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SUMMARY:FREEDM Tech Webinar Series: Residential Load Profile Super-Resolution using Generative Adversarial Networks
DESCRIPTION:Presenter: Lidong Song\, Ph.D. Student \nVIEW THE RECORDING HERE.\nIt is a common practice for utilities to down-sample smart meter measurements from high resolution (e.g. 1-min or 1-sec) to low resolution (e.g. 15-\, 30- or 60-min) to lower the data transmission and storage cost. However\, down-sampling can remove high-frequency components from time-series load profiles\, making them unsuitable for in-depth studies such as quasi-static power flow analysis or non-intrusive load monitoring (NILM). This presentation will review a Generative Adversarial Network (GAN) based load profile super-resolution (LPSR) framework for restoring high-frequency components lost through the smoothing effect of the down-sampling process. This method outperforms the traditional Mean Square Error (MSE) based super-resolution methods. Improving LPSR in this way can reduce utility costs while still leveraging the benefits of smart meter measurements. \n 
URL:https://www.freedm.ncsu.edu/event/freedm-tech-webinar-series-a-gan-based-super-resolution-method-for-generating-high-resolution-load-profiles/
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