Understanding the Importance of Capturing Climate and Occupancy Trends During Concept-Stage Sustainable Building Design

2018 ◽  
Author(s):  
Sean Lin ◽  
Bahaa Albarhami ◽  
Salvador Mayoral ◽  
Joseph Piacenza
Keyword(s):  
Energy Consumption ◽  
Simulation Models ◽  
Building Design ◽  
Building Energy ◽  
Simulation Software ◽  
Phase Iii ◽  
Data Set ◽  
Climate Zones ◽  
Leed Certification ◽  
Actual Energy Consumption

This paper presents a comparison of concept stage computational model predictions to capture how building energy consumption is affected by different climate zones. The California State University, Fullerton (CSUF) Student Housing Phase III, which received a Platinum Leadership in Energy and Environmental Design (LEED) certification for the Building Design and Construction category, and its performance in a LEED California Nonresidential Title 24 (NRT24) and ASHRAE 90.1 climate zones is used as a case study to illustrate the method. Through LEED approved simulation software, the standard compliant energy simulation models are compared to the occupancy scheduled models along with the actual energy consumption in different climate zones. The results provide insight to how variables within student dormitory life affect total building energy usage. Total amount of energy consumed per area is one new factor providing understanding into occupancy trends. This new data set reveals more understanding regarding how and where the energy is consumed to maintain a comfortable learning environment.

Understanding the Effects of Capturing Climate and Occupancy Trends During Concept-Stage Sustainable Building Design

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Sean Lin ◽  
Bahaa Albarhami ◽  
Salvador Mayoral ◽  
Joseph Piacenza
Keyword(s):  
Green Building ◽  
Building Design ◽  
Phase Iii ◽  
State University ◽  
Energy Usage ◽  
Data Set ◽  
Sustainable Building ◽  
Climate Zones ◽  
Leed Certification ◽  
Actual Energy Consumption

Abstract This paper presents a model prediction to capture specifically how energy usage in sustainable buildings on college campuses is affected by different variables of student life. The California State University, Fullerton (CSUF) Student Housing Phase III, which received a Platinum Leadership in Energy and Environmental Design (LEED) certification for the Building Design and Construction category, with its performance in a LEED California Nonresidential Title 24 (NRT24) and ASHRAE 90.1 climate zones, is used as a case study to illustrate the method. Through LEED-approved software, the standard compliant energy models are compared with the occupancy-scheduled models along with the actual energy consumption in different climate zones. The results provide insight into how variables within student dormitory life affect the total building energy usage. The total amount of energy consumed per area is one new factor providing understanding into occupancy trends. This new data set reveals more understanding regarding how and where the energy is consumed to maintain a comfortable learning environment. The LEED certification program is one benchmark used to determine sustainable building design. Designers must adhere to set standards before being awarded a U.S. Green Building Council (USGBC) certification such as LEED. The results from this paper will provide input over which variables within student dormitory life affect the energy usage of the building. With the model results, some solutions are presented to update the LEED project certification as well as to reduce student energy usage.

Understanding the Impact of Climate Zones for Occupancy Trends in Sustainable Housing Designs

2017 ◽  
Author(s):  
Sean Lin ◽  
Bahaa Albarhami ◽  
Salvador Mayoral ◽  
Joseph Piacenza
Keyword(s):  
Simulation Models ◽  
Building Design ◽  
Simulation Software ◽  
Phase Iii ◽  
Energy Usage ◽  
Climate Zones ◽  
Leed Certification ◽  
Sustainable Housing ◽  
Electrical Consumption ◽  
The Impact

The purpose of the paper is to provide a model prediction to capture how energy usage in sustainable buildings on college campuses is affected by different climate zones. A case study focus is on the California State University, Fullerton (CSUF) Student Housing Phase III which received a Platinum Leadership in Energy and Environmental Design (LEED) certification for the Building Design and Construction category. In a previous CSUF study, the energy usage and cost data for the 2014–2015 academic year was compared to the predicted data from the LEED NC 2.2. The comparison revealed there was a small discrepancy, 10%, between the values for predicted electrical consumption versus actual consumption; however, a greater difference, 135%, between the gas consumption exists. Using LEED approved simulation software, the ASHRAE 90.1 and LEED California Nonresidential Title 24 (NRT 24) compliant energy simulation models is compared; the results will provide input over which variables within student dormitory life affect the energy usage of the building. Some solutions may update the LEED project certification as well as reduce student energy usage.

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 Dynamic Simulation-Based Surrogate Model for the Dimensioning of Building Energy Systems

Energies ◽  
2021 ◽  
Vol 14 (21) ◽  
pp. 7141
Author(s):  
Leonidas Zouloumis ◽  
Georgios Stergianakos ◽  
Nikolaos Ploskas ◽  
Giorgos Panaras
Keyword(s):  
Energy Consumption ◽  
Surrogate Model ◽  
Model Fitting ◽  
Energy Systems ◽  
Building Design ◽  
Building Energy ◽  
Thermal System ◽  
Data Set ◽  
Existing Building ◽  
Building Energy Systems

In recent decades, building design and operation have been an important field of study, due to the significant share of buildings in global primary energy consumption and the time that most people spend indoors. As such, multiple studies focus on aspects of building energy consumption and occupant comfort optimization. The scientific community has discerned the importance of operation optimization through retrofitting actions for on-site building energy systems, achieved by the use of simulation techniques, surrogate modeling, as well as the guidance of existing building performance and indoor occupancy standards. However, more knowledge should be attained on the matter of whether this methodology can be extended towards the early stages of thermal system and/or building design. To this end, the present study provides a building thermal system design optimization methodology. A data set of minimum thermal system power, for a typical range of building characteristics, is generated, according to the criterion of occupant discomfort in degree hours. Respectively, a surrogate model, providing a configurable correlation of the above set of thermal system dimensioning solutions is developed, using regression model fitting techniques. Computational results indicate that such a model could provide both desirable calculative simplification and accuracy on par with existing respective thermal load calculation standards and simplified system dimensioning methods.

Research on Energy Consumption Quota for Public Buildings in Hebei Province

2013 ◽  
Vol 361-363 ◽  
pp. 231-234
Author(s):  
Shi Long Liu ◽  
Yue Qun Xu ◽  
De Sheng Ju
Keyword(s):  
Energy Consumption ◽  
Building Energy ◽  
Linear Regression Method ◽  
Public Buildings ◽  
Public Building ◽  
Multiple Linear Regression Method ◽  
Energy Auditing ◽  
Building Area ◽  
The Government ◽  
Actual Energy Consumption

Based on 107 data of public building energy auditing and energy consumption statistics, using multiple linear regression method, this paper given an equation for calculating energy public building consumption quota. It can get energy consumption quota simply and conveniently. The equation was close to actual energy consumption of public buildings. It consider building area, heating degree day (HDD) and building type. The results can be help the government formulate the energy consumption quota for public buildings.

scholarly journals Long-Term Prediction of Weather for Analysis of Residential Building Energy Consumption in Australia

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4805
Author(s):  
Shu Chen ◽  
Zhengen Ren ◽  
Zhi Tang ◽  
Xianrong Zhuo
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Residential Building ◽  
Building Energy ◽  
Space Heating ◽  
Building Energy Consumption ◽  
Climate Zones ◽  
Impact Of Climate Change ◽  
Heating And Cooling ◽  
The Impact

Globally, buildings account for nearly 40% of the total primary energy consumption and are responsible for 20% of the total greenhouse gas emissions. Energy consumption in buildings is increasing with the increasing world population and improving standards of living. Current global warming conditions will inevitably impact building energy consumption. To address this issue, this report conducted a comprehensive study of the impact of climate change on residential building energy consumption. Using the methodology of morphing, the weather files were constructed based on the typical meteorological year (TMY) data and predicted data generated from eight typical global climate models (GCMs) for three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) from 2020 to 2100. It was found that the most severe situation would occur in scenario RCP8.5, where the increase in temperature will reach 4.5 °C in eastern Australia from 2080–2099, which is 1 °C higher than that in other climate zones. With the construction of predicted weather files in 83 climate zones all across Australia, ten climate zones (cities)—ranging from heating-dominated to cooling-dominated regions—were selected as representative climate zones to illustrate the impact of climate change on heating and cooling energy consumption. The quantitative change in the energy requirements for space heating and cooling, along with the star rating, was simulated for two representative detached houses using the AccuRate software. It could be concluded that the RCP scenarios significantly affect the energy loads, which is consistent with changes in the ambient temperature. The heating load decreases for all climate zones, while the cooling load increases. Most regions in Australia will increase their energy consumption due to rising temperatures; however, the energy requirements of Adelaide and Perth would not change significantly, where the space heating and cooling loads are balanced due to decreasing heating and increasing cooling costs in most scenarios. The energy load in bigger houses will change more than that in smaller houses. Furthermore, Brisbane is the most sensitive region in terms of relative space energy changes, and Townsville appears to be the most sensitive area in terms of star rating change in this study. The impact of climate change on space building energy consumption in different climate zones should be considered in future design strategies due to the decades-long lifespans of Australian residential houses.

Application of BIM Technology on Energy Efficiency Building Design

2014 ◽  
Vol 587-589 ◽  
pp. 283-286 ◽  
Author(s):  
Mei Zhang
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Saving ◽  
Design Method ◽  
Building Design ◽  
Building Energy ◽  
Information Modeling ◽  
Building Energy Consumption ◽  
Analysis Software ◽  
Building Model

According to the current application situation and domestic energy of our current building energy efficiency design analysis software, in view of the current traditional energy-saving design method can't meet the need of practical problems, put forward the BIM (building information modeling) analysis technology and building energy consumption are combined, anew design method for energy saving building. Application of BIM technology to create virtual building model contains all the information architecture, the virtual building model into the building energy analysis software, identification, automatic conversion and analyzing a large number of construction data information includes in the model, which is convenient to get the building energy consumption analysis.

scholarly journals Multi-objective Building Design Optimization under Operational Uncertainties Using the NSGA II Algorithm

Buildings ◽  
2020 ◽  
Vol 10 (5) ◽  
pp. 88
Author(s):  
Shobhit Chaturvedi ◽  
Elangovan Rajasekar ◽  
Sukumar Natarajan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Design Optimization ◽  
Building Design ◽  
Building Energy ◽  
Global South ◽  
Efficiency Measure ◽  
Nsga Ii ◽  
Multi Objective ◽  
Energy Efficiency Measure

Operational uncertainties play a critical role in determining potential pathways to reduce the building energy footprint in the Global South. This paper presents the application of a non-dominated sorting genetic (NSGA II) algorithm for multi-objective building design optimization under operational uncertainties. A residential building situated in a mid-latitude steppe and desert region (Köppen climate classification: BSh) in the Global South has been selected for our investigation. The annual building energy consumption and the total number of cooling setpoint unmet hours (h) were assessed over 13,122 different energy efficiency measures. Six Pareto optimal solutions were identified by the NSGA II algorithm. Robustness of Pareto solutions was evaluated by comparing their performance sensitivity over 162 uncertain operational scenarios. The final selection for the most optimal energy efficiency measure was achieved by formulating a robust multi-criteria decision function by incorporating performance, user preference, and reliability criteria. Results from this robust approach were compared with those obtained using a deterministic approach. The most optimal energy efficiency measure resulted in 9.24% lower annual energy consumption and a 45% lower number of cooling setpoint unmet h as compared to the base case.

The Strategies of Passive Energy-Efficiency Design in Low Energy Building

2013 ◽  
Vol 368-370 ◽  
pp. 1318-1321
Author(s):  
Xin Bin Wang ◽  
Jia Ping Liu ◽  
Yu Fu
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Conservation ◽  
Air Conditioning ◽  
Influence Factors ◽  
Building Design ◽  
Building Energy ◽  
Low Energy ◽  
Paper Briefly ◽  
Low Energy Consumption

This paper briefly analyzes the structure and conservation approaches of building energy consumption, analyzes the forming reason and influence factors of heating and air-conditioning energy consumption and proposes the passive energy conservation designing strategies of low energy consumption building. Through the passive methods of building design, envelop enclosure and planning landscape, the goal of last year building low energy conservation can be achieved.

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