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Smart grid, machine learning, Columbia


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Making a Smarter Power Grid

The DOE awarded Consolidated Edison Company of New York (ConEdison) $45 million for its Secure Interoperable Open Smart Grid Demonstration Project - one of the ARRA Smart Grid Demonstration Projects selected nationwide. As ConEdison's long time collaborator in R&D, Columbia University's Center for Computational Learning Systems (CCLS), led by director Dr. David L. Waltz, is working with ConEdison in making a smarter power grid that has the potential to not only eliminate the blackouts New York City residents endured and support emerging smarter technologies such as electric vehicles but also influence the way engineering is taught.

Smart Grid - image by flickr user: daveezaDr. Roger N. Anderson, the ConEdison Senior Scholar at Columbia Engineering and Lecturer in the Dept. of Earth and Environmental Sciences, is the PI. The project is "reducing to practice" a patented Adaptive Stochastic Controller (ASC) technology that was invented by Anderson and Senior Staff Associate Albert G. Boulanger. The ASC is an algorithm-based machine learning system with optimal decision making capabilities to detect power quality issues and predict emergency outages so that power can be distributed to where people need it, when they need it. In addition, the Smart Grid is designed to use power from as many green sources as possible, using photovoltaics, wind, battery storage, and other green sources from areas with less demand. The ASC manages load and sources control so that the light won't go out. It will also allow the Smart Grid to anticipate and respond automatically to problem events such as weather changes and equipment failures in order to prevent cas cading power outages. Another patent pending technology named Metrics Monitoring & Financial Validation System for Smart Grid management, invented by Anderson, Senior Staff Associate Leon L. Wu and Albert Boulanger, will be used to help control center operators manage the systems more efficiently and economically.

Roger N. Anderson (Columbia University)

Agencies (that have supported the research):
Columbia University - Center for Computational Learning Systems, U.S. Department of Energy


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