By Nidhi DhullReviewed by Susha Cheriyedath, M.Sc.Dec 4 2024A recent article published in Buildings addressed the lack of specific energy simulation profiles for accurate energy performance assessment of industrial factories through a detailed building profile investigation. Extended operational data and experimental measurements were used for this investigation in a live factory setting in South Korea.
Study: Investigation of Building Profiles for the Energy Simulation of a Factory Building: A Case Study in South Korea. Image Credit: A9 STUDIO/Shutterstock.com
Background
South Korea aims to lower carbon emissions in the building industry by 32.8% by 2030 relative to 2018 levels. Current efforts to achieve this goal include retrofitting and energy remodeling of existing buildings.
Industrial factory buildings are huge and have high occupancy levels along with the substantial energy demands of their manufacturing processes. However, in contrast to general commercial buildings, energy efficiency in factory buildings is barely explored due to the confidentiality of relevant information safeguarded for corporate security reasons.
Despite the above challenges, impending regulatory sanctions on greenhouse gas emissions and corporate sustainability drive the emerging commitment to enhance energy efficiency in factory buildings. Several studies have employed simulations to study various factors that can improve the energy performance of industrial buildings. However, building characteristics that directly affect its energy performance have not been specifically examined.
Methods
A manufacturing factory in South Korea was selected for this study. A year-long investigation of operational data was performed, and field measurements were recorded in the building. The derived building profile was assessed based on inputs from the Korean government’s building energy performance evaluation program (ECO2).
Several variables were considered for the factory building’s energy simulation. Among these, air change rate per hour (ACH) and zone air temperature profiles were derived from experimental data. Alternatively, internal heat gain, operation schedule, and hot water demand profiles were compiled from the building operation data.
Overall, 7483 and 17450 data points were recorded for the heating and cooling seasons, respectively. The data was preprocessed to minimize noise. MATLAB was utilized for all data processing and analysis tasks.
Long-term vertical and horizontal temperature distribution measurements were conducted to simulate the large factory building zones accurately. This provided essential data on the zones’ thermal characteristics.
After establishing the industrial building profile, the building’s energy performance was assessed and compared with actual energy usage data (Building Energy Efficiency Rating System Operating Regulations of the Republic of Korea) to validate the efficacy of these profiles.
Additionally, the distinct characteristics of the factory building profile were compared with a standard office building profile to determine energy simulation requirements for industrial settings. Finally, the reliability of the developed building profiles was demonstrated by comparing the factory’s actual monthly energy consumption with the energy simulation outcomes.
Results and Discussion
The ACH and temperature setpoints in the factory did not vary significantly from the office norms. A higher ACH in the factory was presumed owing to its structural characteristics; however, the considerably lower surface-to-volume ratio in the factory due to vast open spaces than in typical office buildings contributed to this parity.
Energy simulations assessed the heating and cooling energy requirements based on the detailed building information profiles. Comparing simulation results with actual data revealed a root-mean-squared error of 3.9 kWh/m2 and 7.4 kWh/m2 for the cooling and heating energy consumptions, respectively.
The determination coefficient (R2) for cooling and heating energy consumption was recorded at 98.2% and 94.1%, respectively. Despite some discrepancies observed for heating and cooling in March and August, the simulations exhibited R2 values over 90%, confirming their efficacy in estimating the monthly energy consumption of a factory building.
The monthly heating energy consumption for the office and factory profiles was comparable. However, the monthly cooling energy consumption was lower for the office building profile, resulting in a 2.81% decrease in the average R2 value for simulations using the office profile.
Considering the factory buildings’ longer daily and monthly operation than office buildings, their cooling and heating energy consumption was expected to be higher. However, the factory had 3.29 times more internal heat than the office per unit area. Additionally, the water heating requirement in the office was 20.4 times higher than that in the factory.
Conclusion
Overall, the researchers comprehensively explored the energy simulation profile for factory buildings using empirical operational data and experimental measurements from a manufacturing factory in South Korea.
Building profiles were investigated for energy simulation in a factory characterized by large size and high security. Compared to typical office buildings, factory buildings have minimal information available publicly. Despite this, the energy profiles developed for a factory building are significant for industry stakeholders.
However, focusing on a specific factory building limits the general applicability of this study. The researchers suggest regularly updating factory building profiles by exploring different types of manufacturing facilities through the proposed methodology.
Journal Reference
Lim, H., Park, G.-H., Kim, S., Kim, Y., & Yu, K.-H. (2024). Investigation of Building Profiles for the Energy Simulation of a Factory Building: A Case Study in South Korea. Buildings, 14(12), 3767. DOI: 10.3390/buildings14123767, https://www.mdpi.com/2075-5309/14/12/3767
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