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Benjamin F. Hobbs, the Theodore M. and Kay W. Schad Professor of Environmental Management, uses systems analysis and economics to improve electric utility planning, operations and policy, as well as management of environmental and water resources systems. Hobbs is founding director of Johns Hopkins’ Environment, Energy, Sustainability & Health Institute and holds a joint appointment in the Department of Applied Mathematics and Statistics. A member of the Johns Hopkins faculty since 1995, he is co-director of the USEPA Yale-JHU Solutions for Energy, Air, Climate, and Health (SEARCH) Center, an interdisciplinary team that studies how power generation trends, climate change and public policy interact to affect air quality.
As an example of his research, Hobbs’ lab is working with IBM’s Thomas J. Watson Research Center, the National Renewable Energy Laboratory, the University of Texas at Dallas, and two power grid operators on a project to better forecast sunshine and backup power needs. Traditional power suppliers now have to predict how much power a region will need a day in advance, potentially overestimating or underestimating demand. Hobbs’ project aims to significantly improve solar forecasting, using artificial intelligence and data analytics, so the nation’s grid operators know precisely, and in advance, how much power to produce for any given day and hour. They will test the system initially in California and in the central part of the United States.
As an example of his research, Hobbs’ lab is working with IBM’s Thomas J. Watson Research Center, the National Renewable Energy Laboratory, the University of Texas at Dallas, and two power grid operators on a project to better forecast sunshine and backup power needs. Traditional power suppliers now have to predict how much power a region will need a day in advance, potentially overestimating or underestimating demand. Hobbs’ project aims to significantly improve solar forecasting, using artificial intelligence and data analytics, so the nation’s grid operators know precisely, and in advance, how much power to produce for any given day and hour. They will test the system initially in California and in the central part of the United States.
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IEEE Transactions on Industry Applicationsno. 1 (2024): 1433-1441
2024 IEEE Texas Power and Energy Conference (TPEC)pp.1-6, (2024)
PROCEEDINGS OF THE 2023 THE 14TH ACM INTERNATIONAL CONFERENCE ON FUTURE ENERGY SYSTEMS, E-ENERGY 2023pp.324-332, (2023)
Renewable Energy Focus (2023): 100495-100495
Renewable and Sustainable Energy Reviews (2023): 113465-113465
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2023 IEEE Power & Energy Society General Meeting (PESGM)pp.1-5, (2023)
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