Towards fast energy performance evaluation: A pilot study for office buildings

2016 ◽  
Vol 121 ◽  
pp. 104-113 ◽  
Author(s):  
Jiachen Mao ◽  
Yiqun Pan ◽  
Yangyang Fu
Keyword(s):  
Performance Evaluation ◽  
Pilot Study ◽  
Energy Performance ◽  
Office Buildings

scholarly journals Energy and Greenhouse Gas Savings for LEED-Certified U.S. Office Buildings

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 749
Author(s):  
John H. Scofield ◽  
Susannah Brodnitz ◽  
Jakob Cornell ◽  
Tian Liang ◽  
Thomas Scofield
Keyword(s):  
Greenhouse Gas ◽  
Energy Use ◽  
Energy Savings ◽  
Electric Energy ◽  
Building Energy ◽  
Energy Performance ◽  
Office Buildings ◽  
Ghg Emission ◽  
Site Energy ◽  
New Construction

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED points awarded for energy optimization. This analysis uncovered minimal correlation, i.e., an R2 < 1% for New Construction (NC) and Core and Shell (CS), and 8% for Existing Euildings (EB). The total measured site energy savings for LEED-NC and LEED-CS was 11% lower than projected while the total measured source energy savings for LEED-EB was 81% lower than projected. Only LEED offices certified at the gold level demonstrated statistically significant savings in source energy and greenhouse gas emissions as compared with non-LEED offices.

scholarly journals A Fundamental Study on the Development of New Energy Performance Index in Office Buildings

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2064
Author(s):  
Jin-Hee Kim ◽  
Seong-Koo Son ◽  
Gyeong-Seok Choi ◽  
Young-Tag Kim ◽  
Sung-Bum Kim ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Requirement ◽  
Energy Performance ◽  
Office Buildings ◽  
Light Transmittance ◽  
Wall Structure ◽  
Fundamental Study ◽  
Future Studies ◽  
U Value ◽  
The Impact

Recently, there have been significant concerns regarding excessive energy use in office buildings with a large window-to-wall ratio (WWR) because of the curtain wall structure. However, prior research has confirmed that the impact of the window area on energy consumption varies depending on building size. A newly proposed window-to-floor ratio (WFR) correlates better with energy consumption in the building. In this paper, we derived the correlation by analyzing a simulation using EnergyPlus, and the results are as follows. In the case of small buildings, the results of this study showed that the WWR and energy requirement increase proportionally, and the smaller the size is, the higher the energy sensitivity will be. However, results also confirmed that this correlation was not established for buildings approximately 3600 m2 or larger. Nevertheless, from analyzing the correlation between the WFR and the energy requirements, it could be deduced that energy required increased proportionally when the WFR was 0.1 or higher. On the other hand, the correlation between WWR, U-value, solar heat gain coefficient (SHGC), and material property values of windows had little effect on energy when the WWR was 20%, and the highest effect was seen at a WWR of 100%. Further, with an SHGC below 0.3, the energy requirement decreased with an increasing WWR, regardless of U-value. In addition, we confirmed the need for in-depth research on the impact of the windows’ U-value, SHGC, and WWR, and this will be verified through future studies. In future studies on window performance, U-value, SHGC, visible light transmittance (VLT), wall U-value as sensitivity variables, and correlation between WFR and building size will be examined.

scholarly journals Modeling Energy Efficiency Performance and Cost-Benefit Analysis Achieving Net-Zero Energy Building Design: Case Studies of Three Representative Offices in Thailand

2021 ◽  
Vol 13 (9) ◽  
pp. 5201
Author(s):  
Kittisak Lohwanitchai ◽  
Daranee Jareemit
Keyword(s):  
High Efficiency ◽  
Energy Gap ◽  
Cost Benefit ◽  
Building Design ◽  
Energy Performance ◽  
Office Buildings ◽  
Zero Energy ◽  
Zero Energy Building ◽  
Investment Cost ◽  
High Investment

The concept of a zero energy building is a significant sustainable strategy to reduce greenhouse gas emissions. The challenges of zero energy building (ZEB) achievement in Thailand are that the design approach to reach ZEB in office buildings is unclear and inconsistent. In addition, its implementation requires a relatively high investment cost. This study proposes a guideline for cost-optimal design to achieve the ZEB for three representative six-story office buildings in hot and humid Thailand. The energy simulations of envelope designs incorporating high-efficiency systems are carried out using eQuest and daylighting simulation using DIALux evo. The final energy consumptions meet the national ZEB target but are higher than the rooftop PV generation. To reduce such an energy gap, the ratios of building height to width are proposed. The cost-benefit of investment in ZEB projects provides IRRs ranging from 10.73 to 13.85%, with payback periods of 7.2 to 8.5 years. The energy savings from the proposed designs account for 79.2 to 81.6% of the on-site energy use. The investment of high-performance glazed-windows in the small office buildings is unprofitable (NPVs = −14.77–−46.01). These research results could help architects and engineers identify the influential parameters and significant considerations for the ZEB design. Strategies and technical support to improve energy performance in large and mid-rise buildings towards ZEB goals associated with the high investment cost need future investigations.

scholarly journals Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1049
Author(s):  
Zhang Deng ◽  
Yixing Chen ◽  
Xiao Pan ◽  
Zhiwen Peng ◽  
Jingjing Yang
Keyword(s):  
Large Scale ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Modeling ◽  
Office Buildings ◽  
Building Energy Modeling ◽  
Downtown Area ◽  
Point Of Interest

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.

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