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Privacy-Preserving and Tractable Coordination Models for Active Loads in Smart Grids
Privacy-Preserving and Tractable Coordination Models for Active Loads in Smart Grids
The transition towards sustainable, distributed, and intelligent power systems necessitates effective coordination between transmission and distribution system operators (TSOs and DSOs). This project addresses the dual challenges of computational tractability and privacy in DSO-TSO coordination, by developing advanced data-driven decision-making models for harnessing the flexibility of distributed energy resources and active loads.
Image source: Ryan Said/Shutterstock.com
VIPES2X - Fully AI-driven Virtual Power Plant for Energy Storage and Power-to-X
VIPES2X - Fully AI-driven Virtual Power Plant for Energy Storage and Power-to-X
As the complexity of the energy system grows, so does the need for dimensioning assets such as batteries, electrolysers, and other types of energy storage, as well as the need to operate them efficiently in the grid to keep CO2 emissions and energy costs as low as possible. This project will develop a fully AI-driven Virtual Power Plant (VPP) using self-improving algorithms for operating energy storage and Power-to-X (P2X) systems in the most optimal way.
The project is supported by EUDP and runs from 2023 - 2025.
Image source: Ryan Said/Shutterstock.com
DigiWind
DigiWind
DigiWind is a pioneering EU-co-funded project, within the Digital Europe Programme (DEP), that aims to support Europe’s digital and green transformation. Through interdisciplinary Specialised Education Programmes (SEPs), DigiWind aims to future-proof the careers of Science, Technology, Engineering, and Math (STEM) professionals in renewable energy. The project will provide advanced digital skills in areas such as High-Performance Computing (HPC), Artificial Intelligence (AI), CyberSec, and other emerging technologies, aligning with the objectives of the DEP.
DigiWind drives excellence through dynamic cooperation and strategic partnerships, revolutionising education by significantly expanding geographic reach, gender inclusivity, and overall diversity for learners and educators. This is achieved through a robust modular system featuring three distinct learning journeys: Master of Science (M.Sc.) degrees, self-paced online Masters programs, and Lifelong Learning Modules.
AI-Powered Electricity Markets
AI-Powered Electricity Markets
Growing complexities in power systems have made market-clearing problems computationally challenging, and even intractable. Furthermore, the intrinsically limited cognitive capacity of human decision-makers to process complex information (so-called bounded rationality) further complicates market design. While AI-powered solutions to achieve efficient solutions may be attractive, the security-critical nature of power systems makes their implementation challenging. In this context, can we trust the decisions of AI-powered markets? This project will address this by designing trustworthy AI-powered electricity markets.
The project is funded by the La Cour Fellowship at DTU Wind and runs from 2023 - 2026.
Uncertainty Propagation and Systemic Risk Analysis in Energy Systems
Uncertainty Propagation and Systemic Risk Analysis in Energy Systems
Due to the tighter interdependencies between energy systems, uncertainty from weather-dependent energy resources is expected to propagate from the power system to other interconnected energy sectors, creating a risk for systemic instability, and, under worst case scenarios, leading to partial or total energy system failures. This project proposes to model this risk, by developing a range of mathematical models of uncertainty propagation, and to develop strategies to control them relying on the state-of-the-art applied probability, operations research, and energy system modelling.
The project is funded by the DTU Alliance program at DTU Wind and runs from 2024 - 2027.
Image source: Gade et. al. (2022)
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