scholarly journals VARIABILITY OF BUILDING SIMULATION RESULTS DEPENDING ON SELECTED WEATHER FILES AND CONDITIONING SET POINTS – A CASE STUDY FOR A RESIDENTIAL BUILDING IN VICTORIA, AUSTRALIA

2016 ◽  
Vol 11 (4) ◽  
pp. 91-108
Author(s):  
Astrid Roetzel
Keyword(s):  
Residential Building ◽  
Building Simulation ◽  
Weather Data ◽  
Data Sets ◽  
Heating And Cooling ◽  
Data Files ◽  
Final Energy Consumption ◽  
Simulation Results ◽  
Simulation Input ◽  
Heating Loads

Building simulation is a powerful way to evaluate the performance of a building. The quality of simulation results however strongly depends on the accuracy of simulation input data. Especially for weather data files and occupant behaviour it is difficult to obtain accurate data. This paper evaluates the variability of building simulation results with regards to different weather data sets as well as different heating and cooling set points for a residential building in Victoria, Australia. Thermal comfort according to ASHRAE Standard 55, final energy consumption and peak cooling and heating loads are assessed. Simulations have been performed with Energy-Plus, and weather data for a multi-year approach have been generated with the software Meteonorm. The results show that different weather files for the same location as well as different conditioning set points can influence the results by approximately a factor of 2.

scholarly journals Experimental and numerical modelling of thermal performance of a residential building in Belgrade

2009 ◽  
Vol 13 (4) ◽  
pp. 245-252 ◽  
Author(s):  
Biljana Vucicevic ◽  
Valentina Turanjanin ◽  
Vukman Bakic ◽  
Marina Jovanovic ◽  
Zana Stevanovic
Keyword(s):  
Thermal Performance ◽  
Residential Building ◽  
Total Surface Area ◽  
Weather Data ◽  
Climatic Data ◽  
Heating Season ◽  
Monthly Basis ◽  
Liquid Petroleum Gas ◽  
U Value ◽  
Heating Loads

The main objective of this paper is to evaluate simulation of thermal performance of a residential 4 floors high building placed in the suburb of Belgrade (ground and 3 upper floors) with it's total surface area of 1410 m2. It's supplied with liquid petroleum gas storage tank as a fuel reservoir since there is automatic gas boiler in each apartment. Measurements have been carried out in first floor apartment (68 m2 heating area) in heating season period. Measured parameters are: inside and outside air temperature and U-value of apartment envelope. Weather data is obtained by using METEONORM, the software package for climatic data calculation based on last 10 years measurements. TRNSYS 16 has been used as the simulation tool. The behavior of the building in terms of heating loads for climate on a daily and monthly basis in heating season is investigated. The calculations show possibility for saving energy by optimization inside temperature during different gas boiler working regimes.

Comparison of Simulated and Actual Energy Use of a Hospital Building in Austria

2014 ◽  
Vol 899 ◽  
pp. 11-15 ◽  
Author(s):  
Nargjil Saipi ◽  
Matthias Schuss ◽  
Ulrich Pont ◽  
Ardeshir Mahdavi
Keyword(s):  
Energy Use ◽  
Energy Performance ◽  
Building Construction ◽  
Weather Data ◽  
Heating And Cooling ◽  
Numeric Simulation ◽  
Demand Information ◽  
Hospital Building ◽  
Heating Loads ◽  
Cooling Loads

This paper compares calculated and measured energy use data (for space heating and cooling) pertaining to a hospital building in Austria. The building's existing energy certificate as well as monitored heating and cooling demand information were acquired from the hospitals administration. Moreover, the energy performance of the building was modeled using a numeric simulation application. Thereby, an extensive effort was made to define model input assumptions (building construction, weather data, internal gains) based on actual circumstances in reality. The results of the study suggest that calculated (energy certificate) and simulated heating loads were reasonably close to actual values, whereas in case of cooling loads considerable discrepancies were observed.

An Hourly Building Simulation Model Aimed at Fuel Cell Applications

2006 ◽  
Author(s):  
Hugh I. Henderson ◽  
Bharathkrishna Karambakkam ◽  
Jeffrey Boyer ◽  
Rhonda Staudt
Keyword(s):  
Fuel Cell ◽  
Simulation Model ◽  
New York State ◽  
Hot Water ◽  
Building Simulation ◽  
Weather Data ◽  
Space Heating ◽  
Simulation Tool ◽  
Water Heating ◽  
Heating And Cooling

The successful widespread adoption of fuel cell systems is highly dependent upon the economics of the installation. This entails closely matching system capabilities with customer requirements. System sizing requires accurate predictions of building thermal and electrical loads. The TRNSYS-based building simulation model presented in this paper was developed to accurately integrate a fuel cell into the space heating, water heating, and cooling equipment in a building. The simulation tool determines water heating, space heating, and cooling loads for a single zone building on an hour-by-hour basis throughout the year using TMY2 weather data. It integrates empirical and theoretical state point models of the components of a fuel cell-based cogeneration and tri-generation system as well as baseline HVAC technologies. The key components include: hot water loops, stratified water tanks, boilers, furnaces, air conditioners, absorption chillers, space conditioning coils, heat rejection equipment, and ventilation controls. Various control options are incorporated to maintain setpoints, stage equipment, and limit power export. Renewable power systems such as PV and wind are also integrated into the model. The TRNSYS calculation engine iterates to find the state of the system for each hour. The simulation tool also includes post-processing capabilities to apply complex electric tariffs, organize annual simulation results, and manage multiple parametric runs. The tool has been developed to optimize the configuration of a fuel cell in a given building application and to complete numerous parametric runs to evaluate the economics of a system in different locations and building applications. This work was funded in part by the New York State Energy Research and Development Authority.

HOW TO USE CROP GROWTH MODEL WOFOST FOR FORECASTING GROWTH AND YIELD OF A CROP

2016 ◽  
Vol 3 (1) ◽  
Author(s):  
LAL SINGH ◽  
PARMEET SINGH ◽  
RAIHANA HABIB KANTH ◽  
PURUSHOTAM SINGH ◽  
SABIA AKHTER ◽  
...  
Keyword(s):  
User Interface ◽  
Graphical User Interface ◽  
Input Data ◽  
Growth And Yield ◽  
Weather Data ◽  
Data Sets ◽  
Crop Growth Model ◽  
Control Center ◽  
Field Crops ◽  
Crop Calendar

WOFOST version 7.1.3 is a computer model that simulates the growth and production of annual field crops. All the run options are operational through a graphical user interface named WOFOST Control Center version 1.8 (WCC). WCC facilitates selecting the production level, and input data sets on crop, soil, weather, crop calendar, hydrological field conditions, soil fertility parameters and the output options. The files with crop, soil and weather data are explained, as well as the run files and the output files. A general overview is given of the development and the applications of the model. Its underlying concepts are discussed briefly.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

scholarly journals Comparison of Factorial and Latin Hypercube Sampling Designs for Meta-Models of Building Heating and Cooling Loads

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 512
Author(s):  
Younhee Choi ◽  
Doosam Song ◽  
Sungmin Yoon ◽  
Junemo Koo
Keyword(s):  
Latin Hypercube Sampling ◽  
Building Design ◽  
Gain Coefficient ◽  
Design Parameters ◽  
Latin Hypercube ◽  
Heating And Cooling ◽  
Factor Design ◽  
Heating Loads ◽  
Cooling Loads ◽  
Interest In Research

Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative to Fractional Factor Design (FFD), since it can improve the accuracy while including the nonlinear effect of design parameters with a smaller size of data. Building energy loads of an office floor with ten design parameters were selected as the meta-models’ objectives, and were developed using the two sampling methods. The accuracy of predicting the heating/cooling loads of the meta-models for alternative floor designs was compared. For the considered ranges of design parameters, window insulation (WDI) and Solar Heat Gain Coefficient (SHGC) were found to have nonlinear characteristics on cooling and heating loads. LHS showed better prediction accuracy compared to FFD, since LHS considers the nonlinear impacts for a given number of treatments. It is always a good idea to use LHS over FFD for a given number of treatments, since the existence of nonlinearity in the relation is not pre-existing information.

scholarly journals Guidelines to Calibrate a Multi-Residential Building Simulation Model Addressing Overheating Evaluation and Residents’ Influence

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 242
Author(s):  
Christoph Schünemann ◽  
David Schiela ◽  
Regine Ortlepp
Keyword(s):  
Simulation Model ◽  
Time Window ◽  
Residential Building ◽  
Simulation Models ◽  
Building Simulation ◽  
Night Time ◽  
Building Performance Simulation ◽  
Starting Point ◽  
3D Simulation Model ◽  
Building Physics

Can building performance simulation reproduce measured summertime indoor conditions of a multi-residential building in good conformity? This question is answered by calibrating simulated to monitored room temperatures of several rooms of a multi-residential building for an entire summer in two process steps. First, we did a calibration for several days without the residents being present to validate the building physics of the 3D simulation model. Second, the simulations were calibrated for the entire summer period, including the residents’ impact on evolving room temperature and overheating. As a result, a high degree of conformity between simulation and measurement could be achieved for all monitored rooms. The credibility of our results was secured by a detailed sensitivity analysis under varying meteorological conditions, shading situations, and window ventilation or room use in the simulation model. For top floor dwellings, a high overheating intensity was evoked by a combination of insufficient use of night-time window ventilation and non-heat-adapted residential behavior in combination with high solar gains and low heat storage capacities. Finally, the overall findings were merged into a process guideline to describe how a step-by-step calibration of residential building simulation models can be done. This guideline is intended to be a starting point for future discussions about the validity of the simplified boundary conditions which are often used in present-day standard overheating assessment.

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