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    Investigation on Optimal Electric Energy Storage Capacity to Maximize Self-Consumption of Photovoltaic System 

    Source: Journal of Energy Resources Technology:;2021:;volume( 144 ):;issue: 007:;page 70903-1
    Author(s): Lee, Ruda; Lee, Hyomun; Kim, Dongsu; Yoon, Jongho
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Battery systems are critical factors in the effective use of renewable energy systems because the self-production of electricity by renewables for self-consumption has become profitable for building applications. This study ...
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    Potential Impacts of Net-Zero Energy Buildings With Distributed Photovoltaic Power Generation on the U.S. Electrical Grid 

    Source: Journal of Energy Resources Technology:;2019:;volume( 141 ):;issue: 006:;page 62005
    Author(s): Kim, Dongsu; Cho, Heejin; Luck, Rogelio
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This study evaluates the potential aggregate effects of net-zero energy building (NZEB) implementations on the electrical grid in a simulation-based analysis. To estimate the impact of NZEBs on the electrical grid, a ...
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    In-Situ Thermal Bridge Evaluation of a Building Using Bayesian Inference With Measured Infrared Thermography 

    Source: Journal of Energy Resources Technology:;2021:;volume( 144 ):;issue: 007:;page 70905-1
    Author(s): Kang, Eunho; Kim, Dongsu; Lee, Hyomoon; Yoon, Jongho
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Useful thermal bridge performance indicators (ITBs) of existing buildings may differ from calculated thermal bridge performance derived theoretically due to actual construction conditions, such as irregular shapes and ...
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    A Nonlinear Autoregressive With Exogenous Inputs Artificial Neural Network Model for Building Thermal Load Prediction 

    Source: Journal of Energy Resources Technology:;2020:;volume( 142 ):;issue: 005:;page 050902-1
    Author(s): Yu, Byeongho; Kim, Dongsu; Cho, Heejin; Mago, Pedro
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Thermal load prediction is a key part of energy system management and control in buildings, and its accuracy plays a critical role to improve building energy performance and efficiency. Regarding thermal load prediction, ...
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