Identification of medical devices using machine learning on distribution feeder data for informing power outage response. (arXiv:2211.08310v1 [cs.LG])

Power outages caused by extreme weather events due to climate change have
doubled in the United States in the last two decades. Outages pose severe
health risks to over 4.4 million individuals dependent on in-home medical
devices. Data on the number of such individuals residing in a given area is
limited. This study proposes a load disaggregation model to predict the number
of medical devices behind an electric distribution feeder. This data can be
used to inform planning and response. …

arxiv data devices distribution identification machine machine learning medical medical devices outage power