Building Simulation Models Research Articles

Net-zero nation: HVAC and PV systems for residential net-zero energy buildings across the United States

This study compared the energy performance and initial cost of photovoltaic (PV) and heating, ventilating, and air-conditioning (HVAC) equipment for a residential net-zero energy building (NZEB) in different climate zones across the United States. We used an experimentally validated building simulation model to evaluate various electrically-powered and commercially-available HVAC technologies. The HVAC accounted for 23.8% to 72.9% of the total building energy depending on the HVAC option and climate zone. Each HVAC configuration was paired with a PV system sized to exactly reach the net-zero energy target, so the economics were compared based on the initial PV + HVAC cost. Mechanical ventilation was considered with and without heat recovery; the heat recovery ventilator (HRV) saved a significant amount of energy in cold winter months and hot summer months, and the energy recovery ventilator (ERV) provided additional benefit for humid zones. The HRV was cost-effective in the cold northern latitudes of Chicago, Minneapolis, Helena, and Duluth, where energy savings reached 17.3% to 19.7%. In other climates, ventilation without recovery was more cost effective, by 1% to 9%, and sometimes even more energy efficient. The ERV was never the lowest cost option. A ground-source heat pump (GSHP) and an air-source heat pump (ASHP) were compared, with the GSHP providing significant energy savings, 24.3% to 39.2%, in heating-dominated climates (Chicago through Duluth). In warmer climates, the GSHP saved little energy or used more energy than the ASHP. The PV + HVAC cost was lower everywhere with the ASHP, though it is possible for colder climates that a carefully sized GSHP and ground loop could be cost-competitive. The energy and cost data as well as the required PV capacity could guide HVAC and PV designs for residential NZEBs in different climate zones.

A method of building simulation model for organizational decision-making and inter-organizational control

This paper presented a method on the configuration of a social simulation model intended for general-purpose application as “inter-system control model”, for analyzing real societies engaged in complex and diverse organizational decision-making. The model in this paper is a micro-agent-based model, configured using one replicator dynamics for each decision-making behavior, whether the agent is an organization or an individual. Through the model in this paper, it is possible to configure broad types of decision-making model by individuals, internal organization of corporations, inter-corporate relations and the national economy. This paper describes a method of social simulation model primarily focusing on an inter-organizational decision-making and demonstrates a configuration method for this simulation model using case studies on long-term economic growth model with technological change.

Selecting statistical indices for calibrating building energy models

A well-known problem in the dynamic simulation of buildings energy consumption are the discrepancies between the simulated and measured data, which call for calibration techniques to obtain more accurate and reliable building models. The most recognized calibration techniques use statistical indices to assess and improve the quality of simulation models. While there are already well known statistical indices available to evaluate the simulation outputs, the combination of indices offers potential for further improvements in this field. To assess the procedure of calibrating building simulation models, we present a ranking of six tested statistical indices and their combinations (63 statistical metrics), produced by an automated evaluation procedure, in the specific case of calibrating to annual heat demand curves. The developed evaluation procedure is also able to account for eventual deterioration of other statistical metrics, which are not tuned during the calibration. We apply the new method in dynamic, hourly simulations to a use case with 200 buildings, for which extensive measurement data are available. Based on the generated ranking, we recommend using combinations of four statistical indices: the Coefficient of Variation of Root Mean Square Error (CV(RMSE)), the Normalized Mean Error (NME), the standardized contingency coefficient (Cχ2) and the coefficient of determination (R2). In our use case, these combinations lead to better results than the commonly used indices CV(RMSE) and Normalized Mean Bias Error (NMBE). In addition, we could show that it is beneficial to use another index for evaluation than for calibration, because it detects eventual deterioration of the simulation output results.

Towards energy-efficient retrofit of council housing in London: Assessing the impact of occupancy and energy-use patterns on building performance

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

Utilizing thermal building mass for storage in district heating systems: Combined building level simulations and system level optimization

Higher shares of intermittent renewable energy in energy systems have raised the issue of the need for different energy storage solutions. The utilization of existing thermal building mass for storage is a cost-efficient solution. In order to investigate its potential, a detailed building simulation model was coupled with a linear optimization model of the energy system. Different building archetypes were modelled in detail, and their potential preheating and subsequent heat supply cut-off periods were assessed. Energy system optimization focused on the impact of thermal mass for storage on the energy supply of district heating. Results showed that longer preheating time increased the possible duration of cut-off events. System optimization showed that the thermal mass for storage was used as intra-day storage. Flexible load accounted for 5.5%–7.7% of the total district heating demand. Furthermore, thermal mass for storage enabled more solar thermal heating energy to be effectively utilized in the system. One of the sensitivity analyses showed that the large-scale pit thermal energy storage and thermal mass for storage are complimentary. The cut-off duration potential, which did not compromise thermal comfort, was longer in the newer, better insulated buildings, reaching 6 h among different building archetypes.

Design and analysis of PCM based radiant heat exchanger for thermal management of buildings

The present study focuses on the thermal performance of encapsulated phase change material (PCM) based heat exchanger for thermal management of building in Indian conditions. Heat transfer characteristics of the encapsulated PCM based heat exchanger is investigated experimentally and compared vis-à-vis thermally activated roof and radiant panel systems. Experiments are performed on a scaled down concrete cubical test chamber with a window facing the north direction. It is found that the encapsulated PCM based heat exchanger is able to reduce heat gain of the test chamber by approximately 50% as well as mean air temperature by more than 6 °C. The encapsulated PCM based heat exchanger is found more beneficial in flattening the peak for longer duration and reducing the fluctuation in mean air temperature of the test chamber. The developed building simulation model is validated with the experimental results, which is used in parametric studies to identify the effect of different parameters on the average air temperature in the test chamber. The duration of stabilization period can be kept constant by increasing PCM thickness linearly with the increment in thermal load of the test chamber. The inlet water temperature to the PCM based heat exchanger is found to be the most influential parameter affecting the mean air temperature of the test chamber, whereas thermal conductivity of walls and length of pipe in heat exchanger have minimal effect comparatively. Further, a ground heat exchanger is incorporated with the encapsulated PCM based heat exchanger to investigate the effectiveness of ground heat exchanger in discharging the heat load carried by the working fluid.

ЭФФЕКТИВНЫЙ АЛГОРИТМ ГЕНЕРАЦИИ СЛУЧАЙНЫХ ВЕЛИЧИН С КУСОЧНО-ЛИНЕЙНЫМИ ПЛОТНОСТЯМИ РАСПРЕДЕЛЕНИЯ

The PURPOSE of the article is to improve the efficiency of simulation modeling in various subject domains through the use of piecewise linear functions that allow high accuracy in the determination of arbitrary random variables. METHODS. It is proposed to use piecewise linear functions to specify the density of random variables under the transformation of a standard random variable to build simulation models. RESULTS. Based on the type of the random variable density specified by a piecewise linear function three algorithms of action sequence have been proposed for generating the mixture of the components that must have a defined discrete probability distribution. CONCLUSION. Due to their versatility the piecewise linear functions when applied provide sufficiently high generation accuracy of arbitrary random variables. A high simulation efficiency of piecewise-linear functions can improve the accuracy and adequacy of simulation models in different subject domains.

Volume element model for 3D dynamic building thermal modeling and simulation

We present herein the development, experimental validation, and application of a volume element model for 3D dynamic building thermal simulation. The 3D spatial domain in the VEM is discretized with lumped hexahedral elements using ray crossings and ray/triangle intersection techniques that yield sufficiently accurate geometric representation of a building. Subsequently, energy balance is applied to each element in the mesh, and the resulting system of ordinary differential equations is integrated in time to obtain spatiotemporal indoor temperature and relative humidity fields. In this work, we adjusted the model by comparing the simulated indoor air temperatures to the experimental measurements as we calibrated model parameters with high uncertainty. The adjusted model was validated using different experimental data sets, and the numerical results were in a good agreement with the measurements. We employed the validated model to conduct a case study in which the sensible heat gain and loss as well as the time lag were evaluated as functions of different envelope thermal masses. Results showed the trivial effect of floor thermal mass on heat gain, and the changes in sensible heat gain and envelope thermal mass were not linearly proportional, alluding the existence of an optimal envelope design.

A python framework for multi-agent simulation of networked resource systems

Modelling managed resource systems can involve the integration of multiple software modules into a single codebase. These modules are often written by non-software specialists, using heterogeneous terminologies and modelling approaches. One approach to model integration is to use a central structure to which each external module connects. This common interface acts as an agreed mode of communication for all contributors. We propose the Python Network Simulation (Pynsim) Framework, an open-source library for building simulation models of networked systems. Pynsim's central structure is a network, but it also supports non-physical entities like organisational hierarchies. We present two case studies using Pynsim which demonstrate how its use can lead to flexible and maintainable simulation models. First is a multi-agent model simulating the hydrologic and human components of Jordan's water system. The second uses a multi-objective evolutionary algorithm to identify the best locations for new run-of-river power plants in Switzerland.

Thermal and Electrical Characterization of a Semi-Transparent Dye-Sensitized Photovoltaic Module under Real Operating Conditions

Dye-sensitized solar cell technology is having an important role in renewable energy research due to its features and low-cost manufacturing processes. Devices based on this technology appear very well suited for integration into glazing systems due to their characteristics of transparency, color tuning and manufacturing directly on glass substrates. Field data of thermal and electrical characteristics of dye-sensitized solar modules (DSM) are important since they can be used as input of building simulation models for the evaluation of their energy saving potential when integrated into buildings. However, still few studies in the literature provide this information. The study presented here aims to contribute to fill this lack providing a thermal and electrical characterization of a DSM in real operating conditions using a method developed in house. This method uses experimental data coming from test boxes exposed outdoor and dynamic simulation to provide thermal transmittance (U-value) and solar heat gain coefficient (SHGC) of a DSM prototype. The device exhibits a U-value of 3.6 W/m2·K, confirmed by an additional measurement carried on in the lab using a heat flux meter, and a SHGC of 0.2, value compliant with literature results. Electrical characterization shows an increase of module power with respect to temperature resulting DSM being suitable for integration in building facades.

Impact of long-term operation of ground-source heat pump on subsurface thermal state in urban areas

Long-term operation of a ground-source heat pump (GSHP) under a load imbalance condition can lead to thermal buildup or depletion; consequently, this results in performance degradation. In addition, in urban areas where building densities are considerably high with building sites in close proximity to each other, thermal intrusion problems can occur. Under the assumption that GSHPs are used in all the buildings in a city with the same cooling dominant load condition, we assessed the effect of the long-term operation of a GSHP on the subsurface thermal state. Using a coupled simulation scheme that combined a building simulation and numerical borehole heat exchanger (BHE) model, ten years of GSHP operation was simulated under the condition that the cooling load assigned to a BHE is twice the heating load. In the numerical model, the top and bottom axial heat transfer was explicitly considered; a ground heat balance model was integrated into the numerical model as a ground surface boundary condition to examine subsurface thermal behavior realistically. Results showed that detailed consideration of the surface boundary condition plays an important role in a long-term simulation. Moreover, based on the results, possible future problems that may occur in an urban area were discussed.

New 3D model based urban energy simulation for climate protection concepts

Climate protection concepts for cities and regions are designed to establish CO2 emission baselines and develop measures for climate change mitigation. Up to now such concepts were based on aggregated consumption and emission data and only qualitative estimations of the effect of measures were possible. To better quantify the impact of mitigation measures, a large amount of data on the building stock is needed. Very powerful analysis possibilities for an energetic and economic evaluation of scenarios arise, if continuously growing data stock organized in geographical information systems are combined with simulation models of buildings and energy systems. In this work, 3D data models in CityGML format of the entire building stock of Ludwigsburg, a German county with 34 municipalities, were used and enriched with building’s year of construction and its function to allow an automatized quantifying the climate protection indicators. In this regard, the heating demand of each individual building in the region in the current state and after two refurbishment scenarios are calculated. In addition, the local solar photovoltaic potential is determined, as the exact size and orientation of each building surface is in the 3D model available. Besides, some new methodologies are described to better quantify the costs and benefits of CO2 mitigation strategies on a local or regional level and to support decision making.

Using PFEP For Simulation Modeling of Production Systems

Paper focuses on simulation modeling of production systems. Author describes how to use PFEP (Plan for Every Part) to automate building of simulation models of production systems. First section of paper concentrates on the analysis of standard approaches to modeling production systems proposed in simulation programs offered on the market. In next section the idea of lean thinking – continuous flow is presented. The basis of this thinking is formed by Plan For Every Part. The main contribution of this paper is to explain how to use the PFEP for simulation modeling. The example of forming simulation model based on PFEP is presented as last section of the paper. Data from automotive industry were used to build this sample model.

Effect of air chamber and oil properties on damping characteristics of single-tube pneumatic shock absorber

PurposeThe shock absorber is an important component of vehicle suspension that attenuates the vehicle vibration. Its running state directly affects the performance of the vehicle suspension. The purpose of this paper is to quantitatively study the relationship between damping characteristics and air chamber and oil properties in single-tube pneumatic shock absorber.Design/methodology/approachCombined with the principle of fluid dynamics and hydraulic transmission technology, the rebound stroke and compression stroke mathematical models, and damping characteristics simulation model are established to investigate the effect of the air chamber and oil property on damping characteristics.FindingsResearch results show that the initial pressure of the air chamber is the key parameter which influences the damping characteristics of the shock absorber. The change of the initial pressure has more impact on damping force, and less impact on the speed characteristic; the initial volume of the air chamber almost has no effect on the damping characteristics. The density and viscosity of the oil have certain influence on the damping characteristics. Therefore, selecting suitable damping oil is very important.Originality/valueUsing Matlab/Simulink software to build simulation models, its results are very accurate. The conclusions can provide a theoretical reference for the structure design of a single-tube pneumatic shock absorber.

Reducing cooling load of buildings in the tropical climate through window glazing: A model to model comparison

The comparison studies among various building simulation models are always the research interest for various researchers though most of them are based on a general overview. Here we compared two popular building simulation models TRNSYS & eQUEST for a multizone building to judge the relative accuracy of the models. The base case building having 1465.8m2 area is situated in a tropical climate zone of India. Both the models were validated with actual and simulated annual energy consumption data of the case building and a model to model comparison has also been performed. The RMSE values for both TRNSYS & eQUEST were found varying between 2.1–12.5% and the Relative Error was found varying −19.6% to 18.0% respectively. It was also found that TRNSYS predict more accurately the total energy consumption of building than eQUEST in this case study. However the main aim of this paper is to quantify the energy saving potential of five different type of single and double glazing glasses especially in case of tropical climate condition through two types of simulation models. Five different types of commercially available window glasses were designed using LBNL-Window7 simulation tool and validated with lab tested results. The percentage reduction of electrical energy consumption due to retrofitting of five types window glasses have also been presented separately for both the simulation models. Both the models revealed that SHGC is more dominating factor than U-value to reduce cooling load of building energy.

Energy-Efficient Retrofitting Strategies for Residential Buildings in hot climate of Oman

The aim of this work is to investigate the potential of energy-efficient retrofitting strategies for residential buildings in Oman. An existing residential building located in hot climate with a built-up area of 212 m2 was selected. A building simulation model was created in DesignBuilder software. The model was then calibrated using actual electrical bills and measured weather data for year 2014. The calibrated model was subsequently used to evaluate different energy-efficient retrofitting strategies including the AC efficiencies, using insulations for both walls and roof, upgrading to LED lights, and improving the air tightness of the house. It was concluded that when combing the best strategy from each category, the annual energy consumption of the building can be reduced by as much as 42.5%. This significant reduction in energy consumption can help both the policy makers at governmental institutions and owners to move forward for large retrofitting campaigns to solve the current energy dilemma.

Influence of Buildings Configuration on the Energy Demand and Sizing of Energy Systems in an Urban Context

Energy interaction among buildings play a vital role when considering the energy demand at neighbourhood or urban scale which notably influence the energy system sizing problem. The proper representation of buildings and their effects such as drag force effects, generation of turbulence, shading etc. are crucial in the evaluation of building energy demand and subsequently in energy system sizing. This is not practiced in present literature. To achieve this, we couple a meteorological model, a building energy model and an energy system tool. We show that the use of local climatic data and urban planning scenario have a significant impact on the design of energy systems. More importantly, the results of the study show that co-simulation platform coupling meteorological model, building simulation model and energy system designing model can help to design energy efficient neighbourhoods with more renewable energy integration.

Energy Management Strategies for a Governmental Building in Oman

This work describes the outcome of a study that has been performed to reduce the energy consumption of a library building in a hot climate of Oman. The project follows a systematic approach of collecting data from the project and maintenance department, conducting an energy audit and generating a building simulation model. The building has three floors with a total floor area of 2756 m2 and its average yearly consumption of 1397 MWh. The average energy-use-intensity (EUI) for this building is 507kWh/m2/year. Energy audit has identified many energy-retrofitting strategies including replacing the current florescent lights with LED, switching the air conditioning systems outside the occupancy hours, increase the thermostat setpoint, and reduce the air infiltration. Based on the field measurements and observations, building energy model was generated using DesignBuilder and was subsequently calibrated. Using the calibrated model, several energy management opportunities (EMOs) were evaluated. Only four top most energy management opportunities were top listed because they were technically and economically feasible. The EMOs include adjusting the thermostat setpoint, change the air conditioning operation schedules, replace the fluorescent lights with LED and increase the airtightness. The results show that the energy consumption can be reduced as much as 38.5%.

An efficiency improvement in warehouse operation using simulation analysis

In general, industry requires an efficient system for warehouse operation. There are many important factors that must be considered when designing an efficient warehouse system. The most important is an effective warehouse operation system that can help transfer raw material, reduce costs and support transportation. By all these factors, researchers are interested in studying about work systems and warehouse distribution. We start by collecting the important data for storage, such as the information on products, information on size and location, information on data collection and information on production, and all this information to build simulation model in Flexsim® simulation software. The result for simulation analysis found that the conveyor belt was a bottleneck in the warehouse operation. Therefore, many scenarios to improve that problem were generated and testing through simulation analysis process. The result showed that an average queuing time was reduced from 89.8% to 48.7% and the ability in transporting the product increased from 10.2% to 50.9%. Thus, it can be stated that this is the best method for increasing efficiency in the warehouse operation.

An efficiency improvement in warehouse operation using simulation analysis

In general, industry requires an efficient system for warehouse operation. There are many important factors that must be considered when designing an efficient warehouse system. The most important is an effective warehouse operation system that can help transfer raw material, reduce costs and support transportation. By all these factors, researchers are interested in studying about work systems and warehouse distribution. We start by collecting the important data for storage, such as the information on products, information on size and location, information on data collection and information on production, and all this information to build simulation model in Flexsim® simulation software. The result for simulation analysis found that the conveyor belt was a bottleneck in the warehouse operation. Therefore, many scenarios to improve that problem were generated and testing through simulation analysis process. The result showed that an average queuing time was reduced from 89.8% to 48.7% and the ability in transporting the product increased from 10.2% to 50.9%. Thus, it can be stated that this is the best method for increasing efficiency in the warehouse operation.