Building energy retrofits under capital constraints and greenhouse gas pricing scenarios

Dahlhausen, Matthew; Heidarinejad, Mohammad; Srebric, Jelena

doi:10.1016/j.enbuild.2015.08.046

Cited by 25 publications

(13 citation statements)

References 10 publications

(11 reference statements)

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“…Furthermore, a simple payback period analysis (SPP) can be utilized from previous studies [33][34][35][36]. Wang et al [37] defined as the variables to be optimized based on the minimum simple payback period which Dahlhausen et al [38] analyzed the financial performance in their study. Weissbach et al [39] identified the simple payback period as energy payback time.…”

Section: Original Research Papermentioning

confidence: 99%

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Techno‐economic Analysis of a More Efficient Hydrogen Generation System Prototype: A Case Study of PEM Electrolyzer with Cr‐C Coated SS304 Bipolar Plates

2019

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This study presents a more efficient and innovative prototype of a hydrogen generation system using proton exchange membrane (PEM) electrolyzer. The aim of this study is to generate hydrogen gas energy that conducts the chemical reaction by electrolytic movements as well as to design a system that generates energy with H2 through new technology. The Cr‐C coated SS304 bipolar plates were used in the electrolysis cells and the septic mixture (urea, ammonia, methyl alcohol) was used in the electrolyzer as a chemical solution to make the hydrogen production more efficient and cost effective. The super strong magnets were also mounted on the outer surface of the electrolysis cells to improve the performance and efficiency. The performance of the electrolyzer was determined by operating the current and voltage parameters. The results were collected through experiments and the optimization of the different parameters. In this prototype study, the production of hydrogen gas in the system (1 MW) through the presented system was found to be as 6 m3 h−1 and the simple payback period (SPP) was calculated as 2.32 y. These results indicate that this system can produce hydrogen more efficiently and economically.

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Section: Original Research Papermentioning

confidence: 99%

“…Weissbach et al [39] identified the simple payback period as energy payback time. The simple payback period is as follows [33][34][35][36][37][38][39]:…”

Section: Original Research Papermentioning

confidence: 99%

Techno‐economic Analysis of a More Efficient Hydrogen Generation System Prototype: A Case Study of PEM Electrolyzer with Cr‐C Coated SS304 Bipolar Plates

2019

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“…There are many different ways to reduce greenhouse gas emissions from buildings. High-performance buildings have been regarded as one of the most advanced and effective ways of reducing greenhouse gas emissions [6][7][8]. The successful implementation of high-performance building requires the application of renewable energy systems (RES), as well as passive building design approaches [9,10].…”

Section: Introductionmentioning

confidence: 99%

Optimal Decision-Making of Renewable Energy Systems in Buildings in the Early Design Stage

Baek

Lee

2019

Sustainability

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Renewable energy systems (RES) in buildings should be designed carefully, not only because of the need for an optimal design, but also to comply with related laws. Therefore, the design of RES in the buildings requires close collaboration between architects and engineers from the beginning of the design process. To support such collaboration, this study proposes a simplified design method for RES in buildings during the early design stage. By using the proposed design method, design alternatives that meet the required energy standards as suggested by law are first generated. Further designs are made to evaluate the performance and cost of the design alternatives and to find the optimal types of RES for the building. The study also uses a case study to verify the applicability of the design method to the early design stage. Although the performance and cost of the different design alternatives are similar, the implementation of each type of RES in each design alternative is different. Nonetheless, by analyzing performance patterns and the cost ratio of each type of RES in each design alternative, the study allows the most suitable type of RES to be chosen for the building.

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“…The specific consumers of the electric energy are important to determine because the building energy modeling goal is to ultimately predict performance or choose energy conservation measures. Appropriate attribution is needed to be able to choose between component replacement and adjusted control scheme measures, especially when defining appropriate energy efficiency measures [20][21][22][23]. Therefore, this study aims to provide a novel method to accurately represent occupancy rates in building energy models, resulting in a reliable model calibration.…”

Section: Introductionmentioning

confidence: 99%

Building energy model calibration with schedules derived from electricity use data

et al. 2017

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Building energy models can accurately predict energy performance of buildings, if properly calibrated. This study developed and demonstrated a novel method to calibrate building energy models based on the occupancy and plug-load schedules derived from metered electric use data. Importantly, this study also proposed an occupancy assessment method applicable to resource limited situation when a building sub-metering system is not available. Furthermore, the developed method can facilitate accurate predictions of building energy performance without a requirement to simultaneously monitor energy use and occupancy rates. The method development process used data from an office type building (OB1), and further verified the method accuracy with data from two campus buildings (CB1 and CB2). The developed method is novel because it considers interactions of the validated modeled occupancy patterns, processed electricity use patterns, and the calibrated building energy model results at the hourly level. This approach allows addressing limitations in the current studies that are not fully capable of modeling occupancy patterns, electricity use patterns, and calibrated building energy models with this level of granularity. The accuracy of the building energy modeling results increases with the derived occupancy schedules and plug-loads. Specifically, the Coefficient of Variation Root Mean Square Error (CVRMSE) of OB1 building energy modeling results improved from 21% to 12% compared to the modeling results obtained with default schedules. The results from case study buildings CB1 and CB2 show that the accuracy of modeling results increased as the hourly electricity CVRMSE decreased from 128% to 31% and from 156% to 16%, respectively. These improvements are significant, while the

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Building energy retrofits under capital constraints and greenhouse gas pricing scenarios

Cited by 25 publications

References 10 publications

Techno‐economic Analysis of a More Efficient Hydrogen Generation System Prototype: A Case Study of PEM Electrolyzer with Cr‐C Coated SS304 Bipolar Plates

Techno‐economic Analysis of a More Efficient Hydrogen Generation System Prototype: A Case Study of PEM Electrolyzer with Cr‐C Coated SS304 Bipolar Plates

Optimal Decision-Making of Renewable Energy Systems in Buildings in the Early Design Stage

Building energy model calibration with schedules derived from electricity use data

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