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| Creator | Title | Description | Subject | Date | ||
|---|---|---|---|---|---|---|
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Didier, Richard C. | Linking microclimate and energy use with a low cost wall mounted measurement system | Urban microclimate plays a critical role in overall urban energy demand and efficiency. At the building scale, energy use and internal conditions are directly impacted by local microclimate. The direct link between building energy use and local microclimate is through building envelope heat fluxes. ... | Microclimate; Energy; Temperature; Humidity; Arduino; EnergyPlus | 2016-06 |
| 2 |
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Rahman, Aowabin | Predicting fuel consumption for commercial building with machine learning algorithms | This paper presents a modeling framework that uses machine learning algorithms to make longterm, i.e. one year-ahead predictions, of fuel consumption in multiple types of commercial prototype buildings at one-hour resolutions. Weather and schedule variables were used as model inputs, and the hourly ... | Building energy modeling; Machine learning; Prediction; Heating load; Data-driven modeling | 2017-08 |
| 3 |
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Rahman, Aowabin | Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks | This paper presents a recurrent neural network model to make medium-to-long term predictions, i.e. time horizon of ≥ 1 week, of electricity consumption profiles in commercial and residential buildings at one-hour resolution. Residential and commercial buildings are responsible for a significant fr... | Building Energy Modeling; Machine learning; Recurrent neural networks; Deep learning; Electric load prediction | 2017 |
| 4 |
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Thomas, Tran T. D. | Evaluation of renewable energy technologies and their potential for technical integration and cost-effective use within the U.S. energy sector | Energy demands, environmental impacts of energy conversion, and the depletion of fossil; fuels are constant topics of discussion in the energy industry. Renewable energy technologies; have been proposed for many years to address these concerns. However, the transformation; from traditional methods o... | Renewable energy; Power generation; Electrical grid; Emerging energy systems; System integration | 2017-07 |
| 5 |
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Tran, Thomas T.D. | Incorporating performance-based global sensitivity and uncertainty analysis into LCOE calculations for emerging renewable energy technologies | Assessing system costs for power generation is essential for evaluating the economical aspect of energy resources. This paper examines traditional and renewable energy resources under uncertainty and variability of input variables. The levelized cost of electricity (LCOE) of each technology is compu... | Renewable energy technologies; LCOE levelized cost of electricity | 2018-02-14 |
| 6 |
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Rahman, Aowabin | Predicting heating demand and sizing a stratified thermal storage tank using deep learning algorithms | This paper evaluates the performance of deep recurrent neural networks in predicting heating demand for a commercial building over a medium-to-long term time horizon (≥ 1 week), and proposes a modeling framework to demonstrate how these longer-term predictions can be used to aid design of a strati... | Building Energy Modeling; Machine Learning; Recurrent Neural Networks; Deep Learning; Heating Load Prediction; Thermal Energy Storage | 2018 |
| 7 |
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Tran, Thomas T. D. | System scaling approach and thermoeconomic analysis of a pressure retarded osmosis system for power production with hypersaline draw solution: A Great Salt Lake study | Osmotic power with pressure retarded osmosis (PRO) is an emerging renewable energy option for locations where fresh water and salt water mix. Energy can be recovered from the salinity gradient between the solutions. This study provides a comprehensive feasibility analysis for a PRO power plant in a ... | Pressure retarded osmosis; Power generation; Renewable energy; Hydroelectric; Levelized cost | 2017-06 |
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