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About The Position
The Grid Interactive Controls (GIC) Group in the Electrification and Energy Infrastructure Division (EEID) at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral Research Associate. This group specializes in pioneering innovations at the edge of today's power grid, focusing on enhancing grid security, reliability, resilience, and advancing decarbonization. The primary focus is on comprehensive ‘Everything-to-Grid' (X2G) strategies, developing cutting-edge solutions in grid-edge integration and control. The GIC Group is committed to seamlessly incorporating emerging distributed energy resources, including demand response, which are crucial for the reliable operation of the grid. The research involves a diverse range of disciplines such as urban modeling, control theory, optimization, economics, game theory, data analytics, and machine learning, aimed at understanding intricate grid-edge interactions and operations. The urban energy modeling team within the GIC Group has created and simulated a model of every U.S. building, involving urban-scale building energy modeling at the resolution of individual buildings and at the scale of nations. This work analyzes building codes, energy efficiency, demand response, and climate change impacts towards a sustainable and resilient built environment. The team has achieved significant milestones, including the world-first simulation of 125.7 million U.S. buildings and the public release of 122.9 million building energy models. They are actively improving the Automatic Building Energy Modeling (AutoBEM) software suite, which involves big data processing, data analytics, machine learning, and high-performance computing resources to create, model, simulate, validate, and analyze building performance. The successful candidate will be expected to conduct independent research under general guidance, prepare manuscripts for scientific publication, and present findings at conferences. The role requires the development of innovative software techniques, knowledge of building energy modeling, and frequent collaboration with a multi-disciplinary team of researchers from various sectors. The candidate will assist in the development and implementation of data organization and software development for scalable use and analysis of business-sensitive data, supporting senior R&D staff in various innovative projects.
