Machine learning energy consumption forecasting system
- Summary
- Roger N. Anderson, Ph.D.
- Technology Benefits
- Machine learning system becomes increasingly accurate over timeSystem integrates with electric vehicle (EV) charging station, and is scalable to cover thousands of EVsAllows manufacturing and processing facilities to avoid peak consumption penaltiesGreater efficiency in consuming electricity means facilities using the system can reduce capital expenses and extend the lifetime of capital equipmentPatent information:Patent Pending (WO/2013/023178)
- Technology Application
- Electricity consumption management for manufacturing and delivery facilitiesLoad prediction and assignments for electric vehicle recharging stationsEnergy management within power plants and smart gridsEnergy management and consumption predictions for municipalitiesL. Wu, G. Kaiser, D. Solomon, R. Winter, A. Boulanger, R. Anderson. Improving Efficiency and Reliability of Building Systems Using Machine Learning and Automated Online Evaluation. Systems, Applications and Technology Conference (LISAT), 2012 IEEE Long Island, May 4 2012, pp. 1-6.
- Detailed Technology Description
- Roger N. Anderson, Ph.D.
- *Abstract
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None
- *Inquiry
- Jay HickeyColumbia Technology VenturesTel: (212) 854-8444Email: TechTransfer@columbia.edu
- *IR
- CU13111
- *Principal Investigator
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- Country/Region
- USA
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