scholarly journals Design and development of Building energy simulation Software for prefabricated cabin type of industrial building (PCES)

2018 ◽  
Vol 38 ◽  
pp. 03019 ◽  
Author(s):  
Jun Zhang ◽  
Ri Yi Li
Keyword(s):  
Energy Consumption ◽  
Physical Model ◽  
Building Energy ◽  
Simulation Software ◽  
Energy Simulation ◽  
Industrial Building ◽  
Building Energy Simulation ◽  
Energy Consumption Analysis ◽  
Environment Control ◽  
Prefabricated Building

Building energy simulation is an important supporting tool for green building design and building energy consumption assessment, At present, Building energy simulation software can't meet the needs of energy consumption analysis and cabinet level micro environment control design of prefabricated building. thermal physical model of prefabricated building is proposed in this paper, based on the physical model, the energy consumption calculation software of prefabricated cabin building(PCES) is developed. we can achieve building parameter setting, energy consumption simulation and building thermal process and energy consumption analysis by PCES.

The Influence of Street Geometry on Building’s Energy Consumption in Different Climate Zones

2012 ◽  
Vol 178-181 ◽  
pp. 147-150
Author(s):  
Nan Wang ◽  
Mahjoub Elnimeiri
Keyword(s):  
Energy Consumption ◽  
Urban Planning ◽  
Energy Efficient ◽  
Building Energy ◽  
Simulation Software ◽  
Energy Simulation ◽  
Community Design ◽  
Building Energy Simulation ◽  
Climate Condition ◽  
Climate Zones

This research explores the influence of different street geometry towards reducing the energy consumption in buildings by utilizing building energy simulation software. In different climate condition, the different street geometry has different influence on building’s energy consumption. This influence is quantified in this research. It is found that in three climate zones – Beijing, Shanghai and Guangzhou, the energy consumption of buildings is changed according to different H/W ratio of buildings. This finding determines that the optimum street geometry will be different in these climate zones. The designers should consider such difference before doing architecture or urban planning work. This research will also provide some suggestions and recommendations to the energy-efficient community design based on the findings.

scholarly journals Evaluation of implicit numerical methods for building energy simulation

1998 ◽  
Vol 212 (5) ◽  
pp. 331-342 ◽  
Author(s):  
M E Crowley ◽  
M S J Hashmi
Keyword(s):  
Numerical Methods ◽  
Numerical Method ◽  
Strong Stability ◽  
Building Energy ◽  
Computational Effort ◽  
Simulation Software ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Implicit Solvers ◽  
Simulation Problem

The stability of numerical methods used for finite difference thermal modelling of buildings is discussed. A known instability in a commonly used process is described and alternative numerical methods with suitable stability properties are identified. With a view to selecting the optimum numerical method, the building energy simulation problem is characterized mathematically and appropriate implicit solvers are compared on the basis of accuracy and computational effort using a building-related test problem prepared for this purpose. A recently developed numerical method with the necessary strong stability is found to possess higher computational efficiency than methods frequently used in this application and it is recommended for inclusion in building energy simulation software.

A Multi-Zone Building Energy Simulation of a Data Center Model With Hot and Cold Aisles

2013 ◽  
Author(s):  
Long Phan ◽  
Cheng-Xian Lin ◽  
Mirko Schäfer
Keyword(s):  
Energy Consumption ◽  
Boundary Conditions ◽  
Data Center ◽  
Building Energy ◽  
Energy Simulation ◽  
Building Energy Simulation ◽  
Simulation Code ◽  
Climate Conditions ◽  
Wall Boundary ◽  
Wall Boundary Conditions

In this paper, a building energy simulation code, EnergyPlus, was used to study selected important conditions, i.e. wall boundary conditions and locations, which potentially affect the energy consumption and thermal management of a popular data center model. The data center model having 1120 servers distributed in four rows of rack was investigated under two major climate conditions — hot and humid (Miami, FL), and cool and humid (Chicago, IL), and under five different wall boundary conditions. The data center model was first simulated under a well-mixed single-zone condition as a baseline. Then, a multi-zone approach was proposed to resolve the hot and cold aisles and used to investigate the data center performance. Both monthly and annual overall energy consumption as well as cooling load reports were analyzed and compared among various boundary conditions. In addition, monthly thermal behavior of hot and cold aisle zones within the data center was analyzed. The simulation results show that thermal performance of the data center is significantly affected by locations or climate conditions. The effects of location and wall boundary conditions are particularly appreciable during the summer and winter seasons.

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.

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