Fires caused by electric grid failures are increasing at an alarming rate with complex problems involving local and global factors such as rapid weather changes or failing infrastructure unable to keep up with power fluctuations. To deal with climate change, green power is rapidly coming online, but accepting renewables into the grid creates complex issues with reverse power flows. The Napa fires last year, and perhaps the recent California Camp fire, may have been ignited by such power fluctuations.
Michael Enescu and Peter Enescu examine the energy adaptive networks application previously used to monitor and control reverse power flows in microgrids and are now used to create a “planetary skin,” a mesh of devices that capture time-series data, analyze it in real time, and minimize power fluctuations in the grid. They highlight the system architecture, first deployments, examples, and collaboration required to address the challenge of gathering the data and analyzing it in real time reliably enough to take action to make communities safer, healthier, and more sustainable.
Michael Enescu is cofounder of Project EAN, responsible for the development of network virtualization technology based on smart grid research from Caltech. Previously, he was CTO of open source initiatives at Cisco, where he led the strategy and execution across the company’s top priorities in Cloud, IoT, and SDN. He led the formation of multiple projects in Eclipse, Apache, and Linux Foundation and won the Interop Grand Prize with Open Daylight, first time ever for an Open Source project. Previously he served as the first VP of Engineering at XenSource, a founding member of the Mobile Web Services group at Palm, and a founding member of the Java Content Partners Program and J2ME teams at Sun, a project that led to Android. Michael is a CS graduate from Caltech and Stanford University.
Peter Enescu is a researcher and software developer in smart energy and optimal power flow, a research project started at Caltech. He’s a CS student at the University of California, San Diego, specializing in data science and machine learning. Previously, he was an DB intern at IBM and an IoT developer at Energy Adaptive Networks. He’s an avid photographer, drone flyer, surfer, soccer fan, and YouTuber.
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