Hourly Calculation Method of Building Energy Demand for Space Heating and Cooling Based on Steady-State Heat Balance Equations

Monstvilas, Edmundas; Stankevičius, Vytautas; Karbauskaitė, Jūratė; Burlingis, Arūnas; Banionis, Karolis

doi:10.3846/13923730.2012.689994

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…One of the most widely-used BEA engines in the world is the DOE-2.2 engine; however, since the BEA engine cannot support a complex building model, a specific algorithm is necessary to analyze a complex building model, and researchers have attempted to analyze complex building models (Sun et al 2002;Tang et al 2006;Monstvilas et al 2012;Suter, Mahdavi 2004;Kim, Yu 2013b). Previous research, however, has been limited in that a specific system or mathematical algorithm must be used that lacks data interoperability with other BEA tools.…”

Section: Introductionmentioning

confidence: 99%

A Process to Divide Curved Walls in Ifc-Bim Into Segmented Straight Walls for Building Energy Analysis

Kim

2015

Journal of Civil Engineering and Management

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The amount of energy that buildings consume is currently attracting significant interest throughout the world, and considerable attention is being devoted to the development of green buildings to reduce energy consumption; however, the current process being used to conduct building energy analysis has a significant shortcoming in that it cannot directly use building information modelling (BIM)-based representational data that includes a curved wall. Currently, the curved wall must be converted into segmented straight walls (SSWs) in the building model in order for the building energy analysis (BEA) program to be able to recognize and use the data. In this paper, we have proposed a segmentation process for curved walls in industry foundation classes (IFC)-based BIM for BEA. The proposed process consists of three sub-processes: 1) extracting data from the IFC model; 2) dividing the curved wall into several segmented straight walls; and 3) generating an INP file as a building description for DOE-2.2-based BEA. The proposed process will enable the engineers who are responsible for BEA to use a BIM-based model directly in the BEA program without having to do additional work. The proposed process can help ensure that the BEA results are accurate and reliable.

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Section: Introductionmentioning

confidence: 99%

A Process to Divide Curved Walls in Ifc-Bim Into Segmented Straight Walls for Building Energy Analysis

Kim

2015

Journal of Civil Engineering and Management

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“…This is an alternative method of evaluating indoor thermal comfort or quantifying the energy demand for heating and cooling of the building [8]. Annual energy demand was calculated on an hourly basis for four zones of NE and SW-facing buildings which were further integrated to obtain the monthly requirement.…”

Section: Heating Cooling Loadmentioning

confidence: 99%

Simulation and Field-Based Study of Thermal Performance of a Building - A Case Study

Malesh

Kamal²,

Yaman³

et al. 2023

IOP Conf. Ser.: Mater. Sci. Eng.

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Concerns about building thermal performance and energy consumption are fast growing as they account for roughly 40% of worldwide annual energy use. Building construction in Nepal is controlled by the National Building Codes (NBC), which focus solely on structural considerations and ignore thermal behaviour. As a result, housing tends to be too much warm and too cold during summer and winter respectively due to the lack of passive heating and cooling mechanisms considered during the construction phase. The Thakle Integrated Settle (TIS), built by the Department of Urban Development and Building Construction (DUDBC) under the National Reconstruction Authority and supported by Oxfam Nepal, was the subject of this research. The building’s performance in the chosen location was analysed using a field and TRNSY simulation-based technique. Using meteorological data from Meteonorm software, the TRNSYS model was created to examine the performance in terms of internal air temperature and heating/cooling load of two buildings with different orientations, e.g., North-East (NE) and South-West (SW). According to simulation results, there is a heating demand that covers roughly 37% of the year, while cooling and comfort conditions were 32% and 31%, respectively. For NE and SW-facing buildings, heating demand was 4.10 MWh and 4.07 MWh, while cooling demand was 1.302 MWh and 1.309 MWh respectively.

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“…Authors in [46] propose a 5R1C thermal model based on EN ISO 13790:2008 and allows the correct estimation of the user profile with limited and not sufficiently precise input data. In [47], the proposed method is compared to EN 13790:2008 and it differs, since it considers additional physical laws for the conversion of solar short-wave thermal radiation energy admitted into the room into thermal energy. Ref.…”

Section: Grey-box Techniquesmentioning

confidence: 99%

Modeling of Heating and Cooling Energy Needs in Different Types of Smart Buildings

2020

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Over the last decades, the growing energy consumption of commercial and residential buildings has considerably increased the energy-related carbon dioxide (CO 2) emissions. At EU level, the Energy Performance of Buildings Directive (EPBD) has introduced the transformation of buildings into nearly zero energy buildings (nZEBs) that cover the majority of their low energy demand by on-site renewable energy sources. In this direction, the project PV-ESTIA ''Enhancing storage integration in buildings with Photovoltaics'' aims at developing and validating various optimal energy management strategies in buildings equipped with Photovoltaics (PV) and storage systems. One of the main requirements for the application of the developed strategies is the accurate computation of energy consumption, and particularly, of heating and cooling energy needs. In this paper, a simple and accurate model based on the ''grey-box'' concept is proposed for the computation of hourly thermal energy needs in different types of premises by using the standard ISO 52016-1:2017. The method's performance is evaluated by comparing the results with those of other simulation programs for ten European cities with climatic variations. It is concluded that the proposed model presents high accuracy on the computation of the operative temperature, since it considers the air temperature, as well as the temperatures and the areas of the internal surfaces. Finally, any deviations with the other simulation tools are due to differences in the internal air temperature, weather data, as well as the approaches of ventilation and shading effects.

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Hourly Calculation Method of Building Energy Demand for Space Heating and Cooling Based on Steady-State Heat Balance Equations

Cited by 5 publications

References 11 publications

A Process to Divide Curved Walls in Ifc-Bim Into Segmented Straight Walls for Building Energy Analysis

A Process to Divide Curved Walls in Ifc-Bim Into Segmented Straight Walls for Building Energy Analysis

Simulation and Field-Based Study of Thermal Performance of a Building - A Case Study

Modeling of Heating and Cooling Energy Needs in Different Types of Smart Buildings

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