/occupants’ diverse preferences. In contrast, occupant-centric control (OCC) is an operational strategy whereby occupancy/occupants’ preferences are estimated to improve energy efficiency and comfort. This paper develops a practical workflow for implementing

This paper presents a structured, generically applicable, method for using building performance simulation to aid the development of comfort-driven solar shading controls by mapping predicted occupant comfort conditions to sensor measurements. The method uses confusion matrices as a statistical classification approach to facilitate (i) selection of sensor deployment strategies that offer beneficial

Fully defined physics-based building energy models can accurately represent building systems; however, generating models based on high-level parameters is time consuming and simulation time of complex models can be slow. This article discusses the development of a Metamodelling Framework to create metamodels from a building energy modelling dataset. The framework generates metamodels using either linear

Building performance indicators are widely used to guide building design and track and benchmark operational performance. Traditional building performance indicators mostly focus on the energy efficiency perspective. As occupants are the primary building service recipients in residential and most commercial buildings, their comfort and wellbeing are crucial. This study first identified significant

Building performance indicators are widely used to guide building design and track and benchmark operational performance. Traditional building performance indicators mostly focus on the energy efficiency perspective. As occupants are the primary building service recipients in residential and most commercial buildings, their comfort and wellbeing are crucial. This study first identified significant

Courtyards are an effective passive strategy for improving the energy performance of buildings. However, there is a lack of accurate simulation tools for their thermal performance due to their complex thermodynamics. This paper’s contribution is the coupling of a CFD model with a system of differential equations at the walls, governing surface and inner wall temperatures, providing an accurate computation

Predictive residential HVAC controls can reduce a building's energy consumption; however, they require customized thermal models for each home. In this setting, detailed physical models are not practical. Fortunately, the recent availability of fine-grained thermostat data from residential buildings combined with modern machine learning creates an unprecedented opportunity to build customized data-driven

ABSTRACT Given climate change and rapid global development, buildings must meet increasingly stringent environmental performance goals. Although numerous building simulation software assess energy performance, few inform the early stages of design when critical decisions impacting energy use and carbon footprint are made. Underrepresented early design simulation software could potentially significantly

Demand-controlled ventilation (DCV) is a crucial part of ventilation design used in buildings and its effects are widely studied in modern construction. To assess the effect of DCV, accurate models are required. The simulation of CO2-based DCV is still challenging due to the complexity of the system. In addition, in this type of system, there is a prominent interaction between the temperature and CO2

ABSTRACT Estimating the temperature field of a building envelope could be a time-consuming task. The use of a reduced-order method is then proposed: the Proper Generalized Decomposition method. The solution of the transient heat equation is then re-written as a function of its parameters: the boundary conditions, the initial condition, etc. To avoid a tremendous number of parameters, the initial condition

A one-dimensional Finite Difference Model for Breathing Wall components under time dependent Dirichlet boundary conditions is presented. The algorithm undergoes a comprehensive validation against a dynamic analytical model, under either sinusoidal and generically periodic boundary conditions, adopting different airflow velocities and in relation to capacitive and resistive materials alternatively.

Open-air school movement aims to maximize daylighting through fully glazed façade to enhance the well-being and performance of students. Excessive daylight, however, causes discomfort and would, therefore, require shading. While research into optimizing daylighting are numerous; these, however, do not seem to follow a clear and consistent path of investigation. Consequently, the optimized solution

This work proposes a method for developing an accurate correlation to predict thermal comfort (TC) as function of occupant physiological and environmental parameters. This method is implemented for a space that relies on hybrid natural ventilation (NV) and personalized ventilation (PV) cooling. Multivariable linear regression was adopted to develop the TC correlation while retaining variables based

Performing a probabilistic assessment of a building component can easily become computationally inhibitive. To solve this issue, the hygrothermal model can be replaced by a metamodel, which mimics the original model with a strongly reduced calculation time. In this paper, convolutional neural networks are used to predict hygrothermal performance. Because neural networks do not extrapolate well outside

ABSTRACT Fluid temperature predictions of geothermal borefields usually involve temporal superposition of its characteristic g-function, using load aggregation schemes to reduce computational times. Assuming that the ground has linear properties, it can be modelled as a linear state-space system where the states are the aggregated loads. However, the application and accuracy of these models is compromised

ABSTRACT The growing use of intermittent renewable energy sources requires an increased amount of storage capacity to match uncertain generation with uncertain demand. A possible solution is the use of thermal and electrical storages. This paper compares several model formulations: mixed integer linear programs (MILPs), nonlinear programs (NLPs), mixed integer nonlinear programs (MINLPs) for optimizing

Effective and scalable methods for modelling existing non-domestic buildings and their HVAC systems under uncertainty continue to be instrumental in risk-conscious building performance assessment, recommissioning, and retrofit practice. This study makes such an attempt for large buildings with radiator system with a modelling method that builds upon detailed state space models of radiator-heated spaces

In order to improve the performance of a surrogate model-based optimization method for building optimization problems, a new active sampling strategy employing a committee of surrogate models is developed. This strategy selects new samples that are in the regions of the parameter space where the surrogate model predictions are highly uncertain and have low energy use. Results show that the new sampling

Perceptions of occupants to energy use, collected in questionnaire surveys, were used as input variable for building simulations. These perceptions are related to occupant interactions with lighting, plug loads, heating, cooling, windows opening and shading. The simulations were performed to a green-rated (GB) and a non-rated building, in Sydney Australia, with similar characteristics. The simulation

ABSTRACT With recent advancement in energy-based sustainable design of building structures, the need for inclusive yet practical models to integrate resilience and sustainability is increasingly recognized. This paper integrates structural seismic resilience and sustainability assessment methods with whole-building energy simulation techniques to present a new comprehensive decision model for the design

This study presents a new integration of air-source heat pumps, solar collectors, and phase change material tanks regarding the dynamics of outdoor swimming pools, and investigates its application in outdoor swimming pools to extend their availability in the winter in subtropical climates. Since multiple heat sources are used, two issues in the development are addressed: (1) main component sizing and

Power consumption in buildings show nonlinear behaviours that linear models cannot capture, whereas recurrent neural networks (RNNs) can. This ability makes RNNs attractive alternatives for the model-predictive control (MPC) of buildings. However, RNNs are nonlinear and non-smooth functions which makes their use challenging in optimization problems. Therefore, this work systematically investigates

To improve the prediction of the building’s energy performance, it has become necessary to evaluate their interactions with the urban microclimate. This study aims to propose an integrated model in the TRNSYS software with a simplified approach to assess building energy demand, including microclimate interactions on buildings. This model is based on thermoradiative and aeraulic modelling by considering

In this paper, the proper orthogonal decomposition (POD) method and the discrete empirical interpolation method (DEIM) are combined to construct a reduced-order model for a cost-optimal simulation of heat and moisture transfer in building materials. The POD-DEIM performance is assessed via two applications: a relatively simple case study on nonlinear heat conduction and a more complex case study on

The present study aims to examine the effects of medical staff’s turning movements on the number of particles falling onto the patient. A simplified computational fluid dynamics (CFD) model of the operating room was developed and validated based on the published data. An RNG k-ε turbulence model based on the Reynolds-Averaged Navier-Stokes (RANS) equations was used to simulate the airflow, while a

Buildings energy efficiency is highly dependent on occupants’ energy and environmental lifestyle. In this view, this work aims at identifying the potential benefits of human-based energy retrofit strategies, namely human behaviour triggering actions and associated energy awareness, through large-scale surveys and calibrated building dynamic simulation. In detail, a questionnaire is submitted to office

Office lighting installations often inefficiently expend energy illuminating space that is unoccupied and/or already receiving adequate daylight. Illuminance and occupancy sensors can enable substantial energy savings by deploying electric lighting only in proximity to occupants, and at levels required to supplement available daylight. Savings vary based on sensor granularity, daylight availability

Annual luminance maps provide meaningful evaluations for occupants’ visual comfort and perception. This paper presents a novel data-driven approach for predicting annual luminance maps from a limited number of point-in-time high-dynamic-range imagery by utilizing a deep neural network. A sensitivity analysis is performed to develop guidelines for determining the minimum and optimum data collection

This paper analyses structural and acoustic performance interactions of a building covered with a cable net and membrane roof following a multiphysics approach. The problem has three different variables: the roof time-depending deformed shape under wind action (duration 1800 s), the extremely variable position of a singer on the stage (30 s speaker recorded movements were expanded through a 6th order

In the UK, heating systems are the most prominent contributor to residential energy demand, with about 80% of the share. Their representation has thus been at the core of all UK-focussed Housing Stock Energy Models (HSEMs). However, these HSEMs estimate heating demand based on monthly or annual energy balances, with correspondingly approximate representations of heating systems and practices (incl

Operational parameters of air handling units (AHUs) play an important role in the energy and comfort performance of commercial buildings. Current guidelines to determine these parameters are based on heuristics and are not informed by formal optimization. This paper presents a building performance optimization method to derive sequence of operations for multi-zone AHUs. To this end, 27 variants of

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis

Predictive controllers can greatly improve the performance of energy systems in buildings. An important challenge of these controllers is the need of a building model accurate and simple enough for optimization. Grey-box modelling stands as a popular approach, but the identification of reliable grey-box models is hampered by the complexity of the parameter estimation process, specifically for multi-zone

This paper compares Building Control Virtual Test Bed (BCVTB) and Functional Mock-up Interface (FMI) standard to conduct coupled energy modelling and control for academic and research campuses. The intent is to systematically compare BCVTB and FMI. As proof-of-concept demonstration, building energy models of Colorado School of Mines are developed in EnergyPlus and coupled through BCVTB and FMI. The

Developing a computationally efficient but accurate building energy simulation (BES) model is important for many purposes. Model order reduction (MOR) methods are attractive and much more reliable than identification approaches, since it directly extract a lower-dimensional model from a detailed physics-based model without any pre-simulations. However, because of computational and data storage requirements

The present study numerically and experimentally investigates, for the first time in the literature, the thermo-fluid dynamics and ultrafine particle (UFP) concentration in surgical smoke, with diameters smaller than 100 nm, inside an actual operating room (OR) equipped with a turbulent circular diffuser system. The velocity values and temperature fields measured during the experimental analysis at

Planning the operation of large ground source heat pump (GSHP) systems requires accurate models of borehole heat exchangers (BHEs) that are not computationally intensive. In this paper, we propose parameter estimation using measured data as a method to improve the analytical models of BHE. The method was applied to a GSHP system operating for over 3 years. The deviation between modelled and measured

ABSTRACT Active chilled beams (ACBs) are often modelled as generic cooling devices. Due to induction, the air flow discharged from an ACB is several times higher than supplied from the air handling unit, and due to its design, it affects the temperature of the ceiling to a greater extent than an arbitrary cooling device. This paper investigates the impact of taking these features into account when

Occupant behaviour (OB) is recognized as a leading source of uncertainty in building performance predictions. Neglecting the potential influence of uncertainties on building performance could result in erroneous decision-making during the design phase. Therefore, it is essential that uncertainties are appropriately considered within building performance simulation (BPS) models. As for OB, there are

Event-driven optimal control was recently developed for central air-conditioning systems to speed up the response of optimal control to irregular changes in the system optioning conditions. In a time-driven paradigm usually, the optimization is carried out with a constant frequency, however the event-driven optimal control triggers optimization actions by events, which will be essentially defined to

ABSTRACT The World Championship in Cybernetic Building Optimization (WCCBO) was held in 2019 to test participants’ ability to optimize buildings cybernetically. Office buildings with a total floor area of 10,000 m2 were built in cyberspace, one for each of the 33 participating teams. The cyber buildings were controlled by BACnet, and the participants competed to show their operational skills by tuning

Building performance simulation can support parametric explorations of design option spaces. Resources available for modelling and computing often require the reduction of the descriptive information of a design solution at the level of design-space model rather than at that of building model. To obtain that reduction, two design-space models of different scope (for example, one full-scope and simplified

The target of the paper is to study how to devise an efficient discrete-event model for the yearly energy simulation of buildings. Conventionally, software tools use time-driven schemes and many components must be computed at every sampling time-point. Event-driven simulation aims at lowering this burden, by calling only those components whose state is evolving quickly. The article explores a model

This study proposes a replicable approach for evaluating the impact of different weather data sources during the building refurbishment. Starting from a deep energy diagnosis, the numerical model is calibrated by using the weather data and the energy billings of the same year. Then, the performance gap is evaluated due to the adoption of conventional or new weather files defined with data recently