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validate the tools identified and/or developed, using as a reference case the remote training of grid operators in operational scenarios for power networks with a high penetration of renewable energy—one
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industry needs. One of the laboratories involved is the x-Energy Lab – SmartGrids and Electric Vehicles Laboratory, part of INESC TEC’s Centre for Power and Energy Systems.; It is in this context that INESC
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in hypervision, decision support systems, and AI agents applied to power grid operations (based on LF Energy's GridFM and OperatorFabric projects).; - Scenario modeling using real and synthetic data
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on artificial intelligence (AI) for energy systems and electrical grids - Execution of functional tests to validate the safety and robustness features of AI, taking into account the data-driven nature of AI and
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on artificial intelligence (AI) for energy systems and electrical grids ; - Execution of functional tests to validate the safety and robustness features of AI, taking into account the data-driven nature of AI and
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leveraging on AI and optimization, applying data science and analytics techniques. Such tools will support the integration of Distributed Energy Storage (DES) and Distributed Energy Resources (DER) in
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work on electricity and renewable energy markets, Advanced knowledge (specialization) in power systems. Preference factors: Experience in developing optimization problems and experience with GAMS
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Experience with power capping mechanisms; - Experience on the design and development of energy
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architectures for the energy and power management system on ships Develop control and dispatch strategies for hybrid microgrids, taking into account the specific power and energy requirements of ships Modeling
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intelligent surfaces ; - Identification and selection of the most adequate optimization methods to address the proposed workplan: ; - Develop the research skills through the application of the selected methods