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Thesis

Bridging probabilistic forecasts and power system optimization considering uncertainty: a joint chance-constrained perspective

Abstract:

Power systems globally are significantly integrating renewable energy to achieve net zero emission targets. Nonetheless, these renewable energy sources are weather-dependent and uncertain, bringing challenges to ensure operational reliability. Additionally, extreme weather and natural disasters damage power infrastructure, leading to contingencies or large-scale blackouts occasionally. These pressing issues necessitate uncertainty-aware power system management and give rise to the main res...

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Division:
MPLS
Department:
Engineering Science
Role:
Author

Contributors

Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Supervisor
Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Role:
Examiner
ORCID:
0000-0001-8865-8568
Institution:
Imperial College London
Role:
Examiner
ORCID:
0000-0002-1480-0282
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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