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join the Sheffield Control and Power Systems (CAPS) Laboratory ( https://www.sheffield.ac.uk/acse/department/facilities/control-and-power-systems-lab ), led by Prof Xin Zhang as the Chair in Control and
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Master Thesis - Decoding Occupancy: Classifying User Activity from Building Power Consumption with Machine Learning At the Institute of Climate and Energy Systems Engineering (ICE-1) we focus on the
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Your Job The increasing complexity of future power systems, driven by renewable energy integration, power electronics, and distributed energy resources, requires computational methods capable of
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, and to support informed decision-making for integrated energy systems. Your tasks in detail: Analyze the impacts of future energy transition pathways on the planning and operation of European power and
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neural networks, and physics-informed machine learning in power systems Set up benchmark grids and generate or process suitable simulation data for power-flow, voltage-prediction, or state-estimation
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Systems on a research project investigating interactions between the power grid and turbine-generators, with Olkiluoto 3 nuclear power plant as the main case study. Olkiluoto 3 is one of the largest
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support informed decision-making for integrated energy systems. Your tasks in detail: Analyse the impacts of future energy transition pathways on the planning and operation of European power and gas
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Your Job The transition toward renewable and converter-interfaced energy resources is creating increasingly fast and complex dynamics in modern power systems. In this Master’s thesis, you will
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researcher to join the Department of Electrical Engineering and Automation at Aalto University, Finland. You will work in the Research Group of Power Transmission Systems on a research project
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charging systems. Proficiency in MATLAB and/or Python. Experience in student supervision and teaching. Preferred: Experience in dynamic modeling and simulation of power system components. Familiarity with