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Browsing by Author "Li, Jiale"

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    Bloom and Doom
    Li, Jiale (Virginia Tech, 2024-05-24)
    This thesis harnesses 3D modeling to present a contrasting world through Maya 3D models, Substance Painter textures, and Adobe's audio-visual editing tools. Influenced by my childhood experiences and cultural history, the project contrasts the natural environment with a polluted, urban landscape. The paper also discusses future expansions aiming to enhance interactivity and deepening the narrative on human environmental impact.
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    Model and Procedures for Reliable Near Term Wind Energy Production Forecast
    Li, Jiale; Yu, Xiong (Virginia Tech, 2015-06)
    Accurate and reliable prediction of wind energy production is important for the operational management of wind farm as well as for the stability of electrical grid with renewable energy integration. This paper describes a model and procedure that accurately predict wind energy production using weather forecast. An aerodynamic model is used to predict the wind speed distribution with elevation from the 24 hour forecasted wind speeds at three hours intervals. The model considers the effects of factors such as ground topology, land cover, etc. on the wind speed distribution. Therefore, it is applicable for different types of territories. The simulated wind speed, at time interval of 15 minutes, is then used together with the factory or calibrated turbine production curve to predict the energy production in 24 hours. The model and procedures for wind energy production forecast are validated on a 100kw prototype research wind turbine installed on the campus of CWRU. The actual energy production data in different seasons from the prototype wind turbine was analyzed and compared with that by model forecast. It was found this new model-based forecast method provide more reliable and accurate prediction of wind energy production, compared with alternative methods. The potential application of this wind energy forecast method include to improve the management of wind farm operations, to evaluate the electric power storage demand, to optimize the market values of wind energy , and to assist the electric grid integration of renewable energies.