Calibration of a commercial building energy simulation models using energy and weather data

2018 ◽  
Author(s):  
N.N.N. Azmi ◽  
N.A. Ramli ◽  
A. Kassim ◽  
S.A.A. Munaff
Keyword(s):  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Building Energy Simulation ◽  
Commercial Building

scholarly journals Uncertainty Sources and Calculation Approaches for Building Energy Simulation Models

2015 ◽  
Vol 78 ◽  
pp. 2566-2571 ◽  
Author(s):  
Yinchun Ding ◽  
Yang Shen ◽  
Jianguo Wang ◽  
Xing Shi
Keyword(s):  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Uncertainty Sources

Building Energy Simulation with On-Site Weather Station

2016 ◽  
Vol 859 ◽  
pp. 88-92 ◽  
Author(s):  
Radu Manescu ◽  
Ioan Valentin Sita ◽  
Petru Dobra
Keyword(s):  
Energy Consumption ◽  
Energy Demand ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Building Energy Simulation ◽  
Existing Buildings ◽  
Existing Building ◽  
Simulation Tools ◽  
Heating And Cooling

Energy consumption awareness and reducing consumption are popular topics. Building energy consumption counts for almost a third of the global energy consumption and most of that is used for building heating and cooling. Building energy simulation tools are currently gaining attention and are used for optimizing the design for new and existing buildings. For O&M phase in existing buildings, the multiannual average weather data used in the simulation tools is not suitable for evaluating the performance of the building. In this study an existing building was modeled in EnergyPlus. Real on-site weather data was used for the dynamic simulation for the heating energy demand with the aim of comparing the measured energy consumption with the simulated one. The aim is to develop an early fault detection tool for building management.

Building Energy Simulation for LEED Qualification on a Commercial Building in China

2012 ◽  
Vol 193-194 ◽  
pp. 258-269 ◽  
Author(s):  
Ching Hin Law ◽  
Jian Kun Yang ◽  
Xiang Yang Jiang
Keyword(s):  
Energy Consumption ◽  
Energy Cost ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Commercial Building ◽  
Simulation Process

This research introduced and implemented building energy simulation via a case study of a commercial project in China, by considering the green features which can reduce the annual energy consumption of this building. This simulation process was based on the requirement described within LEED EA c1 Optimize Energy Performance. The result concluded that more than 39.41% of energy cost was reduced and thus the project can obtain 16 points from this credit.

Procedures for Calibrating Hourly Simulation Models to Measured Building Energy and Environmental Data

1998 ◽  
Vol 120 (3) ◽  
pp. 193-204 ◽  
Author(s):  
J. S. Haberl ◽  
T. E. Bou-Saada
Keyword(s):  
Goodness Of Fit ◽  
Building Energy ◽  
Building Envelope ◽  
Energy Simulation ◽  
Environmental Data ◽  
Simulation Program ◽  
Weather Data ◽  
Mean Bias Error ◽  
Building Energy Simulation ◽  
Calibration Methods

This paper discusses procedures for creating calibrated building energy simulation programs. It begins with reviews of the calibration techniques that have been reported in the previous literature and presents new hourly calibration methods including a temperature bin analysis to improve hourly x−y scatter plots, a 24-hour weather-daytype bin analysis to allow for the evaluation of hourly temperature and schedule dependent comparisons, and a 52-week bin analysis to facilitate the evaluation of long-term trends. In addition, architectural rendering is reviewed as a means of verifying the dimensions of the building envelope and external shading placement as seen by the simulation program. Several statistical methods are also presented that provide goodness-of-fit indicators, including percent difference calculations, mean bias error (MBE), and the coefficient of variation of the root mean squared error (CV(RMSE)). The procedures are applied to a case study building located in Washington, D. C. where nine months of hourly whole-building electricity data and sitespecific weather data were measured and used with the DOE-2.1D building energy simulation program to test the new techniques. Simulations that used the new calibration procedures were able to produce an hourly MBE of –0.7% and a CV(RMSE) of 23.1% which compare favorably with the most accurate hourly neural network models (Kreider and Haberl, 1994a, b).

A Procedure for Testing the Ability of Whole Building Energy Simulation Programs to Thermally Model the Building Fabric

1995 ◽  
Vol 117 (1) ◽  
pp. 7-15 ◽  
Author(s):  
R. D. Judkoff ◽  
J. S. Neymark
Keyword(s):  
International Energy Agency ◽  
Simulation Models ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Thermal Mass ◽  
Reference Ranges ◽  
Energy Agency ◽  
Hourly Data ◽  
Whole Building Energy Simulation

A procedure was developed for systematically testing whole building energy simulation models and diagnosing the sources of predictive disagreement. Field trials of the method were conducted with a number of detailed state-of-the-art programs by researchers from nations participating in International Energy Agency (IEA) Task 12 and Annex 21. The technique consists of a series of carefully specified test case buildings that progress systematically from extremely simple to relatively realistic. Output values for the cases, such as annual loads, annual maximum and minimum temperatures, peak loads, and some hourly data are compared, and used in conjunction with diagnostic logic to determine the algorithms responsible for prediction differences. The more realistic cases, while geometrically simple, test the ability of the programs to model such combined effects as thermal mass, direct solar gain windows, window shading devices, internally generated heat, infiltration, sunspaces, earth coupling, and deadband and setback thermostat control. The more simplified cases facilitate diagnosis by allowing excitation of particular heat transfer mechanisms. The procedure was very effective at revealing bugs, faulty algorithms, and input errors in a group of building energy simulation programs that may be considered among the world’s best. The output data from the simulation programs can be used as reference ranges for comparing and diagnosing other detailed or simplified design tools.

scholarly journals Integrating climate change into meteorological weather data for building energy simulation

2019 ◽  
Vol 183 ◽  
pp. 749-760 ◽  
Author(s):  
Sleiman Farah ◽  
David Whaley ◽  
Wasim Saman ◽  
John Boland
Keyword(s):  
Climate Change ◽  
Building Energy ◽  
Energy Simulation ◽  
Weather Data ◽  
Building Energy Simulation
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